{"id":213,"date":"2024-03-04T00:50:45","date_gmt":"2024-03-03T16:50:45","guid":{"rendered":"http:\/\/tobykskgd.life\/?p=213"},"modified":"2024-11-14T22:14:35","modified_gmt":"2024-11-14T14:14:35","slug":"09","status":"publish","type":"post","link":"https:\/\/tobykskgd.life\/index.php\/09\/","title":{"rendered":"\u674e\u5b8f\u6bc5\u673a\u5668\u5b66\u4e60\u8bfe\u7a0b\u7b14\u8bb0EP5"},"content":{"rendered":"\n

\u3010HW1\u3011Regression0.1\u674e\u5b8f\u6bc52021\/2022\u6625\u673a\u5668\u5b66\u4e60\u8bfe\u7a0b\u7b14\u8bb0EP5(P11-P12)<\/p>\n\n\n\n

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\u90a3\u4e48\u9996\u5148\u8fd9\u95e8\u8bfe\u7a0b\u9700\u8981\u6709\u4e00\u5b9a\u7684\u4ee3\u7801\u57fa\u7840\uff0c\u7b80\u5355\u5b66\u4e60\u4e00\u4e0bPython\u7684\u57fa\u672c\u7528\u6cd5\uff0c\u8fd8\u6709\u91cc\u9762\u7684NumPy\u5e93\u7b49\u7b49\u7684\u57fa\u672c\u77e5\u8bc6\u3002\u518d\u5c31\u662f\u6570\u5b66\u65b9\u9762\u7684\u57fa\u7840\u5566\uff0c\u5fae\u79ef\u5206\u3001\u7ebf\u6027\u4ee3\u6570\u548c\u6982\u7387\u8bba\u7684\u57fa\u7840\u90fd\u662f\u542c\u61c2\u8fd9\u95e8\u8bfe\u5fc5\u987b\u7684\u3002<\/p>\n\n\n\n

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\u8fd9\u91cc\u662f\u8fd9\u95e8\u8bfe\u7a0b\u7684\u4f5c\u4e1a1\uff0c\u90a3\u56e0\u4e3a\u672c\u4eba\u6bd4\u8f83\u5e9f\uff0c\u57fa\u7840\u8fd8\u6ca1\u6709\u5f88\u597d\uff0c\u8fd9\u91cc\u5148\u653e\u4e00\u4e2a\u57fa\u672c\u6ca1\u6709\u4ec0\u4e48\u6539\u52a8\u7684\u52a9\u6559\u7684\u7a0b\u5e8f\u4f5c\u4e3aHW1\u76840.1\u7248\u672c\uff0c\u8fd9\u91cc\u56e0\u4e3a\u6ca1\u6709\u4ec0\u4e48\u6539\u52a8\uff0c\u8fd9\u4e2amodel\u4e5f\u5f88\u5e9f\u5566\uff0c\u8fd9\u91cc\u7684loss\u6bd4\u8f83\u5927\u3002\u7b49\u4e4b\u540e\u6709\u4e86\u6570\u5b66\u548c\u7a0b\u5e8f\u4e0a\u7684\u57fa\u7840\u4e4b\u540e\uff0c\u4e00\u5b9a\u4f1a\u56de\u6765\u8865\u4e00\u4e2a\u6548\u679c\u597d\u4e00\u70b9\u76841.0\u7248\u672c\uff01<\/p>\n\n\n\n

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# \u4e0b\u8f7d\u6570\u636e\n!gdown --id '1kLSW_-cW2Huj7bh84YTdimGBOJaODiOS' --output covid.train.csv\n!gdown --id '1iiI5qROrAhZn-o4FPqsE97bMzDEFvIdg' --output covid.test.csv<\/code><\/pre>\n\n\n\n
\/usr\/local\/lib\/python3.10\/dist-packages\/gdown\/cli.py:138: FutureWarning: Option `–id` was deprecated in version 4.3.1 and will be removed in 5.0. You don’t need to pass it anymore to use a file ID. warnings.warn( Downloading… From: https:\/\/drive.google.com\/uc?id=1kLSW_-cW2Huj7bh84YTdimGBOJaODiOS<\/a> To: \/content\/covid.train.csv 100% 2.49M\/2.49M [00:00<00:00, 171MB\/s] \/usr\/local\/lib\/python3.10\/dist-packages\/gdown\/cli.py:138: FutureWarning: Option `–id` was deprecated in version 4.3.1 and will be removed in 5.0. You don’t need to pass it anymore to use a file ID. warnings.warn( Downloading… From: https:\/\/drive.google.com\/uc?id=1iiI5qROrAhZn-o4FPqsE97bMzDEFvIdg<\/a> To: \/content\/covid.test.csv 100% 993k\/993k [00:00<00:00, 117MB\/s]<\/p>\n\n\n\n
\u5bfc\u5165\u5305<\/p>\n\n\n\n
# \u5bfc\u5165\u5fc5\u8981\u7684\u5305\n# \u6570\u636e\u7684\u64cd\u4f5c\nimport math\nimport numpy as np\n\n# \u8bfb\u53d6\u548c\u5199\u5165\u6570\u636e\nimport pandas as pd\nimport os\nimport csv\n\n# \u8fdb\u5ea6\u6761\nfrom tqdm import tqdm\n\n# Pytorch\nimport torch\nimport torch.nn as nn\nfrom torch.utils.data import Dataset, DataLoader, random_split\n\n# \u7ed8\u56fe\nfrom torch.utils.tensorboard import SummaryWriter<\/code><\/pre>\n\n\n\n
\u4e00\u4e9b\u91cd\u8981\u51fd\u6570\u7684\u5b9a\u4e49<\/p>\n\n\n\n
# \u4e00\u4e9b\u91cd\u8981\u7684\u51fd\u6570\uff08\u65e0\u9700\u4fee\u6539\u6b64\u5904\u4ee3\u7801\uff09\ndef same_seed(seed):\n    '''Fixes random number generator seeds for reproducibility.'''\n    torch.backends.cudnn.deterministic = True\n    torch.backends.cudnn.benchmark = False\n    np.random.seed(seed)\n    torch.manual_seed(seed)\n    if torch.cuda.is_available():\n        torch.cuda.manual_seed_all(seed)\n\ndef train_valid_split(data_set, valid_ratio, seed):\n    '''Split provided training data into training set and validation set'''\n    valid_set_size = int(valid_ratio * len(data_set))\n    train_set_size = len(data_set) - valid_set_size\n    train_set, valid_set = random_split(data_set, [train_set_size, valid_set_size], generator=torch.Generator().manual_seed(seed))\n    return np.array(train_set), np.array(valid_set)\n\ndef predict(test_loader, model, device):\n    model.eval() # \u5c06\u6a21\u578b\u8bbe\u7f6e\u4e3a\u8bc4\u4ef7\u6a21\u5f0f.\n    preds = []\n    for x in tqdm(test_loader):\n        x = x.to(device)\n        with torch.no_grad():\n            pred = model(x)\n            preds.append(pred.detach().cpu())\n    preds = torch.cat(preds, dim=0).numpy()\n    return preds<\/code><\/pre>\n\n\n\n
dataset<\/p>\n\n\n\n
# dataset\nclass COVID19Dataset(Dataset):\n    '''\n    x: Features.\n    y: Targets, if none, do prediction.\n    '''\n    def __init__(self, x, y=None):\n        if y is None:\n            self.y = y\n        else:\n            self.y = torch.FloatTensor(y)\n        self.x = torch.FloatTensor(x)\n\n    def __getitem__(self, idx):\n        if self.y is None:\n            return self.x[idx]\n        else:\n            return self.x[idx], self.y[idx]\n\n    def __len__(self):\n        return len(self.x)<\/code><\/pre>\n\n\n\n
\u795e\u7ecf\u7f51\u7edc\u6a21\u578b<\/p>\n\n\n\n
class My_Model(nn.Module):\n    def __init__(self, input_dim):\n        super(My_Model, self).__init__()\n        # TODO: modify model's structure, be aware of dimensions.\n        self.layers = nn.Sequential(\n            nn.Linear(input_dim, 64),\n            nn.BatchNormld(64),\n            nn.Linear(16, 8),\n            nn.ReLU(),\n            nn.Linear(8, 1)\n        )\n\n    def forward(self, x):\n        x = self.layers(x)\n        x = x.squeeze(1) # (B, 1) -> (B)\n        return x<\/code><\/pre>\n\n\n\n
# feature\u9009\u62e9\uff08\u6b64\u5904\u9700\u8981\u4fee\u6539\u4ee3\u7801\uff0c\u9009\u62e9\u5408\u9002\u7684\uff09\ndef select_feat(train_data, valid_data, test_data, select_all=True):\n    '''Selects useful features to perform regression'''\n    y_train, y_valid = train_data[:,-1], valid_data[:,-1]\n    raw_x_train, raw_x_valid, raw_x_test = train_data[:,:-1], valid_data[:,:-1], test_data\n\n    if select_all:\n        feat_idx = list(range(raw_x_train.shape[1]))\n    else:\n        feat_idx = [0,1,2,3,4] # TODO: Select suitable feature columns.\n\n    return raw_x_train[:,feat_idx], raw_x_valid[:,feat_idx], raw_x_test[:,feat_idx], y_train, y_valid<\/code><\/pre>\n\n\n\n
\u5f00\u59cb\u8bad\u7ec3<\/p>\n\n\n\n
# \u8bad\u7ec3\u5faa\u73af\ndef trainer(train_loader, valid_loader, model, config, device):\n\n    criterion = nn.MSELoss(reduction='mean') # Define your loss function, do not modify this.\n\n    # Define your optimization algorithm.\n    # TODO: Please check https:\/\/pytorch.org\/docs\/stable\/optim.html to get more available algorithms.\n    # TODO: L2 regularization (optimizer(weight decay...) or implement by your self).\n    optimizer = torch.optim.SGD(model.parameters(), lr=config['learning_rate'], momentum=0.9)\n\n    writer = SummaryWriter() # Writer of tensoboard.\n\n    if not os.path.isdir('.\/models'):\n        os.mkdir('.\/models') # Create directory of saving models.\n\n    n_epochs, best_loss, step, early_stop_count = config['n_epochs'], math.inf, 0, 0\n\n    for epoch in range(n_epochs):\n        model.train() # Set your model to train mode.\n        loss_record = []\n\n        # tqdm is a package to visualize your training progress.\n        train_pbar = tqdm(train_loader, position=0, leave=True)\n\n        for x, y in train_pbar:\n            optimizer.zero_grad()               # Set gradient to zero.\n            x, y = x.to(device), y.to(device)   # Move your data to device.\n            pred = model(x)\n            loss = criterion(pred, y)\n            loss.backward()                     # Compute gradient(backpropagation).\n            optimizer.step()                    # Update parameters.\n            step += 1\n            loss_record.append(loss.detach().item())\n\n            # Display current epoch number and loss on tqdm progress bar.\n            train_pbar.set_description(f'Epoch [{epoch+1}\/{n_epochs}]')\n            train_pbar.set_postfix({'loss': loss.detach().item()})\n\n        mean_train_loss = sum(loss_record)\/len(loss_record)\n        writer.add_scalar('Loss\/train', mean_train_loss, step)\n\n        model.eval() # \u5c06\u6a21\u578b\u8bbe\u7f6e\u4e3a\u8bc4\u4f30\u6a21\u5f0f\n        loss_record = []\n        for x, y in valid_loader:\n            x, y = x.to(device), y.to(device)\n            with torch.no_grad():\n                pred = model(x)\n                loss = criterion(pred, y)\n\n            loss_record.append(loss.item())\n\n        mean_valid_loss = sum(loss_record)\/len(loss_record)\n        print(f'Epoch [{epoch+1}\/{n_epochs}]: Train loss: {mean_train_loss:.4f}, Valid loss: {mean_valid_loss:.4f}')\n        writer.add_scalar('Loss\/valid', mean_valid_loss, step)\n\n        if mean_valid_loss < best_loss:\n            best_loss = mean_valid_loss\n            torch.save(model.state_dict(), config['save_path']) # \u4fdd\u5b58\u6548\u679c\u6700\u597d\u7684model\n            print('Saving model with loss {:.3f}...'.format(best_loss))\n            early_stop_count = 0\n        else:\n            early_stop_count += 1\n\n        if early_stop_count >= config['early_stop']:\n            print('\\nModel is not improving, so we halt the training session.')\n            return<\/code><\/pre>\n\n\n\n
# \u914d\u7f6e\ndevice = 'cuda' if torch.cuda.is_available() else 'cpu'\nconfig = {\n    'seed': 5201314,      # Your seed number, you can pick your lucky number. :)\n    'select_all': True,   # Whether to use all features.\n    'valid_ratio': 0.2,   # validation_size = train_size * valid_ratio\n    'n_epochs': 3000,     # Number of epochs.\n    'batch_size': 256,\n    'learning_rate': 1e-5,\n    'early_stop': 400,    # If model has not improved for this many consecutive epochs, stop training.\n    'save_path': '.\/models\/model.ckpt'  # Your model will be saved here.\n}<\/code><\/pre>\n\n\n\n
# \u4ece\u6587\u4ef6\u4e2d\u8bfb\u53d6\u8bad\u7ec3\u3001\u9a8c\u8bc1\u548c\u6d4b\u8bd5\u96c6\uff08\u6b64\u5904\u4ee3\u7801\u4e0d\u9700\u8981\u4fee\u6539\uff09\n# Set seed for reproducibility\nsame_seed(config['seed'])\n\n\n# train_data size: 2699 x 118 (id + 37 states + 16 features x 5 days)\n# test_data size: 1078 x 117 (without last day's positive rate)\ntrain_data, test_data = pd.read_csv('.\/covid.train.csv').values, pd.read_csv('.\/covid.test.csv').values\ntrain_data, valid_data = train_valid_split(train_data, config['valid_ratio'], config['seed'])\n\n# Print out the data size.\nprint(f\"\"\"train_data size: {train_data.shape}\nvalid_data size: {valid_data.shape}\ntest_data size: {test_data.shape}\"\"\")\n\n# Select features\nx_train, x_valid, x_test, y_train, y_valid = select_feat(train_data, valid_data, test_data, config['select_all'])\n\n# Print out the number of features.\nprint(f'number of features: {x_train.shape[1]}')\n\ntrain_dataset, valid_dataset, test_dataset = COVID19Dataset(x_train, y_train), \\\n                                            COVID19Dataset(x_valid, y_valid), \\\n                                            COVID19Dataset(x_test)\n\n# Pytorch data loader loads pytorch dataset into batches.\ntrain_loader = DataLoader(train_dataset, batch_size=config['batch_size'], shuffle=True, pin_memory=True)\nvalid_loader = DataLoader(valid_dataset, batch_size=config['batch_size'], shuffle=True, pin_memory=True)\ntest_loader = DataLoader(test_dataset, batch_size=config['batch_size'], shuffle=False, pin_memory=True)<\/code><\/pre>\n\n\n\n
train_data size: (2160, 118) valid_data size: (539, 118) test_data size: (1078, 117) number of features: 117<\/p>\n\n\n\n
# \u5f00\u59cb\u8bad\u7ec3\nmodel = My_Model(input_dim=x_train.shape[1]).to(device) # put your model and data on the same computation device.\ntrainer(train_loader, valid_loader, model, config, device)<\/code><\/pre>\n\n\n\n
Epoch [1\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 40.58it\/s, loss=60.4] Epoch [1\/3000]: Train loss: 134.2442, Valid loss: 107.2154 Saving model with loss 107.215… Epoch [2\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.90it\/s, loss=65.9] Epoch [2\/3000]: Train loss: 69.8928, Valid loss: 50.8182 Saving model with loss 50.818… Epoch [3\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.13it\/s, loss=61.8] Epoch [3\/3000]: Train loss: 48.5299, Valid loss: 39.1161 Saving model with loss 39.116… Epoch [4\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.36it\/s, loss=42] Epoch [4\/3000]: Train loss: 39.2690, Valid loss: 39.9759 Epoch [5\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.29it\/s, loss=37.6] Epoch [5\/3000]: Train loss: 34.3680, Valid loss: 34.5855 Saving model with loss 34.586… Epoch [6\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.68it\/s, loss=35.4] Epoch [6\/3000]: Train loss: 32.7019, Valid loss: 34.4896 Saving model with loss 34.490… Epoch [7\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.51it\/s, loss=30.4] Epoch [7\/3000]: Train loss: 31.6557, Valid loss: 32.7823 Saving model with loss 32.782… Epoch [8\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.79it\/s, loss=31.8] Epoch [8\/3000]: Train loss: 31.0152, Valid loss: 28.5507 Saving model with loss 28.551… Epoch [9\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.02it\/s, loss=28.6] Epoch [9\/3000]: Train loss: 30.0828, Valid loss: 29.0465 Epoch [10\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.99it\/s, loss=30] Epoch [10\/3000]: Train loss: 29.1485, Valid loss: 29.9683 Epoch [11\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.27it\/s, loss=30.9] Epoch [11\/3000]: Train loss: 27.2044, Valid loss: 34.4240 Epoch [12\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.17it\/s, loss=28.5] Epoch [12\/3000]: Train loss: 30.4587, Valid loss: 30.5449 Epoch [13\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.42it\/s, loss=26.4] Epoch [13\/3000]: Train loss: 28.8501, Valid loss: 38.8157 Epoch [14\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.90it\/s, loss=25.9] Epoch [14\/3000]: Train loss: 30.4944, Valid loss: 23.6369 Saving model with loss 23.637… Epoch [15\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.32it\/s, loss=20] Epoch [15\/3000]: Train loss: 22.0876, Valid loss: 21.6633 Saving model with loss 21.663… Epoch [16\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.32it\/s, loss=27.3] Epoch [16\/3000]: Train loss: 21.9709, Valid loss: 21.4195 Saving model with loss 21.419… Epoch [17\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.66it\/s, loss=18.6] Epoch [17\/3000]: Train loss: 18.8818, Valid loss: 17.4514 Saving model with loss 17.451… Epoch [18\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 64.24it\/s, loss=16.5] Epoch [18\/3000]: Train loss: 19.4508, Valid loss: 16.2921 Saving model with loss 16.292… Epoch [19\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.20it\/s, loss=18.7] Epoch [19\/3000]: Train loss: 17.1156, Valid loss: 12.4207 Saving model with loss 12.421… Epoch [20\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.92it\/s, loss=16.1] Epoch [20\/3000]: Train loss: 14.4296, Valid loss: 12.4151 Saving model with loss 12.415… Epoch [21\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.48it\/s, loss=11.5] Epoch [21\/3000]: Train loss: 12.4319, Valid loss: 10.2072 Saving model with loss 10.207… Epoch [22\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.95it\/s, loss=8.66] Epoch [22\/3000]: Train loss: 9.8818, Valid loss: 8.9822 Saving model with loss 8.982… Epoch [23\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.78it\/s, loss=9.7] Epoch [23\/3000]: Train loss: 9.4213, Valid loss: 8.1968 Saving model with loss 8.197… Epoch [24\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.83it\/s, loss=5.93] Epoch [24\/3000]: Train loss: 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Valid loss: 5.7169 Epoch [82\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.31it\/s, loss=6.68] Epoch [82\/3000]: Train loss: 5.2744, Valid loss: 4.3004 Epoch [83\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.45it\/s, loss=4.63] Epoch [83\/3000]: Train loss: 4.8566, Valid loss: 5.8771 Epoch [84\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.69it\/s, loss=6.3] Epoch [84\/3000]: Train loss: 5.5020, Valid loss: 5.1094 Epoch [85\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.03it\/s, loss=5.91] Epoch [85\/3000]: Train loss: 5.0469, Valid loss: 4.6944 Epoch [86\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.75it\/s, loss=5.93] Epoch [86\/3000]: Train loss: 5.2458, Valid loss: 5.7958 Epoch [87\/3000]: 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100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.70it\/s, loss=4.03] Epoch [297\/3000]: Train loss: 3.3919, Valid loss: 4.1198 Epoch [298\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.64it\/s, loss=2.86] Epoch [298\/3000]: Train loss: 3.7716, Valid loss: 2.9484 Epoch [299\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.43it\/s, loss=2.92] Epoch [299\/3000]: Train loss: 2.8516, Valid loss: 3.2554 Epoch [300\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.21it\/s, loss=3.31] Epoch [300\/3000]: Train loss: 3.2842, Valid loss: 2.4619 Saving model with loss 2.462… Epoch [301\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.29it\/s, loss=2.58] Epoch [301\/3000]: Train loss: 2.8510, Valid loss: 2.5666 Epoch [302\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.90it\/s, loss=3.09] Epoch [302\/3000]: Train loss: 2.9875, Valid loss: 3.6627 Epoch [303\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.91it\/s, loss=3.04] Epoch [303\/3000]: Train loss: 2.8602, Valid loss: 3.0794 Epoch [304\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 17.26it\/s, loss=3.62] Epoch [304\/3000]: Train loss: 3.0934, Valid loss: 3.1227 Epoch [305\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.22it\/s, loss=3.05] Epoch [305\/3000]: Train loss: 2.9018, Valid loss: 3.5898 Epoch [306\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.51it\/s, loss=5.66] Epoch [306\/3000]: Train loss: 3.7750, Valid loss: 6.7416 Epoch [307\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.12it\/s, loss=3.58] Epoch [307\/3000]: Train loss: 3.6324, Valid loss: 3.5795 Epoch [308\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.77it\/s, loss=3.14] Epoch [308\/3000]: Train loss: 2.9955, Valid loss: 2.8809 Epoch [309\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.11it\/s, loss=2.49] Epoch [309\/3000]: Train loss: 3.2752, Valid loss: 2.6057 Epoch [310\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.61it\/s, loss=1.99] Epoch [310\/3000]: Train loss: 2.9320, Valid loss: 3.1684 Epoch [311\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 100.11it\/s, loss=2.7] Epoch [311\/3000]: Train loss: 3.0372, Valid loss: 3.4146 Epoch [312\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.38it\/s, loss=2.94] Epoch [312\/3000]: Train loss: 3.0822, Valid loss: 3.1031 Epoch [313\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.26it\/s, loss=4.25] Epoch [313\/3000]: Train loss: 2.9853, Valid loss: 2.6593 Epoch [314\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.34it\/s, loss=3.34] Epoch [314\/3000]: Train loss: 3.3308, Valid loss: 3.5130 Epoch [315\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.65it\/s, loss=4.14] Epoch [315\/3000]: Train loss: 3.0278, Valid loss: 4.1210 Epoch [316\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 103.05it\/s, loss=3.27] Epoch [316\/3000]: Train loss: 3.0554, Valid loss: 3.1320 Epoch [317\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.30it\/s, loss=2.88] Epoch [317\/3000]: Train loss: 3.8156, Valid loss: 6.4564 Epoch [318\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.42it\/s, loss=3.81] Epoch [318\/3000]: Train loss: 4.0646, Valid loss: 3.9689 Epoch [319\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.10it\/s, loss=3.45] Epoch [319\/3000]: Train loss: 3.8134, Valid loss: 4.4446 Epoch [320\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.15it\/s, loss=5.61] Epoch [320\/3000]: Train loss: 4.2660, Valid loss: 3.9781 Epoch [321\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.71it\/s, loss=7.95] Epoch [321\/3000]: Train loss: 5.3725, Valid loss: 4.8789 Epoch [322\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.98it\/s, loss=2.5] Epoch [322\/3000]: Train loss: 4.2666, Valid loss: 3.1405 Epoch [323\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.63it\/s, loss=2.4] Epoch [323\/3000]: Train loss: 2.8328, Valid loss: 2.6067 Epoch [324\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.01it\/s, loss=3] Epoch [324\/3000]: Train loss: 2.9509, Valid loss: 2.9684 Epoch [325\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.82it\/s, loss=2.52] Epoch [325\/3000]: Train loss: 3.4400, Valid loss: 5.6546 Epoch [326\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.48it\/s, loss=8.67] Epoch [326\/3000]: Train loss: 4.4679, Valid loss: 6.1391 Epoch [327\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.58it\/s, loss=2.98] Epoch [327\/3000]: Train loss: 3.8706, Valid loss: 5.8560 Epoch [328\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.91it\/s, loss=6.55] Epoch [328\/3000]: Train loss: 5.0640, Valid loss: 4.4458 Epoch [329\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.18it\/s, loss=2.26] Epoch [329\/3000]: Train loss: 3.2477, Valid loss: 4.2497 Epoch [330\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.25it\/s, loss=2.77] Epoch [330\/3000]: Train loss: 2.8118, Valid loss: 3.4926 Epoch [331\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.28it\/s, loss=3.38] Epoch [331\/3000]: Train loss: 3.4455, Valid loss: 4.2721 Epoch [332\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 103.26it\/s, loss=6.75] Epoch [332\/3000]: Train loss: 3.7624, Valid loss: 5.2285 Epoch [333\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.59it\/s, loss=2.47] Epoch [333\/3000]: Train loss: 3.4638, Valid loss: 2.9239 Epoch [334\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 101.76it\/s, loss=2.53] Epoch [334\/3000]: Train loss: 2.9495, Valid loss: 3.4138 Epoch [335\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 104.86it\/s, loss=2.5] Epoch [335\/3000]: Train loss: 2.8287, Valid loss: 2.4784 Epoch [336\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.09it\/s, loss=2.51] Epoch [336\/3000]: Train loss: 2.6776, Valid loss: 2.8056 Epoch [337\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.99it\/s, loss=2.33] Epoch [337\/3000]: Train loss: 2.8702, Valid loss: 3.7128 Epoch [338\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.20it\/s, loss=3.19] Epoch [338\/3000]: Train loss: 3.2051, Valid loss: 3.6362 Epoch [339\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.32it\/s, loss=3.24] Epoch [339\/3000]: Train loss: 3.0094, Valid loss: 2.7970 Epoch [340\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.00it\/s, loss=3.85] Epoch [340\/3000]: Train loss: 3.4108, Valid loss: 2.7561 Epoch [341\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.24it\/s, loss=3.24] Epoch [341\/3000]: Train loss: 3.5041, Valid loss: 3.1119 Epoch [342\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.53it\/s, loss=3.6] Epoch [342\/3000]: Train loss: 4.1326, Valid loss: 11.2525 Epoch [343\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.41it\/s, loss=3.6] Epoch [343\/3000]: Train loss: 4.7742, Valid loss: 3.1641 Epoch [344\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.24it\/s, loss=3.21] Epoch [344\/3000]: Train loss: 3.4504, Valid loss: 3.7801 Epoch [345\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.35it\/s, loss=3.43] Epoch [345\/3000]: Train loss: 2.9553, Valid loss: 3.4663 Epoch [346\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.49it\/s, loss=2.08] Epoch [346\/3000]: Train loss: 2.8073, Valid loss: 2.8425 Epoch [347\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.33it\/s, loss=3.62] Epoch [347\/3000]: Train loss: 3.2338, Valid loss: 4.0943 Epoch [348\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.96it\/s, loss=3.95] Epoch [348\/3000]: Train loss: 3.5725, Valid loss: 6.5409 Epoch [349\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.87it\/s, loss=2.48] Epoch [349\/3000]: Train loss: 5.9774, Valid loss: 6.9343 Epoch [350\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.16it\/s, loss=4.26] Epoch [350\/3000]: Train loss: 5.5974, Valid loss: 7.4151 Epoch [351\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.40it\/s, loss=6.45] Epoch [351\/3000]: Train loss: 5.8096, Valid loss: 5.4890 Epoch [352\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.49it\/s, loss=3.12] Epoch [352\/3000]: Train loss: 3.4961, Valid loss: 2.9939 Epoch [353\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.59it\/s, loss=2.82] Epoch [353\/3000]: Train loss: 3.2390, Valid loss: 5.7079 Epoch [354\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.60it\/s, loss=6.18] Epoch [354\/3000]: Train loss: 4.4285, Valid loss: 3.4510 Epoch [355\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 88.66it\/s, loss=3.26] Epoch [355\/3000]: Train loss: 3.3214, Valid loss: 2.9046 Epoch [356\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.49it\/s, loss=3.5] Epoch [356\/3000]: Train loss: 3.5557, Valid loss: 3.7571 Epoch [357\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.08it\/s, loss=3.82] Epoch [357\/3000]: Train loss: 3.5230, Valid loss: 2.9421 Epoch [358\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.87it\/s, loss=2.27] Epoch [358\/3000]: Train loss: 2.7578, Valid loss: 3.9499 Epoch [359\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.01it\/s, loss=3.1] Epoch [359\/3000]: Train loss: 2.9557, Valid loss: 4.1616 Epoch [360\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.86it\/s, loss=3.69] Epoch [360\/3000]: Train loss: 3.0305, Valid loss: 2.9928 Epoch [361\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.87it\/s, loss=2.51] Epoch [361\/3000]: Train loss: 2.9525, Valid loss: 3.5110 Epoch [362\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.75it\/s, loss=2.56] Epoch [362\/3000]: Train loss: 2.6036, Valid loss: 2.9102 Epoch [363\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.49it\/s, loss=2.27] Epoch [363\/3000]: Train loss: 2.8204, Valid loss: 2.6886 Epoch [364\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.62it\/s, loss=2.62] Epoch [364\/3000]: Train loss: 2.6462, Valid loss: 3.1595 Epoch [365\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 39.24it\/s, loss=4.05] Epoch [365\/3000]: Train loss: 3.2701, Valid loss: 4.8460 Epoch [366\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 22.92it\/s, loss=3.09] Epoch [366\/3000]: Train loss: 3.4968, Valid loss: 2.6863 Epoch [367\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.79it\/s, loss=2.31] Epoch [367\/3000]: Train loss: 2.9613, Valid loss: 2.5769 Epoch [368\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 104.36it\/s, loss=3.3] Epoch [368\/3000]: Train loss: 3.1499, Valid loss: 3.0976 Epoch [369\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 100.33it\/s, loss=5.59] Epoch [369\/3000]: Train loss: 3.8831, Valid loss: 4.7759 Epoch [370\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.85it\/s, loss=3.25] Epoch [370\/3000]: Train loss: 3.9875, Valid loss: 3.3788 Epoch [371\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 24.18it\/s, loss=2.78] Epoch [371\/3000]: Train loss: 2.8503, Valid loss: 3.0923 Epoch [372\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 38.00it\/s, loss=2.29] Epoch [372\/3000]: Train loss: 2.6553, Valid loss: 2.7460 Epoch [373\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.98it\/s, loss=3.34] Epoch [373\/3000]: Train loss: 2.9150, Valid loss: 2.9464 Epoch [374\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.01it\/s, loss=3.02] Epoch [374\/3000]: Train loss: 2.7933, Valid loss: 2.6760 Epoch [375\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.49it\/s, loss=2.53] Epoch [375\/3000]: Train loss: 2.6363, Valid loss: 2.5503 Epoch [376\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.28it\/s, loss=3.37] Epoch [376\/3000]: Train 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[00:00<00:00, 80.25it\/s, loss=3.1] Epoch [434\/3000]: Train loss: 2.8259, Valid loss: 3.6940 Epoch [435\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.01it\/s, loss=3.8] Epoch [435\/3000]: Train loss: 3.6410, Valid loss: 3.7170 Epoch [436\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.46it\/s, loss=3.59] Epoch [436\/3000]: Train loss: 3.0176, Valid loss: 4.9087 Epoch [437\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.04it\/s, loss=4.82] Epoch [437\/3000]: Train loss: 4.9971, Valid loss: 4.6024 Epoch [438\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.90it\/s, loss=3.48] Epoch [438\/3000]: Train loss: 3.8955, Valid loss: 5.3130 Epoch [439\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.75it\/s, loss=2.75] Epoch [439\/3000]: Train loss: 3.3036, Valid loss: 3.2723 Epoch [440\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.95it\/s, loss=3.22] Epoch [440\/3000]: Train loss: 2.8608, Valid loss: 2.9944 Epoch [441\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.17it\/s, loss=4.2] Epoch [441\/3000]: Train loss: 2.8937, Valid loss: 6.2373 Epoch [442\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.53it\/s, loss=3.57] Epoch [442\/3000]: Train loss: 3.9937, Valid loss: 4.0479 Epoch [443\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.30it\/s, loss=3.67] Epoch [443\/3000]: Train loss: 3.1385, Valid loss: 2.7464 Epoch [444\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.28it\/s, loss=4.58] Epoch [444\/3000]: Train loss: 3.2392, Valid loss: 2.8205 Epoch [445\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.10it\/s, loss=2.97] Epoch [445\/3000]: Train loss: 4.4301, Valid loss: 4.1801 Epoch [446\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.10it\/s, loss=2.34] Epoch [446\/3000]: Train loss: 3.0381, Valid loss: 2.5242 Epoch [447\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.84it\/s, loss=2.99] Epoch [447\/3000]: Train loss: 3.4018, Valid loss: 5.2090 Epoch [448\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.96it\/s, loss=3.66] Epoch [448\/3000]: Train loss: 3.6274, Valid loss: 4.1256 Epoch [449\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.35it\/s, loss=3.56] Epoch [449\/3000]: Train loss: 4.0709, Valid loss: 3.4506 Epoch [450\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.21it\/s, loss=3.71] Epoch [450\/3000]: Train loss: 3.5461, Valid loss: 4.0639 Epoch [451\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.21it\/s, loss=3.37] Epoch [451\/3000]: Train loss: 3.8035, Valid loss: 2.4226 Epoch [452\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.94it\/s, loss=2.59] Epoch [452\/3000]: Train loss: 2.7660, Valid loss: 2.8297 Epoch [453\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.67it\/s, loss=3.48] Epoch [453\/3000]: Train loss: 3.0293, Valid loss: 5.4717 Epoch [454\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.26it\/s, loss=3.02] Epoch [454\/3000]: Train loss: 3.7111, Valid loss: 2.4652 Epoch [455\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.89it\/s, loss=2.4] Epoch [455\/3000]: Train loss: 2.8762, Valid loss: 3.3572 Epoch [456\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.78it\/s, loss=3.56] Epoch [456\/3000]: Train loss: 2.8325, Valid loss: 3.0713 Epoch [457\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.31it\/s, loss=3.38] Epoch [457\/3000]: Train loss: 3.5340, Valid loss: 2.6300 Epoch [458\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.44it\/s, loss=3.97] Epoch [458\/3000]: Train loss: 4.3645, Valid loss: 5.6404 Epoch [459\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.93it\/s, loss=2.67] Epoch [459\/3000]: Train loss: 3.2311, Valid loss: 2.9755 Epoch [460\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.29it\/s, loss=2.12] Epoch [460\/3000]: Train loss: 2.6489, Valid loss: 2.8953 Epoch [461\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.75it\/s, loss=2.28] Epoch [461\/3000]: Train loss: 2.7590, Valid loss: 3.9783 Epoch [462\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 17.89it\/s, loss=3.93] Epoch [462\/3000]: Train loss: 3.2317, Valid loss: 2.9334 Epoch [463\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.72it\/s, loss=3.01] Epoch [463\/3000]: Train loss: 2.9662, Valid loss: 2.7372 Epoch [464\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.25it\/s, loss=1.8] Epoch [464\/3000]: Train loss: 2.7374, Valid loss: 3.4904 Epoch [465\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.00it\/s, loss=3.96] Epoch [465\/3000]: Train loss: 3.0571, Valid loss: 4.0122 Epoch [466\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.68it\/s, loss=3.61] Epoch [466\/3000]: Train loss: 3.0489, Valid loss: 3.3783 Epoch [467\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.17it\/s, loss=2.41] Epoch [467\/3000]: Train loss: 3.0929, Valid loss: 2.6805 Epoch [468\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.02it\/s, loss=2.72] Epoch [468\/3000]: Train loss: 2.7422, Valid loss: 2.8651 Epoch [469\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.61it\/s, loss=2.59] Epoch [469\/3000]: Train loss: 2.6588, Valid loss: 3.0628 Epoch [470\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.21it\/s, loss=4.11] Epoch [470\/3000]: Train loss: 3.2769, Valid loss: 4.7475 Epoch [471\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.77it\/s, loss=2.19] Epoch [471\/3000]: Train loss: 3.7956, Valid loss: 3.0154 Epoch [472\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.06it\/s, loss=4.4] Epoch [472\/3000]: Train loss: 3.1666, Valid loss: 3.0074 Epoch [473\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.68it\/s, loss=2.79] Epoch [473\/3000]: Train loss: 2.8417, Valid loss: 5.2566 Epoch [474\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.08it\/s, loss=3.42] Epoch [474\/3000]: Train loss: 2.8095, Valid loss: 4.0360 Epoch [475\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.25it\/s, loss=4.29] Epoch [475\/3000]: Train loss: 4.1017, Valid loss: 4.4775 Epoch [476\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.74it\/s, loss=3.22] Epoch [476\/3000]: Train loss: 2.8787, Valid loss: 3.1419 Epoch [477\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.14it\/s, loss=3.65] Epoch [477\/3000]: Train loss: 3.1836, Valid loss: 3.5846 Epoch [478\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.59it\/s, loss=2.92] Epoch [478\/3000]: Train loss: 2.9483, Valid loss: 3.1968 Epoch [479\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.41it\/s, loss=2.52] Epoch [479\/3000]: Train loss: 2.7976, Valid loss: 2.3959 Epoch [480\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.48it\/s, loss=2.89] Epoch [480\/3000]: Train loss: 2.8191, Valid loss: 3.3128 Epoch [481\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.62it\/s, loss=3.06] Epoch [481\/3000]: Train loss: 3.5151, Valid loss: 4.8240 Epoch [482\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.15it\/s, loss=2.95] Epoch [482\/3000]: Train loss: 3.0630, Valid loss: 3.4282 Epoch [483\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.27it\/s, loss=2.3] Epoch [483\/3000]: Train loss: 3.0707, Valid loss: 3.1659 Epoch [484\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.66it\/s, loss=2.6] Epoch [484\/3000]: Train loss: 2.7651, Valid loss: 3.1546 Epoch [485\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.84it\/s, loss=2.62] Epoch [485\/3000]: Train loss: 2.7700, Valid loss: 2.4764 Epoch [486\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.10it\/s, loss=3.42] Epoch [486\/3000]: Train loss: 2.6984, Valid loss: 3.0341 Epoch [487\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.49it\/s, loss=11.2] Epoch [487\/3000]: Train loss: 4.4403, Valid loss: 17.0117 Epoch [488\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.69it\/s, loss=19.5] Epoch [488\/3000]: Train loss: 15.8401, Valid loss: 20.1903 Epoch [489\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.02it\/s, loss=5.2] Epoch [489\/3000]: Train loss: 11.6985, Valid loss: 6.0664 Epoch [490\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.59it\/s, loss=3.6] Epoch [490\/3000]: Train loss: 4.9335, Valid loss: 5.8675 Epoch [491\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.89it\/s, loss=7.78] Epoch [491\/3000]: Train loss: 5.2051, Valid loss: 3.4165 Epoch [492\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.07it\/s, loss=5.11] Epoch [492\/3000]: Train loss: 4.2499, Valid loss: 3.4294 Epoch [493\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.62it\/s, loss=3.1] Epoch [493\/3000]: Train loss: 3.1762, Valid loss: 7.3670 Epoch [494\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.23it\/s, loss=6.34] Epoch [494\/3000]: Train loss: 4.6036, Valid loss: 3.3444 Epoch [495\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.14it\/s, loss=3.29] Epoch [495\/3000]: Train loss: 3.8106, Valid loss: 4.3508 Epoch [496\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.83it\/s, loss=3.58] Epoch [496\/3000]: Train loss: 3.5781, Valid loss: 2.8628 Epoch [497\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.14it\/s, loss=3.3] Epoch [497\/3000]: Train loss: 2.6977, Valid loss: 2.9403 Epoch [498\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.07it\/s, loss=3.03] Epoch [498\/3000]: Train loss: 2.8719, Valid loss: 2.6411 Epoch [499\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.33it\/s, loss=1.78] Epoch [499\/3000]: Train loss: 2.5174, Valid loss: 2.5163 Epoch [500\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.06it\/s, loss=3.11] Epoch [500\/3000]: Train loss: 2.5963, Valid loss: 2.9316 Epoch [501\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.81it\/s, loss=2.77] Epoch [501\/3000]: Train loss: 2.8195, Valid loss: 2.2875 Epoch [502\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.63it\/s, loss=2.98] Epoch [502\/3000]: Train loss: 4.1152, Valid loss: 6.0365 Epoch [503\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.27it\/s, loss=2.49] Epoch [503\/3000]: Train loss: 3.6826, Valid loss: 2.8998 Epoch [504\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.26it\/s, loss=4.5] Epoch [504\/3000]: Train loss: 3.3610, Valid loss: 2.9274 Epoch [505\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.73it\/s, loss=2.37] Epoch [505\/3000]: Train loss: 3.3488, Valid loss: 7.2336 Epoch [506\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 66.75it\/s, loss=3.45] Epoch [506\/3000]: Train loss: 3.8404, Valid loss: 3.2248 Epoch [507\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.36it\/s, loss=2.46] Epoch [507\/3000]: Train loss: 2.7418, Valid loss: 2.9692 Epoch [508\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.70it\/s, loss=3.13] Epoch [508\/3000]: Train loss: 3.0545, Valid loss: 3.4805 Epoch [509\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.46it\/s, loss=3.37] Epoch [509\/3000]: Train loss: 3.1896, Valid loss: 2.5817 Epoch [510\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.67it\/s, loss=4.39] Epoch [510\/3000]: Train loss: 3.0890, Valid loss: 4.5509 Epoch [511\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.99it\/s, loss=3.52] Epoch [511\/3000]: Train loss: 3.6172, Valid loss: 3.0488 Epoch [512\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.73it\/s, loss=3.04] Epoch [512\/3000]: Train loss: 3.5045, Valid loss: 4.3581 Epoch [513\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.05it\/s, loss=6.6] Epoch [513\/3000]: Train loss: 4.3861, Valid loss: 2.8028 Epoch [514\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.34it\/s, loss=2.85] Epoch [514\/3000]: Train loss: 3.6332, Valid loss: 4.9198 Epoch [515\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.02it\/s, loss=2.87] Epoch [515\/3000]: Train loss: 3.1620, Valid loss: 2.4178 Epoch [516\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.64it\/s, loss=3.86] Epoch [516\/3000]: Train loss: 2.8584, Valid loss: 6.1108 Epoch [517\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.18it\/s, loss=3.05] Epoch [517\/3000]: Train loss: 3.5481, Valid loss: 2.5959 Epoch [518\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.24it\/s, loss=2.16] Epoch [518\/3000]: Train loss: 3.1900, Valid loss: 2.8114 Epoch [519\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.65it\/s, loss=2.14] Epoch [519\/3000]: Train loss: 2.8547, Valid loss: 4.1752 Epoch [520\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.64it\/s, loss=3.21] Epoch [520\/3000]: Train loss: 3.2500, Valid loss: 2.6009 Epoch [521\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.64it\/s, loss=2.71] Epoch [521\/3000]: Train loss: 2.5122, Valid loss: 2.5676 Epoch [522\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.23it\/s, loss=3.3] Epoch [522\/3000]: Train loss: 2.6330, Valid loss: 3.9387 Epoch [523\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.59it\/s, loss=2.85] Epoch [523\/3000]: Train loss: 3.1182, Valid loss: 2.2492 Epoch [524\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.87it\/s, loss=3.08] Epoch [524\/3000]: Train loss: 2.5117, Valid loss: 5.1198 Epoch [525\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.72it\/s, loss=6.31] Epoch [525\/3000]: Train loss: 4.7467, Valid loss: 2.8812 Epoch [526\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.09it\/s, loss=3.66] Epoch [526\/3000]: Train loss: 4.0047, Valid loss: 3.1585 Epoch [527\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.69it\/s, loss=2.5] Epoch [527\/3000]: Train loss: 2.6775, Valid loss: 2.9030 Epoch [528\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.61it\/s, loss=2.66] Epoch [528\/3000]: Train loss: 2.4765, Valid loss: 2.4541 Epoch [529\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.59it\/s, loss=2.87] Epoch [529\/3000]: Train loss: 2.5036, Valid loss: 3.4864 Epoch [530\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.27it\/s, loss=2.82] Epoch [530\/3000]: Train loss: 2.6984, Valid loss: 3.0412 Epoch [531\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.72it\/s, loss=2.63] Epoch [531\/3000]: Train loss: 2.5396, Valid loss: 4.7338 Epoch [532\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.39it\/s, loss=3.19] Epoch [532\/3000]: Train loss: 3.9364, Valid loss: 2.4208 Epoch [533\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.48it\/s, loss=4.61] Epoch [533\/3000]: Train loss: 3.5655, Valid loss: 6.7029 Epoch [534\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.07it\/s, loss=2.55] Epoch [534\/3000]: Train loss: 3.5163, Valid loss: 4.3437 Epoch [535\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.00it\/s, loss=4.35] Epoch [535\/3000]: Train loss: 4.4360, Valid loss: 3.3007 Epoch [536\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.59it\/s, loss=3.74] Epoch [536\/3000]: Train loss: 3.0101, Valid loss: 4.6487 Epoch [537\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.05it\/s, loss=3.55] Epoch [537\/3000]: Train loss: 3.3689, Valid loss: 2.4006 Epoch [538\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.12it\/s, loss=2.95] Epoch [538\/3000]: Train loss: 3.2336, Valid loss: 2.3178 Epoch [539\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.18it\/s, loss=2.38] Epoch [539\/3000]: Train loss: 2.5088, Valid loss: 2.6000 Epoch [540\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.19it\/s, loss=3.07] Epoch [540\/3000]: Train loss: 2.4991, Valid loss: 2.4115 Epoch [541\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.86it\/s, loss=4.81] Epoch [541\/3000]: Train loss: 3.1559, Valid loss: 3.0052 Epoch [542\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.45it\/s, loss=2.35] Epoch [542\/3000]: Train loss: 3.0186, Valid loss: 3.0020 Epoch [543\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.13it\/s, loss=2.43] Epoch [543\/3000]: Train loss: 2.6677, Valid loss: 2.5364 Epoch [544\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.90it\/s, loss=3.57] Epoch [544\/3000]: Train loss: 2.9277, Valid loss: 2.2704 Epoch [545\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.09it\/s, loss=2.2] Epoch [545\/3000]: Train loss: 2.8573, Valid loss: 3.0948 Epoch [546\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.29it\/s, loss=7.64] Epoch [546\/3000]: Train loss: 3.8944, Valid loss: 5.4914 Epoch [547\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.26it\/s, loss=2.6] Epoch [547\/3000]: Train loss: 4.7816, Valid loss: 4.1140 Epoch [548\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.42it\/s, loss=2.37] Epoch [548\/3000]: Train loss: 3.1337, Valid loss: 3.6573 Epoch [549\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.89it\/s, loss=4.16] Epoch [549\/3000]: Train loss: 3.7297, Valid loss: 3.9265 Epoch [550\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.09it\/s, loss=2.39] Epoch [550\/3000]: Train loss: 2.8698, Valid loss: 2.6519 Epoch [551\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.93it\/s, loss=2.29] Epoch [551\/3000]: Train loss: 3.3595, Valid loss: 3.7313 Epoch [552\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.34it\/s, loss=5.04] Epoch [552\/3000]: Train loss: 4.3775, Valid loss: 4.7634 Epoch [553\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.81it\/s, loss=2.98] Epoch [553\/3000]: Train loss: 3.8454, Valid loss: 3.8588 Epoch [554\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.03it\/s, loss=4.17] Epoch [554\/3000]: Train loss: 3.1775, Valid loss: 3.1981 Epoch [555\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.27it\/s, loss=2.65] Epoch [555\/3000]: Train loss: 2.5629, Valid loss: 3.6634 Epoch [556\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 104.08it\/s, loss=2.19] Epoch [556\/3000]: Train loss: 2.7709, Valid loss: 2.3835 Epoch [557\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.46it\/s, loss=2.5] Epoch [557\/3000]: Train loss: 2.3735, Valid loss: 2.7212 Epoch [558\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.74it\/s, loss=2.51] Epoch [558\/3000]: Train loss: 2.4336, Valid loss: 2.9481 Epoch [559\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.00it\/s, loss=3.5] Epoch [559\/3000]: Train loss: 2.7382, Valid loss: 5.4690 Epoch [560\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.37it\/s, loss=3.29] Epoch [560\/3000]: Train loss: 3.4269, Valid loss: 2.7617 Epoch [561\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.66it\/s, loss=2.29] Epoch [561\/3000]: Train loss: 2.5645, Valid loss: 3.2413 Epoch [562\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.61it\/s, loss=2.67] Epoch [562\/3000]: Train loss: 2.5185, Valid loss: 2.5099 Epoch [563\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.55it\/s, loss=3.12] Epoch [563\/3000]: Train loss: 2.5507, Valid loss: 2.4758 Epoch [564\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.31it\/s, loss=2.66] Epoch [564\/3000]: Train loss: 2.4615, Valid loss: 2.6301 Epoch [565\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.14it\/s, loss=2.36] Epoch [565\/3000]: Train loss: 2.4942, Valid loss: 2.6289 Epoch [566\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.22it\/s, loss=4.22] Epoch [566\/3000]: Train loss: 3.4040, Valid loss: 2.6129 Epoch [567\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.74it\/s, loss=3.2] Epoch [567\/3000]: Train loss: 3.2035, Valid loss: 2.9145 Epoch [568\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.98it\/s, loss=3.86] Epoch [568\/3000]: Train loss: 2.8981, Valid loss: 6.0288 Epoch [569\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.79it\/s, loss=2.88] Epoch [569\/3000]: Train loss: 3.1874, Valid loss: 2.7995 Epoch [570\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.75it\/s, loss=3.86] Epoch [570\/3000]: Train loss: 3.7331, Valid loss: 5.7574 Epoch [571\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.82it\/s, loss=4.79] Epoch [571\/3000]: Train loss: 4.9020, Valid loss: 5.1144 Epoch [572\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.51it\/s, loss=3.49] Epoch [572\/3000]: Train loss: 3.6340, Valid loss: 2.6116 Epoch [573\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.92it\/s, loss=2.76] Epoch [573\/3000]: Train loss: 2.8137, Valid loss: 3.5325 Epoch [574\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.18it\/s, loss=2.19] Epoch [574\/3000]: Train loss: 2.8845, Valid loss: 3.5842 Epoch [575\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.26it\/s, loss=4.74] Epoch [575\/3000]: Train loss: 3.0502, Valid loss: 2.6822 Epoch [576\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.07it\/s, loss=3.46] Epoch [576\/3000]: Train loss: 2.8815, Valid loss: 2.4284 Epoch [577\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.64it\/s, loss=2.76] Epoch [577\/3000]: Train loss: 3.0101, Valid loss: 2.8518 Epoch [578\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.66it\/s, loss=2.36] Epoch [578\/3000]: Train loss: 2.6349, Valid loss: 4.4351 Epoch [579\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.37it\/s, loss=3.27] Epoch [579\/3000]: Train loss: 3.7680, Valid loss: 3.5364 Epoch [580\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.17it\/s, loss=4.06] Epoch [580\/3000]: Train loss: 3.0235, Valid loss: 2.3764 Epoch [581\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.48it\/s, loss=2.89] Epoch [581\/3000]: Train loss: 2.6834, Valid loss: 3.4096 Epoch [582\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.53it\/s, loss=1.65] Epoch [582\/3000]: Train loss: 2.6111, Valid loss: 2.5888 Epoch [583\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.88it\/s, loss=1.95] Epoch [583\/3000]: Train 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Epoch [620\/3000]: Train loss: 3.0107, Valid loss: 3.0196 Epoch [621\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.44it\/s, loss=2.5] Epoch [621\/3000]: Train loss: 2.5267, Valid loss: 2.7389 Epoch [622\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.17it\/s, loss=2.89] Epoch [622\/3000]: Train loss: 2.4655, Valid loss: 2.3140 Epoch [623\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.70it\/s, loss=2.62] Epoch [623\/3000]: Train loss: 2.5478, Valid loss: 2.3983 Epoch [624\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.27it\/s, loss=2.34] Epoch [624\/3000]: Train loss: 2.6344, Valid loss: 3.3228 Epoch [625\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.89it\/s, loss=4.23] Epoch [625\/3000]: Train loss: 4.0349, Valid loss: 3.8820 Epoch 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2.4901, Valid loss: 3.0390 Epoch [642\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.09it\/s, loss=2.41] Epoch [642\/3000]: Train loss: 3.0298, Valid loss: 3.8754 Epoch [643\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.61it\/s, loss=2.58] Epoch [643\/3000]: Train loss: 2.7025, Valid loss: 2.5848 Epoch [644\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.44it\/s, loss=2.53] Epoch [644\/3000]: Train loss: 2.3920, Valid loss: 2.0791 Saving model with loss 2.079… Epoch [645\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.88it\/s, loss=3.61] Epoch [645\/3000]: Train loss: 2.3851, Valid loss: 2.2501 Epoch [646\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.16it\/s, loss=2.22] Epoch [646\/3000]: Train loss: 2.2790, Valid loss: 3.2215 Epoch 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100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.55it\/s, loss=3.46] Epoch [652\/3000]: Train loss: 3.4462, Valid loss: 4.5703 Epoch [653\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.44it\/s, loss=4.75] Epoch [653\/3000]: Train loss: 3.9583, Valid loss: 4.6221 Epoch [654\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 101.08it\/s, loss=4.91] Epoch [654\/3000]: Train loss: 4.1569, Valid loss: 4.5601 Epoch [655\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.28it\/s, loss=1.65] Epoch [655\/3000]: Train loss: 3.4206, Valid loss: 3.9113 Epoch [656\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.69it\/s, loss=3.77] Epoch [656\/3000]: Train loss: 3.2228, Valid loss: 2.5658 Epoch [657\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.10it\/s, loss=2.45] Epoch [657\/3000]: Train loss: 3.5734, Valid loss: 4.6903 Epoch [658\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.84it\/s, loss=3.61] Epoch [658\/3000]: Train loss: 3.1149, Valid loss: 2.6996 Epoch [659\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.39it\/s, loss=2.69] Epoch [659\/3000]: Train loss: 2.6486, Valid loss: 3.7775 Epoch [660\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.41it\/s, loss=3.04] Epoch [660\/3000]: Train loss: 2.7094, Valid loss: 2.6695 Epoch [661\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.32it\/s, loss=2.29] Epoch [661\/3000]: Train loss: 2.4245, Valid loss: 3.5819 Epoch [662\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.82it\/s, loss=3.2] Epoch [662\/3000]: Train loss: 2.8739, Valid loss: 2.0655 Saving model with loss 2.066… Epoch [663\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.49it\/s, loss=1.58] Epoch [663\/3000]: Train loss: 2.3290, Valid loss: 2.6541 Epoch [664\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.03it\/s, loss=3.39] Epoch [664\/3000]: Train loss: 2.5145, Valid loss: 1.9403 Saving model with loss 1.940… Epoch [665\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.14it\/s, loss=2.62] Epoch [665\/3000]: Train loss: 2.5405, Valid loss: 3.1732 Epoch [666\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.93it\/s, loss=3.09] Epoch [666\/3000]: Train loss: 2.6761, Valid loss: 2.5599 Epoch [667\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.50it\/s, loss=2.14] Epoch [667\/3000]: Train loss: 2.5081, Valid loss: 2.6800 Epoch [668\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.99it\/s, loss=2.4] Epoch [668\/3000]: Train loss: 2.5129, Valid loss: 3.3198 Epoch [669\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.30it\/s, loss=3.71] Epoch [669\/3000]: Train loss: 2.8122, Valid loss: 3.6785 Epoch [670\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.61it\/s, loss=2.58] Epoch [670\/3000]: Train loss: 2.4009, Valid loss: 2.6116 Epoch [671\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.24it\/s, loss=1.94] Epoch [671\/3000]: Train loss: 2.3034, Valid loss: 2.4541 Epoch [672\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.45it\/s, loss=2.85] Epoch [672\/3000]: Train loss: 2.2343, Valid loss: 2.4609 Epoch [673\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.81it\/s, loss=2.19] Epoch [673\/3000]: Train loss: 2.4299, Valid loss: 3.6618 Epoch [674\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.19it\/s, loss=1.94] Epoch [674\/3000]: Train loss: 2.4231, Valid loss: 2.8410 Epoch [675\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.44it\/s, loss=2.79] Epoch [675\/3000]: Train loss: 2.6580, Valid loss: 2.2161 Epoch [676\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.76it\/s, loss=1.54] Epoch [676\/3000]: Train loss: 2.1848, Valid loss: 2.1514 Epoch [677\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.51it\/s, loss=2.38] Epoch [677\/3000]: Train loss: 2.1831, Valid loss: 2.0987 Epoch [678\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 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loss: 8.2048, Valid loss: 15.3238 Epoch [684\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.95it\/s, loss=6.29] Epoch [684\/3000]: Train loss: 7.6412, Valid loss: 3.3807 Epoch [685\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.05it\/s, loss=3.07] Epoch [685\/3000]: Train loss: 3.2330, Valid loss: 2.3681 Epoch [686\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.08it\/s, loss=2.19] Epoch [686\/3000]: Train loss: 2.3890, Valid loss: 1.9705 Epoch [687\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.71it\/s, loss=2.16] Epoch [687\/3000]: Train loss: 2.2128, Valid loss: 2.4509 Epoch [688\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.95it\/s, loss=2.23] Epoch [688\/3000]: Train loss: 2.4273, Valid loss: 4.1685 Epoch [689\/3000]: 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loss: 2.8080, Valid loss: 3.2007 Epoch [700\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.48it\/s, loss=2.92] Epoch [700\/3000]: Train loss: 2.8156, Valid loss: 4.3485 Epoch [701\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.81it\/s, loss=3.01] Epoch [701\/3000]: Train loss: 3.0376, Valid loss: 3.0533 Epoch [702\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.72it\/s, loss=4.09] Epoch [702\/3000]: Train loss: 3.1303, Valid loss: 2.9586 Epoch [703\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.45it\/s, loss=1.72] Epoch [703\/3000]: Train loss: 2.8404, Valid loss: 3.1110 Epoch [704\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.64it\/s, loss=2.34] Epoch [704\/3000]: Train loss: 2.2877, Valid loss: 3.0061 Epoch [705\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.28it\/s, loss=2.44] Epoch [705\/3000]: Train loss: 2.4469, Valid loss: 3.2856 Epoch [706\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.20it\/s, loss=2.64] Epoch [706\/3000]: Train loss: 3.6272, Valid loss: 4.0980 Epoch [707\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.54it\/s, loss=8.28] Epoch [707\/3000]: Train loss: 3.9179, Valid loss: 5.5950 Epoch [708\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.36it\/s, loss=2.26] Epoch [708\/3000]: Train loss: 3.7030, Valid loss: 3.2367 Epoch [709\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.78it\/s, loss=2.74] Epoch [709\/3000]: Train loss: 2.5318, Valid loss: 2.8506 Epoch [710\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.52it\/s, loss=2.78] Epoch [710\/3000]: Train loss: 3.0241, Valid loss: 4.1639 Epoch [711\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.59it\/s, loss=2.48] Epoch [711\/3000]: Train loss: 2.7863, Valid loss: 3.5457 Epoch [712\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.12it\/s, loss=6.43] Epoch [712\/3000]: Train loss: 5.1775, Valid loss: 3.1130 Epoch [713\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.83it\/s, loss=3.95] Epoch [713\/3000]: Train loss: 5.1651, Valid loss: 4.8144 Epoch [714\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.54it\/s, loss=2.48] Epoch [714\/3000]: Train loss: 3.3449, Valid loss: 4.1916 Epoch [715\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.78it\/s, loss=3.56] Epoch [715\/3000]: Train loss: 3.2744, Valid loss: 5.4144 Epoch [716\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.49it\/s, loss=3.63] Epoch [716\/3000]: Train loss: 3.7139, Valid loss: 2.1360 Epoch [717\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.85it\/s, loss=2.46] Epoch [717\/3000]: Train loss: 2.7771, Valid loss: 2.2360 Epoch [718\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.14it\/s, loss=2.75] Epoch [718\/3000]: Train loss: 2.5377, Valid loss: 3.0562 Epoch [719\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.29it\/s, loss=1.89] Epoch [719\/3000]: Train loss: 2.5844, Valid loss: 3.0056 Epoch [720\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.33it\/s, loss=1.97] Epoch [720\/3000]: Train loss: 2.3509, Valid loss: 2.3527 Epoch [721\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.15it\/s, loss=2.61] Epoch [721\/3000]: Train loss: 2.5003, Valid loss: 2.3903 Epoch [722\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.42it\/s, loss=1.93] Epoch [722\/3000]: Train loss: 2.3846, Valid loss: 3.2830 Epoch [723\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.66it\/s, loss=2.25] Epoch [723\/3000]: Train loss: 2.4767, Valid loss: 2.6010 Epoch [724\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.05it\/s, loss=3.66] Epoch [724\/3000]: Train loss: 3.4291, Valid loss: 3.5681 Epoch [725\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.04it\/s, loss=2.93] Epoch [725\/3000]: Train loss: 2.9793, Valid loss: 3.3089 Epoch [726\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.98it\/s, loss=3.53] Epoch [726\/3000]: Train loss: 2.7546, Valid loss: 2.5692 Epoch [727\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.97it\/s, loss=5.06] Epoch [727\/3000]: Train loss: 2.9850, Valid loss: 6.8304 Epoch [728\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.41it\/s, loss=4.81] Epoch [728\/3000]: Train loss: 4.5845, Valid loss: 2.5113 Epoch [729\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.26it\/s, loss=2.36] Epoch [729\/3000]: Train loss: 2.9383, Valid loss: 3.3322 Epoch [730\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.18it\/s, loss=2.17] Epoch [730\/3000]: Train loss: 2.5290, Valid loss: 4.0481 Epoch [731\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.93it\/s, loss=5.16] Epoch [731\/3000]: Train loss: 3.4477, Valid loss: 3.6555 Epoch [732\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.78it\/s, loss=3] Epoch [732\/3000]: Train loss: 3.5019, Valid loss: 2.1563 Epoch [733\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.19it\/s, loss=2.33] Epoch [733\/3000]: Train loss: 2.5826, Valid loss: 3.4356 Epoch [734\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.45it\/s, loss=1.98] Epoch [734\/3000]: Train loss: 2.3175, Valid loss: 3.2097 Epoch [735\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 63.67it\/s, loss=5.16] Epoch [735\/3000]: Train loss: 3.4923, Valid loss: 2.2369 Epoch [736\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.19it\/s, loss=3.82] Epoch [736\/3000]: Train loss: 2.7541, Valid loss: 3.0859 Epoch [737\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.92it\/s, loss=1.81] Epoch [737\/3000]: Train loss: 2.2826, Valid loss: 2.3301 Epoch [738\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.65it\/s, loss=2.18] Epoch [738\/3000]: Train loss: 2.2840, Valid loss: 2.1456 Epoch [739\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.58it\/s, loss=2.38] Epoch [739\/3000]: Train loss: 2.2017, Valid loss: 3.1072 Epoch [740\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.63it\/s, loss=1.75] Epoch [740\/3000]: Train loss: 2.4805, Valid loss: 2.6487 Epoch [741\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.06it\/s, loss=2.68] Epoch [741\/3000]: Train loss: 2.8420, Valid loss: 4.5216 Epoch [742\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.30it\/s, loss=2.99] Epoch [742\/3000]: Train loss: 2.8911, Valid loss: 4.3668 Epoch [743\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.27it\/s, loss=3.59] Epoch [743\/3000]: Train loss: 2.8609, Valid loss: 2.3045 Epoch [744\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.66it\/s, loss=1.74] Epoch [744\/3000]: Train loss: 2.1451, Valid loss: 2.7417 Epoch [745\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.72it\/s, loss=2.96] Epoch [745\/3000]: Train loss: 2.5182, Valid loss: 2.8971 Epoch [746\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.26it\/s, loss=2.23] Epoch [746\/3000]: Train loss: 2.7027, Valid loss: 4.4468 Epoch [747\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.66it\/s, loss=2.83] Epoch [747\/3000]: Train loss: 2.7673, Valid loss: 2.2748 Epoch [748\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.87it\/s, loss=2.24] Epoch [748\/3000]: Train loss: 2.1266, Valid loss: 2.3630 Epoch [749\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.14it\/s, loss=1.96] Epoch [749\/3000]: Train loss: 2.1391, Valid loss: 2.1074 Epoch [750\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.14it\/s, loss=2.1] Epoch [750\/3000]: Train loss: 2.2039, Valid loss: 2.3402 Epoch [751\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.09it\/s, loss=2.65] Epoch [751\/3000]: Train loss: 2.5267, Valid loss: 2.9579 Epoch [752\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.03it\/s, loss=2.36] Epoch [752\/3000]: Train loss: 2.3837, Valid loss: 2.8995 Epoch [753\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.55it\/s, loss=2.6] Epoch [753\/3000]: Train loss: 2.3364, Valid loss: 2.1849 Epoch [754\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.55it\/s, loss=2.33] Epoch [754\/3000]: Train loss: 2.2116, Valid loss: 2.5849 Epoch [755\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.29it\/s, loss=2.16] Epoch [755\/3000]: Train loss: 2.2066, Valid loss: 4.1677 Epoch [756\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.51it\/s, loss=3.75] Epoch [756\/3000]: Train loss: 2.8880, Valid loss: 2.3432 Epoch [757\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.36it\/s, loss=3.16] Epoch [757\/3000]: Train loss: 3.1326, Valid loss: 2.3646 Epoch [758\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.04it\/s, loss=2.63] Epoch [758\/3000]: Train loss: 2.7076, Valid loss: 3.0534 Epoch [759\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.99it\/s, loss=2.24] Epoch [759\/3000]: Train loss: 2.5494, Valid loss: 3.4094 Epoch [760\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.93it\/s, loss=2.28] Epoch [760\/3000]: Train loss: 2.5350, Valid loss: 3.1512 Epoch [761\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.65it\/s, loss=2.62] Epoch [761\/3000]: Train loss: 2.6099, Valid loss: 2.1727 Epoch [762\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.73it\/s, loss=2.23] Epoch [762\/3000]: Train loss: 2.7130, Valid loss: 4.2002 Epoch [763\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.88it\/s, loss=4.18] Epoch [763\/3000]: Train loss: 3.1757, Valid loss: 3.0510 Epoch [764\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.30it\/s, loss=1.96] Epoch [764\/3000]: Train loss: 2.6264, Valid loss: 2.2102 Epoch [765\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.36it\/s, loss=1.92] Epoch [765\/3000]: Train loss: 2.0944, Valid loss: 2.3231 Epoch [766\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.80it\/s, loss=2.01] Epoch [766\/3000]: Train loss: 2.1532, Valid loss: 2.2396 Epoch [767\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.20it\/s, loss=3.11] Epoch [767\/3000]: Train loss: 2.4559, Valid loss: 2.4042 Epoch [768\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.38it\/s, loss=2.27] Epoch [768\/3000]: Train loss: 2.4403, Valid loss: 5.3449 Epoch [769\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.22it\/s, loss=4.94] Epoch [769\/3000]: Train loss: 3.3639, Valid loss: 2.4257 Epoch [770\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.56it\/s, loss=1.95] Epoch [770\/3000]: Train loss: 2.9749, Valid loss: 4.4580 Epoch [771\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.37it\/s, loss=3.69] Epoch [771\/3000]: Train loss: 3.1536, Valid loss: 2.3526 Epoch [772\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.08it\/s, loss=2.36] Epoch [772\/3000]: Train loss: 2.4569, Valid loss: 2.6819 Epoch [773\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.61it\/s, loss=1.88] Epoch [773\/3000]: Train loss: 2.2942, Valid loss: 2.3112 Epoch [774\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 18.22it\/s, loss=2.72] Epoch [774\/3000]: Train loss: 2.2765, Valid loss: 2.8759 Epoch [775\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 106.28it\/s, loss=1.75] Epoch [775\/3000]: Train loss: 2.4222, Valid loss: 3.3676 Epoch [776\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.37it\/s, loss=1.84] Epoch [776\/3000]: Train loss: 2.2814, Valid loss: 2.1156 Epoch [777\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.15it\/s, loss=2.93] Epoch [777\/3000]: Train loss: 2.1157, Valid loss: 2.1304 Epoch [778\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.78it\/s, loss=3.06] Epoch [778\/3000]: Train loss: 2.3243, Valid loss: 2.2984 Epoch [779\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.66it\/s, loss=1.97] Epoch [779\/3000]: Train loss: 2.5684, Valid loss: 2.6099 Epoch [780\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.59it\/s, loss=1.99] Epoch [780\/3000]: Train loss: 2.2965, Valid loss: 2.3154 Epoch [781\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.13it\/s, loss=2.48] Epoch [781\/3000]: Train loss: 2.5133, Valid loss: 3.2515 Epoch [782\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.42it\/s, loss=3.35] Epoch [782\/3000]: Train loss: 4.2772, Valid loss: 2.1420 Epoch [783\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.59it\/s, loss=2.37] Epoch [783\/3000]: Train loss: 3.1728, Valid loss: 6.7172 Epoch [784\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 100.11it\/s, loss=3.84] Epoch [784\/3000]: Train loss: 4.6818, Valid loss: 2.7038 Epoch [785\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.19it\/s, loss=4.19] Epoch [785\/3000]: Train loss: 3.0639, Valid loss: 2.2348 Epoch [786\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.63it\/s, loss=2.83] Epoch [786\/3000]: Train loss: 3.3995, Valid loss: 4.2882 Epoch [787\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.10it\/s, loss=3.34] Epoch [787\/3000]: Train loss: 3.1692, Valid loss: 2.3584 Epoch [788\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.06it\/s, loss=2.3] Epoch [788\/3000]: Train loss: 2.2552, Valid loss: 2.4221 Epoch [789\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.73it\/s, loss=2.11] Epoch [789\/3000]: Train loss: 2.3247, Valid loss: 2.7716 Epoch [790\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 66.29it\/s, loss=2.9] Epoch [790\/3000]: Train loss: 3.3057, Valid loss: 3.7420 Epoch [791\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.36it\/s, loss=5.53] Epoch [791\/3000]: Train loss: 3.6044, Valid loss: 4.7485 Epoch [792\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.92it\/s, loss=1.99] Epoch [792\/3000]: Train loss: 3.1639, Valid loss: 3.1113 Epoch [793\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.41it\/s, loss=2.53] Epoch [793\/3000]: Train loss: 2.4302, Valid loss: 2.2509 Epoch [794\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.98it\/s, loss=2.06] Epoch [794\/3000]: Train loss: 2.1576, Valid loss: 2.9067 Epoch [795\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.36it\/s, loss=3.35] Epoch [795\/3000]: Train loss: 2.4144, Valid loss: 2.5407 Epoch [796\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.36it\/s, loss=2.25] Epoch [796\/3000]: Train loss: 2.3543, Valid loss: 2.5973 Epoch [797\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.51it\/s, loss=1.69] Epoch [797\/3000]: Train loss: 2.1499, Valid loss: 2.4979 Epoch [798\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.27it\/s, loss=2.23] Epoch [798\/3000]: Train loss: 2.2037, Valid loss: 2.3776 Epoch [799\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.31it\/s, loss=1.56] Epoch [799\/3000]: Train loss: 2.2762, Valid loss: 2.0624 Epoch [800\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.68it\/s, loss=2.88] Epoch [800\/3000]: Train loss: 2.1508, Valid loss: 2.8196 Epoch [801\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.00it\/s, loss=3.2] Epoch [801\/3000]: Train loss: 2.5665, Valid loss: 2.4627 Epoch [802\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.25it\/s, loss=2.31] Epoch [802\/3000]: Train loss: 3.0202, Valid loss: 5.1984 Epoch [803\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.67it\/s, loss=3.7] Epoch [803\/3000]: Train loss: 2.8955, Valid loss: 2.7984 Epoch [804\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.77it\/s, loss=2.28] Epoch [804\/3000]: Train loss: 2.3565, Valid loss: 2.3290 Epoch [805\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.20it\/s, loss=1.93] Epoch [805\/3000]: Train loss: 2.2755, Valid loss: 2.4139 Epoch [806\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.01it\/s, loss=3.68] Epoch [806\/3000]: Train loss: 2.5469, Valid loss: 2.7840 Epoch [807\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.40it\/s, loss=1.37] Epoch [807\/3000]: Train loss: 3.1902, Valid loss: 3.3694 Epoch [808\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.65it\/s, loss=2.2] Epoch [808\/3000]: Train loss: 2.3039, Valid loss: 2.0234 Epoch [809\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.25it\/s, loss=2.14] Epoch [809\/3000]: Train loss: 2.3174, Valid loss: 2.2693 Epoch [810\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.05it\/s, loss=2.64] Epoch [810\/3000]: Train loss: 2.3077, Valid loss: 2.4819 Epoch [811\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.11it\/s, loss=1.85] Epoch [811\/3000]: Train loss: 2.1487, Valid loss: 2.6050 Epoch [812\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.27it\/s, loss=2.95] Epoch [812\/3000]: Train loss: 2.2864, Valid loss: 3.0497 Epoch [813\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.07it\/s, loss=2.61] Epoch [813\/3000]: Train loss: 2.7491, Valid loss: 2.3695 Epoch [814\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.74it\/s, loss=2.9] Epoch [814\/3000]: Train loss: 3.3393, Valid loss: 3.3992 Epoch [815\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.87it\/s, loss=2.65] Epoch [815\/3000]: Train loss: 2.8985, Valid loss: 3.7377 Epoch [816\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.91it\/s, loss=2.55] Epoch [816\/3000]: Train loss: 2.3878, Valid loss: 2.6837 Epoch [817\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.79it\/s, loss=1.6] Epoch [817\/3000]: Train loss: 2.2873, Valid loss: 2.1450 Epoch [818\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.68it\/s, loss=2.15] Epoch [818\/3000]: Train loss: 2.0465, Valid loss: 2.6081 Epoch [819\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.42it\/s, loss=2.41] Epoch [819\/3000]: Train loss: 2.0998, Valid loss: 3.4995 Epoch [820\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.86it\/s, loss=1.97] Epoch [820\/3000]: Train loss: 2.4567, Valid loss: 2.2759 Epoch [821\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.87it\/s, loss=1.92] Epoch [821\/3000]: Train loss: 2.3125, Valid loss: 2.5369 Epoch [822\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.03it\/s, loss=2.07] Epoch [822\/3000]: Train loss: 2.3085, Valid loss: 2.9622 Epoch [823\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.36it\/s, loss=3.71] Epoch [823\/3000]: Train loss: 2.6831, Valid loss: 4.1392 Epoch [824\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.55it\/s, loss=2.73] Epoch [824\/3000]: Train loss: 2.5803, Valid loss: 2.2061 Epoch [825\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.75it\/s, loss=1.8] Epoch [825\/3000]: Train loss: 2.3754, Valid loss: 2.4249 Epoch [826\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.33it\/s, loss=1.85] Epoch [826\/3000]: Train loss: 2.0645, Valid loss: 2.5717 Epoch [827\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.46it\/s, loss=2.64] Epoch [827\/3000]: Train loss: 2.1440, Valid loss: 2.3166 Epoch [828\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.12it\/s, loss=2.67] Epoch [828\/3000]: Train loss: 2.3818, Valid loss: 3.7606 Epoch [829\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.59it\/s, loss=3.98] Epoch [829\/3000]: Train loss: 3.2636, Valid loss: 6.8539 Epoch [830\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.41it\/s, loss=3.54] Epoch [830\/3000]: Train loss: 3.4702, Valid loss: 3.5368 Epoch [831\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.64it\/s, loss=3.35] Epoch [831\/3000]: Train loss: 2.7041, Valid loss: 2.6873 Epoch [832\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.01it\/s, loss=2.24] Epoch [832\/3000]: Train loss: 2.3015, Valid loss: 2.3863 Epoch [833\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.03it\/s, loss=1.98] Epoch [833\/3000]: Train loss: 2.2055, Valid loss: 3.3000 Epoch [834\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.62it\/s, loss=3.49] Epoch [834\/3000]: Train loss: 3.0848, Valid loss: 2.5471 Epoch [835\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.44it\/s, loss=1.31] Epoch [835\/3000]: Train loss: 2.6865, Valid loss: 2.9010 Epoch [836\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.38it\/s, loss=1.79] Epoch [836\/3000]: Train loss: 2.1052, Valid loss: 2.5396 Epoch [837\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.08it\/s, loss=1.71] Epoch [837\/3000]: Train loss: 2.1150, Valid loss: 2.1872 Epoch [838\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.42it\/s, loss=2.47] Epoch [838\/3000]: Train loss: 2.1801, Valid loss: 2.5129 Epoch [839\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.32it\/s, loss=1.84] Epoch [839\/3000]: Train loss: 2.0296, Valid loss: 2.0137 Epoch [840\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.78it\/s, loss=2.11] Epoch [840\/3000]: Train loss: 2.4764, Valid loss: 3.7798 Epoch [841\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.25it\/s, loss=1.9] Epoch [841\/3000]: Train loss: 2.4510, Valid loss: 3.1116 Epoch [842\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.84it\/s, loss=3.4] Epoch [842\/3000]: Train loss: 3.2153, Valid loss: 4.7290 Epoch [843\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.57it\/s, loss=3.36] Epoch [843\/3000]: Train loss: 2.8108, Valid loss: 2.2275 Epoch [844\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.74it\/s, loss=2.38] Epoch [844\/3000]: Train loss: 2.6538, Valid loss: 3.2720 Epoch [845\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.32it\/s, loss=2.64] Epoch [845\/3000]: Train loss: 2.3694, Valid loss: 2.6815 Epoch [846\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.81it\/s, loss=2.66] Epoch [846\/3000]: Train loss: 2.5853, Valid loss: 2.9036 Epoch [847\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.73it\/s, loss=2.04] Epoch [847\/3000]: Train loss: 2.5462, Valid loss: 3.6156 Epoch [848\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.21it\/s, loss=3.3] Epoch [848\/3000]: Train loss: 3.0342, Valid loss: 6.4222 Epoch [849\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.57it\/s, loss=4.56] Epoch [849\/3000]: Train loss: 4.2875, Valid loss: 5.3043 Epoch [850\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.33it\/s, loss=1.99] Epoch [850\/3000]: Train loss: 3.1273, Valid loss: 2.7059 Epoch [851\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.35it\/s, loss=2.22] Epoch [851\/3000]: Train loss: 2.2874, Valid loss: 4.4700 Epoch [852\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.62it\/s, loss=3.15] Epoch [852\/3000]: Train loss: 3.8641, Valid loss: 3.0829 Epoch [853\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 66.86it\/s, loss=3.08] Epoch [853\/3000]: Train loss: 3.0634, Valid loss: 2.9437 Epoch [854\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.49it\/s, loss=1.7] Epoch [854\/3000]: Train loss: 2.5333, Valid loss: 2.8875 Epoch [855\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.92it\/s, loss=2.3] Epoch [855\/3000]: Train loss: 2.6216, Valid loss: 3.2111 Epoch [856\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.63it\/s, loss=2.06] Epoch [856\/3000]: Train loss: 2.5271, Valid loss: 2.4412 Epoch [857\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.40it\/s, loss=1.69] Epoch [857\/3000]: Train loss: 2.1335, Valid loss: 2.0227 Epoch [858\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.61it\/s, loss=2.4] Epoch [858\/3000]: Train loss: 2.0972, Valid loss: 2.5107 Epoch [859\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.93it\/s, loss=4.37] Epoch [859\/3000]: Train loss: 2.6693, Valid loss: 2.7045 Epoch [860\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.36it\/s, loss=1.85] Epoch [860\/3000]: Train loss: 2.6099, Valid loss: 1.9490 Epoch [861\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.55it\/s, loss=1.56] Epoch [861\/3000]: Train loss: 2.0485, Valid loss: 2.8485 Epoch [862\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.04it\/s, loss=3.6] Epoch [862\/3000]: Train loss: 2.7017, Valid loss: 2.6872 Epoch [863\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.35it\/s, loss=2.56] Epoch [863\/3000]: Train loss: 2.7368, Valid loss: 3.4247 Epoch [864\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.86it\/s, loss=2.08] Epoch [864\/3000]: Train loss: 2.7538, Valid loss: 2.3674 Epoch [865\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.77it\/s, loss=1.92] Epoch [865\/3000]: Train loss: 2.3095, Valid loss: 2.7498 Epoch [866\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 66.24it\/s, loss=3.32] Epoch [866\/3000]: Train loss: 2.3412, Valid loss: 2.6365 Epoch [867\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.88it\/s, loss=1.58] Epoch [867\/3000]: Train loss: 2.4126, Valid loss: 2.5921 Epoch [868\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.91it\/s, loss=3.63] Epoch [868\/3000]: Train loss: 2.6062, Valid loss: 3.6302 Epoch [869\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.45it\/s, loss=2.04] Epoch [869\/3000]: Train loss: 2.7519, Valid loss: 3.1693 Epoch [870\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.93it\/s, loss=3.25] Epoch [870\/3000]: Train loss: 2.9045, Valid loss: 2.5013 Epoch [871\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.62it\/s, loss=2.66] Epoch [871\/3000]: Train loss: 2.8114, Valid loss: 4.1369 Epoch [872\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.54it\/s, loss=2.95] Epoch [872\/3000]: Train loss: 2.9402, Valid loss: 2.0786 Epoch [873\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.06it\/s, loss=2.95] Epoch [873\/3000]: Train loss: 2.4181, Valid loss: 4.4071 Epoch [874\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.22it\/s, loss=1.99] Epoch [874\/3000]: Train loss: 2.9907, Valid loss: 2.1670 Epoch [875\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.10it\/s, loss=1.98] Epoch [875\/3000]: Train loss: 2.0673, Valid loss: 2.1030 Epoch [876\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.38it\/s, loss=2.65] Epoch [876\/3000]: Train loss: 2.1801, Valid loss: 2.2942 Epoch [877\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.34it\/s, loss=1.77] Epoch [877\/3000]: Train loss: 1.9787, Valid loss: 2.7296 Epoch [878\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.35it\/s, loss=1.86] Epoch [878\/3000]: Train loss: 2.0672, Valid loss: 2.7177 Epoch [879\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.23it\/s, loss=2.56] Epoch [879\/3000]: Train loss: 2.2602, Valid loss: 2.5951 Epoch [880\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.06it\/s, loss=2.53] Epoch [880\/3000]: Train loss: 2.4976, Valid loss: 2.3757 Epoch [881\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.12it\/s, loss=2.01] Epoch [881\/3000]: Train loss: 2.0402, Valid loss: 2.4053 Epoch [882\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.02it\/s, loss=2.72] Epoch [882\/3000]: Train loss: 2.2910, Valid loss: 1.9425 Epoch [883\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.41it\/s, loss=2.05] Epoch [883\/3000]: Train loss: 2.0362, Valid loss: 3.1791 Epoch [884\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.04it\/s, loss=4] Epoch [884\/3000]: Train loss: 3.2178, Valid loss: 3.0512 Epoch [885\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.13it\/s, loss=3.15] Epoch [885\/3000]: Train loss: 2.6637, Valid loss: 2.9566 Epoch [886\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.07it\/s, loss=1.45] Epoch [886\/3000]: Train loss: 2.4373, Valid loss: 2.1969 Epoch [887\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.62it\/s, loss=2.35] Epoch [887\/3000]: Train loss: 2.0670, Valid loss: 2.4368 Epoch [888\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.94it\/s, loss=2.1] Epoch [888\/3000]: Train loss: 2.1093, Valid loss: 2.9813 Epoch [889\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.95it\/s, loss=2.01] Epoch [889\/3000]: Train loss: 2.4776, Valid loss: 2.7474 Epoch [890\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.35it\/s, loss=2.3] Epoch [890\/3000]: Train loss: 2.2814, Valid loss: 2.2560 Epoch [891\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.79it\/s, loss=2.12] Epoch [891\/3000]: Train loss: 2.0626, Valid loss: 2.6138 Epoch [892\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.05it\/s, loss=2.02] Epoch [892\/3000]: Train loss: 2.6792, Valid loss: 3.0031 Epoch [893\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.12it\/s, loss=2.46] Epoch [893\/3000]: Train loss: 2.2775, Valid loss: 2.4251 Epoch [894\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.11it\/s, loss=2.36] Epoch [894\/3000]: Train loss: 2.1438, Valid loss: 3.1597 Epoch [895\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.89it\/s, loss=2.34] Epoch [895\/3000]: Train loss: 2.2325, Valid loss: 2.8278 Epoch [896\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.26it\/s, loss=2.17] Epoch [896\/3000]: Train loss: 2.3480, Valid loss: 2.0802 Epoch [897\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.20it\/s, loss=1.98] Epoch [897\/3000]: Train loss: 2.2947, Valid loss: 2.3422 Epoch [898\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.69it\/s, loss=2.33] Epoch [898\/3000]: Train loss: 2.1555, Valid loss: 2.3923 Epoch [899\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.60it\/s, loss=2.65] Epoch [899\/3000]: Train loss: 2.2700, Valid loss: 2.1813 Epoch [900\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.74it\/s, loss=2.68] Epoch [900\/3000]: Train loss: 2.1202, Valid loss: 2.5544 Epoch [901\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.30it\/s, loss=2.02] Epoch [901\/3000]: Train loss: 2.0669, Valid loss: 2.3239 Epoch [902\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.92it\/s, loss=2.41] Epoch [902\/3000]: Train loss: 1.9929, Valid loss: 2.2936 Epoch [903\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.72it\/s, loss=2.67] Epoch [903\/3000]: Train loss: 2.0729, Valid loss: 2.0862 Epoch [904\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.61it\/s, loss=2.02] Epoch [904\/3000]: Train loss: 2.3733, Valid loss: 2.1848 Epoch [905\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 52.09it\/s, loss=1.93] Epoch [905\/3000]: Train loss: 2.2739, Valid loss: 3.5036 Epoch [906\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.10it\/s, loss=2.85] Epoch [906\/3000]: Train loss: 2.2002, Valid loss: 3.0927 Epoch [907\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.82it\/s, loss=3.12] Epoch [907\/3000]: Train loss: 2.3541, Valid loss: 3.2267 Epoch [908\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.75it\/s, loss=1.84] Epoch [908\/3000]: Train loss: 2.4689, Valid loss: 2.2507 Epoch [909\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.38it\/s, loss=2.29] Epoch [909\/3000]: Train loss: 2.1896, Valid loss: 2.3689 Epoch [910\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.98it\/s, loss=2.49] Epoch [910\/3000]: Train loss: 2.4626, Valid loss: 2.9757 Epoch [911\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.46it\/s, loss=2.7] Epoch [911\/3000]: Train loss: 2.4797, Valid loss: 2.0306 Epoch [912\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.04it\/s, loss=3.41] Epoch [912\/3000]: Train loss: 2.4831, Valid loss: 3.9007 Epoch [913\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.69it\/s, loss=3.61] Epoch [913\/3000]: Train loss: 3.2113, Valid loss: 2.9082 Epoch [914\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.82it\/s, loss=5.75] Epoch [914\/3000]: Train loss: 4.0151, Valid loss: 4.1958 Epoch [915\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.95it\/s, loss=1.95] Epoch [915\/3000]: Train loss: 3.0369, Valid loss: 6.3685 Epoch [916\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.79it\/s, loss=3.31] Epoch [916\/3000]: Train loss: 3.9303, Valid loss: 2.8043 Epoch [917\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.94it\/s, loss=1.68] Epoch [917\/3000]: Train loss: 3.4420, Valid loss: 3.6383 Epoch [918\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.06it\/s, loss=1.97] Epoch [918\/3000]: Train loss: 2.2353, Valid loss: 1.9567 Epoch [919\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 65.74it\/s, loss=2.01] Epoch [919\/3000]: Train loss: 2.3713, Valid loss: 3.5012 Epoch [920\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.02it\/s, loss=2.94] Epoch [920\/3000]: Train loss: 2.6495, Valid loss: 2.5708 Epoch [921\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.95it\/s, loss=2.13] Epoch [921\/3000]: Train loss: 2.2062, Valid loss: 2.2666 Epoch [922\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.21it\/s, loss=2.07] Epoch [922\/3000]: Train loss: 2.0631, Valid loss: 2.1188 Epoch [923\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.38it\/s, loss=2.6] Epoch [923\/3000]: Train loss: 3.0046, Valid loss: 4.7100 Epoch [924\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.97it\/s, loss=2.72] Epoch [924\/3000]: Train loss: 2.6115, Valid loss: 2.4387 Epoch [925\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.72it\/s, loss=1.78] Epoch [925\/3000]: Train loss: 2.1129, Valid loss: 2.1061 Epoch [926\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 66.70it\/s, loss=1.81] Epoch [926\/3000]: Train loss: 1.9497, Valid loss: 3.2694 Epoch [927\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.55it\/s, loss=4.83] Epoch [927\/3000]: Train loss: 3.2902, Valid loss: 2.3426 Epoch [928\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.47it\/s, loss=2.84] Epoch [928\/3000]: Train loss: 3.0260, Valid loss: 5.0188 Epoch [929\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.33it\/s, loss=2.38] Epoch [929\/3000]: Train loss: 4.1412, Valid loss: 6.9756 Epoch [930\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 16.07it\/s, loss=3.14] Epoch [930\/3000]: Train loss: 4.8976, Valid loss: 7.7244 Epoch [931\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.91it\/s, loss=5.07] Epoch [931\/3000]: Train loss: 4.4371, Valid loss: 2.3374 Epoch [932\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.17it\/s, loss=4.85] Epoch [932\/3000]: Train loss: 3.3403, Valid loss: 3.8953 Epoch [933\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.95it\/s, loss=3.29] Epoch [933\/3000]: Train loss: 2.6462, Valid loss: 4.0221 Epoch [934\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.62it\/s, loss=2.73] Epoch [934\/3000]: Train loss: 2.3979, Valid loss: 2.6022 Epoch [935\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 65.57it\/s, loss=1.79] Epoch [935\/3000]: Train loss: 2.0473, Valid loss: 2.2970 Epoch [936\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.60it\/s, loss=2.25] Epoch [936\/3000]: Train loss: 2.3213, Valid loss: 4.2771 Epoch [937\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.37it\/s, loss=2.26] Epoch [937\/3000]: Train loss: 2.7881, Valid loss: 2.8667 Epoch [938\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.39it\/s, loss=2.12] Epoch [938\/3000]: Train loss: 2.0967, Valid loss: 2.6100 Epoch [939\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.39it\/s, loss=1.66] Epoch [939\/3000]: Train loss: 1.9948, Valid loss: 2.1340 Epoch [940\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.56it\/s, loss=2.07] Epoch [940\/3000]: Train loss: 2.2086, Valid loss: 3.3330 Epoch [941\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.50it\/s, loss=2.6] Epoch [941\/3000]: Train loss: 2.5955, Valid loss: 2.2535 Epoch [942\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.89it\/s, loss=1.99] Epoch [942\/3000]: Train loss: 2.2653, Valid loss: 2.8166 Epoch [943\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.72it\/s, loss=3.25] Epoch [943\/3000]: Train loss: 2.3210, Valid loss: 3.9312 Epoch [944\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.74it\/s, loss=2.17] Epoch [944\/3000]: Train loss: 2.3949, Valid loss: 2.9773 Epoch [945\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.06it\/s, loss=1.85] Epoch [945\/3000]: Train loss: 2.2001, Valid loss: 2.1214 Epoch [946\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.26it\/s, loss=2.43] Epoch [946\/3000]: Train loss: 2.1671, Valid loss: 2.4949 Epoch [947\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.26it\/s, loss=2.6] Epoch [947\/3000]: Train loss: 2.3004, Valid loss: 3.3704 Epoch [948\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.05it\/s, loss=2.45] Epoch [948\/3000]: Train loss: 2.6889, Valid loss: 3.3064 Epoch [949\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.05it\/s, loss=1.99] Epoch [949\/3000]: Train loss: 2.5949, Valid loss: 2.5061 Epoch [950\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.74it\/s, loss=3.35] Epoch [950\/3000]: Train loss: 2.6194, Valid loss: 4.9724 Epoch [951\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.66it\/s, loss=2.2] Epoch [951\/3000]: Train loss: 2.6057, Valid loss: 2.0025 Epoch [952\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.03it\/s, loss=2.1] Epoch [952\/3000]: Train loss: 2.0790, Valid loss: 3.0761 Epoch [953\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.77it\/s, loss=2.01] Epoch [953\/3000]: Train loss: 2.0404, Valid loss: 2.1603 Epoch [954\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.19it\/s, loss=2.1] Epoch [954\/3000]: Train loss: 2.1094, Valid loss: 3.1278 Epoch [955\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.46it\/s, loss=3.03] Epoch [955\/3000]: Train loss: 2.4955, Valid loss: 3.0328 Epoch [956\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 103.88it\/s, loss=1.48] Epoch [956\/3000]: Train loss: 2.2843, Valid loss: 2.4771 Epoch [957\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.88it\/s, loss=1.89] Epoch [957\/3000]: Train loss: 2.1496, Valid loss: 2.2188 Epoch [958\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.62it\/s, loss=2.36] Epoch [958\/3000]: Train loss: 2.1093, Valid loss: 3.0657 Epoch [959\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.47it\/s, loss=2.46] Epoch [959\/3000]: Train loss: 2.7053, Valid loss: 2.9420 Epoch [960\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.86it\/s, loss=2.04] Epoch [960\/3000]: Train loss: 2.7291, Valid loss: 2.2217 Epoch [961\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.11it\/s, loss=2.12] Epoch [961\/3000]: Train loss: 2.0954, Valid loss: 2.3010 Epoch [962\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.33it\/s, loss=2.57] Epoch [962\/3000]: Train loss: 2.0369, Valid loss: 2.5768 Epoch [963\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.59it\/s, loss=2.91] Epoch [963\/3000]: Train loss: 2.3613, Valid loss: 3.1313 Epoch [964\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.15it\/s, loss=1.69] Epoch [964\/3000]: Train loss: 2.6132, Valid loss: 3.7004 Epoch [965\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.12it\/s, loss=5.45] Epoch [965\/3000]: Train loss: 4.7332, Valid loss: 3.0305 Epoch [966\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.22it\/s, loss=2.12] Epoch [966\/3000]: Train loss: 2.9430, Valid loss: 2.0382 Epoch [967\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.00it\/s, loss=2.1] Epoch [967\/3000]: Train loss: 3.0905, Valid loss: 2.0838 Epoch [968\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.86it\/s, loss=1.65] Epoch [968\/3000]: Train loss: 2.0256, Valid loss: 3.1528 Epoch [969\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.17it\/s, loss=1.87] Epoch [969\/3000]: Train loss: 2.2391, Valid loss: 3.3495 Epoch [970\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.75it\/s, loss=1.79] Epoch [970\/3000]: Train loss: 2.6245, Valid loss: 2.6357 Epoch [971\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.59it\/s, loss=3.89] Epoch [971\/3000]: Train loss: 2.4228, Valid loss: 4.6926 Epoch [972\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.46it\/s, loss=2.91] Epoch [972\/3000]: Train loss: 2.7776, Valid loss: 2.0564 Epoch [973\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.15it\/s, loss=2.31] Epoch [973\/3000]: Train loss: 2.3609, Valid loss: 2.9462 Epoch [974\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.59it\/s, loss=2.51] Epoch [974\/3000]: Train loss: 2.3595, Valid loss: 2.0338 Epoch [975\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.03it\/s, loss=2.03] Epoch [975\/3000]: Train loss: 2.1098, Valid loss: 2.6080 Epoch [976\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.57it\/s, loss=2.66] Epoch [976\/3000]: Train loss: 2.4148, Valid loss: 2.4917 Epoch [977\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.89it\/s, loss=2.14] Epoch [977\/3000]: Train loss: 2.1704, Valid loss: 2.4740 Epoch [978\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.56it\/s, loss=2.65] Epoch [978\/3000]: Train loss: 2.2120, Valid loss: 2.3911 Epoch [979\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.14it\/s, loss=1.7] Epoch [979\/3000]: Train loss: 2.0427, Valid loss: 2.0137 Epoch [980\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.69it\/s, loss=2.2] Epoch [980\/3000]: Train loss: 2.0226, Valid loss: 2.4398 Epoch [981\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.84it\/s, loss=2] Epoch [981\/3000]: Train loss: 2.0125, Valid loss: 4.4904 Epoch [982\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.01it\/s, loss=2.05] Epoch [982\/3000]: Train loss: 2.4721, Valid loss: 2.0388 Epoch [983\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.73it\/s, loss=2.17] Epoch [983\/3000]: Train loss: 2.3436, Valid loss: 2.4680 Epoch [984\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.42it\/s, loss=2.32] Epoch [984\/3000]: Train loss: 2.8695, Valid loss: 3.2027 Epoch [985\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.33it\/s, loss=1.5] Epoch [985\/3000]: Train loss: 2.0732, Valid loss: 2.1571 Epoch [986\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.88it\/s, loss=2.39] Epoch [986\/3000]: Train loss: 2.0363, Valid loss: 2.1272 Epoch [987\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.66it\/s, loss=2.46] Epoch [987\/3000]: Train loss: 2.0879, Valid loss: 2.7579 Epoch [988\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 65.92it\/s, loss=1.69] Epoch [988\/3000]: Train loss: 2.0326, Valid loss: 2.2296 Epoch [989\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.03it\/s, loss=2.42] Epoch [989\/3000]: Train loss: 2.1111, Valid loss: 2.2968 Epoch [990\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.59it\/s, loss=2.04] Epoch [990\/3000]: Train loss: 2.2624, Valid loss: 2.2719 Epoch [991\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.26it\/s, loss=1.95] Epoch [991\/3000]: Train loss: 1.9526, Valid loss: 2.0286 Epoch [992\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 62.64it\/s, loss=1.52] Epoch [992\/3000]: Train loss: 1.9969, Valid loss: 2.4371 Epoch [993\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.01it\/s, loss=1.76] Epoch [993\/3000]: Train loss: 2.0880, Valid loss: 2.6027 Epoch [994\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.23it\/s, loss=2.15] Epoch [994\/3000]: Train loss: 2.2378, Valid loss: 2.3017 Epoch [995\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.32it\/s, loss=1.96] Epoch [995\/3000]: Train loss: 2.0193, Valid loss: 2.4376 Epoch [996\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.42it\/s, loss=2.53] Epoch [996\/3000]: Train loss: 2.1029, Valid loss: 3.3215 Epoch [997\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.18it\/s, loss=2.42] Epoch [997\/3000]: Train loss: 2.4056, Valid loss: 2.6862 Epoch [998\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 63.65it\/s, loss=1.69] Epoch [998\/3000]: Train loss: 2.0405, Valid loss: 2.3032 Epoch [999\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.58it\/s, loss=1.74] Epoch [999\/3000]: Train loss: 2.1001, Valid loss: 2.2598 Epoch [1000\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.92it\/s, loss=1.86] Epoch [1000\/3000]: Train loss: 2.0641, Valid loss: 2.8542 Epoch [1001\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.00it\/s, loss=1.9] Epoch [1001\/3000]: Train loss: 2.3828, Valid loss: 3.6657 Epoch [1002\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.64it\/s, loss=2.02] Epoch [1002\/3000]: Train loss: 2.4294, Valid loss: 2.2234 Epoch [1003\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.07it\/s, loss=2.75] Epoch [1003\/3000]: Train loss: 2.2659, Valid loss: 2.2062 Epoch [1004\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.97it\/s, loss=2.52] Epoch [1004\/3000]: Train loss: 2.1813, Valid loss: 3.3185 Epoch [1005\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.68it\/s, loss=2.15] Epoch [1005\/3000]: Train loss: 2.6227, Valid loss: 2.4367 Epoch [1006\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.54it\/s, loss=1.92] Epoch [1006\/3000]: Train loss: 2.0849, Valid loss: 2.7231 Epoch [1007\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.81it\/s, loss=2.18] Epoch [1007\/3000]: Train loss: 2.2441, Valid loss: 3.0595 Epoch [1008\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.10it\/s, loss=1.67] Epoch [1008\/3000]: Train loss: 2.2299, Valid loss: 2.5243 Epoch [1009\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 62.34it\/s, loss=2.44] Epoch [1009\/3000]: Train loss: 2.1809, Valid loss: 2.1872 Epoch [1010\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.18it\/s, loss=1.61] Epoch [1010\/3000]: Train loss: 2.0497, Valid loss: 2.6462 Epoch [1011\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.01it\/s, loss=1.81] Epoch [1011\/3000]: Train loss: 2.1178, Valid loss: 2.1910 Epoch [1012\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 58.70it\/s, loss=2.81] Epoch [1012\/3000]: Train loss: 2.5254, Valid loss: 3.7281 Epoch [1013\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.38it\/s, loss=3.62] Epoch [1013\/3000]: Train loss: 2.7798, Valid loss: 1.9752 Epoch [1014\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 63.94it\/s, loss=1.47] Epoch [1014\/3000]: Train loss: 2.1562, Valid loss: 1.9572 Epoch [1015\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.05it\/s, loss=2.15] Epoch [1015\/3000]: Train loss: 1.9697, Valid loss: 4.1624 Epoch [1016\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.67it\/s, loss=3.04] Epoch [1016\/3000]: Train loss: 2.7885, Valid loss: 2.3250 Epoch [1017\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.16it\/s, loss=1.98] Epoch [1017\/3000]: Train loss: 2.1062, Valid loss: 2.0646 Epoch [1018\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.92it\/s, loss=2.71] Epoch [1018\/3000]: Train loss: 2.1594, Valid loss: 2.1795 Epoch [1019\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.74it\/s, loss=2.47] Epoch [1019\/3000]: Train loss: 2.2191, Valid loss: 3.8692 Epoch [1020\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.58it\/s, loss=1.86] Epoch [1020\/3000]: Train loss: 2.4280, Valid loss: 2.0427 Epoch [1021\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.68it\/s, loss=2.32] Epoch [1021\/3000]: Train loss: 2.0096, Valid loss: 2.3074 Epoch [1022\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.12it\/s, loss=2.32] Epoch [1022\/3000]: Train loss: 2.2626, Valid loss: 2.3879 Epoch [1023\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.59it\/s, loss=2.79] Epoch [1023\/3000]: Train loss: 2.0926, Valid loss: 2.1472 Epoch [1024\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 100.51it\/s, loss=2.39] Epoch [1024\/3000]: Train loss: 2.2135, Valid loss: 3.0137 Epoch [1025\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.61it\/s, loss=1.91] Epoch [1025\/3000]: Train loss: 2.3651, Valid loss: 2.3129 Epoch [1026\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.20it\/s, loss=2.37] Epoch [1026\/3000]: Train loss: 2.0644, Valid loss: 2.3775 Epoch [1027\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.96it\/s, loss=1.43] Epoch [1027\/3000]: Train loss: 1.8633, Valid loss: 2.6200 Epoch [1028\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.23it\/s, loss=1.84] Epoch [1028\/3000]: Train loss: 1.9453, Valid loss: 1.8791 Saving model with loss 1.879… Epoch [1029\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.79it\/s, loss=2.11] Epoch [1029\/3000]: Train loss: 2.0185, Valid loss: 2.8176 Epoch [1030\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 61.53it\/s, loss=1.59] Epoch [1030\/3000]: Train loss: 2.0104, Valid loss: 1.7679 Saving model with loss 1.768… Epoch [1031\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.71it\/s, loss=1.64] Epoch [1031\/3000]: Train loss: 1.9484, Valid loss: 2.1067 Epoch [1032\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.05it\/s, loss=2.07] Epoch [1032\/3000]: Train loss: 2.0531, Valid loss: 1.9497 Epoch [1033\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.15it\/s, loss=1.47] Epoch [1033\/3000]: Train loss: 2.0849, Valid loss: 2.2711 Epoch [1034\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.67it\/s, loss=1.45] Epoch [1034\/3000]: Train loss: 2.0280, Valid loss: 2.2432 Epoch [1035\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.56it\/s, loss=1.85] Epoch [1035\/3000]: Train loss: 2.3867, Valid loss: 2.1267 Epoch [1036\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.78it\/s, loss=2.75] Epoch [1036\/3000]: Train loss: 2.1612, Valid loss: 3.1898 Epoch [1037\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.60it\/s, loss=2.35] Epoch [1037\/3000]: Train loss: 2.0822, Valid loss: 3.0279 Epoch [1038\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.52it\/s, loss=2.71] Epoch [1038\/3000]: Train loss: 2.1648, Valid loss: 2.1501 Epoch [1039\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.75it\/s, loss=1.67] Epoch [1039\/3000]: Train loss: 2.2515, Valid loss: 2.6710 Epoch [1040\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.19it\/s, loss=2.04] Epoch [1040\/3000]: Train loss: 2.2266, Valid loss: 1.9307 Epoch [1041\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.59it\/s, loss=2.03] Epoch [1041\/3000]: Train loss: 2.0912, Valid loss: 2.8922 Epoch [1042\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.95it\/s, loss=2.2] Epoch [1042\/3000]: Train loss: 1.9755, Valid loss: 2.5946 Epoch [1043\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.05it\/s, loss=2.3] Epoch [1043\/3000]: Train loss: 1.9623, Valid loss: 2.0344 Epoch [1044\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.24it\/s, loss=2.31] Epoch [1044\/3000]: Train loss: 2.0129, Valid loss: 2.2655 Epoch [1045\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 102.21it\/s, loss=2.81] Epoch [1045\/3000]: Train loss: 2.2009, Valid loss: 2.3853 Epoch [1046\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 102.32it\/s, loss=2.69] Epoch [1046\/3000]: Train loss: 2.3325, Valid loss: 3.5285 Epoch [1047\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 101.78it\/s, loss=2.63] Epoch [1047\/3000]: Train loss: 2.5418, Valid loss: 3.6480 Epoch [1048\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.06it\/s, loss=1.82] Epoch [1048\/3000]: Train loss: 2.5795, Valid loss: 4.4380 Epoch [1049\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.39it\/s, loss=3.83] Epoch [1049\/3000]: Train loss: 3.3799, Valid loss: 2.6621 Epoch [1050\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.72it\/s, loss=2.43] Epoch [1050\/3000]: Train loss: 2.3231, Valid loss: 2.3659 Epoch [1051\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.03it\/s, loss=2.32] Epoch [1051\/3000]: Train loss: 2.1064, Valid loss: 2.4478 Epoch [1052\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.08it\/s, loss=2.05] Epoch [1052\/3000]: Train loss: 2.1899, Valid loss: 2.7660 Epoch [1053\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.73it\/s, loss=2.37] Epoch [1053\/3000]: Train loss: 2.2598, Valid loss: 2.4063 Epoch [1054\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.64it\/s, loss=1.91] Epoch [1054\/3000]: Train loss: 2.0547, Valid loss: 3.1613 Epoch [1055\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.08it\/s, loss=2.06] Epoch [1055\/3000]: Train loss: 2.4659, Valid loss: 2.1214 Epoch [1056\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.46it\/s, loss=2.19] Epoch [1056\/3000]: Train loss: 2.0581, Valid loss: 2.4068 Epoch [1057\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.78it\/s, loss=1.77] Epoch [1057\/3000]: Train loss: 2.0005, Valid loss: 1.9946 Epoch [1058\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.02it\/s, loss=1.88] Epoch [1058\/3000]: Train loss: 2.2118, Valid loss: 4.8308 Epoch [1059\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.25it\/s, loss=2.99] Epoch [1059\/3000]: Train loss: 2.7443, Valid loss: 1.9769 Epoch [1060\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.75it\/s, loss=2.53] Epoch [1060\/3000]: Train loss: 2.1432, Valid loss: 2.4222 Epoch [1061\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.52it\/s, loss=2.16] Epoch [1061\/3000]: Train loss: 1.9825, Valid loss: 2.4116 Epoch [1062\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.34it\/s, loss=1.84] Epoch [1062\/3000]: Train loss: 2.0326, Valid loss: 2.5910 Epoch [1063\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.38it\/s, loss=1.32] Epoch [1063\/3000]: Train loss: 2.0590, Valid loss: 2.1250 Epoch [1064\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.89it\/s, loss=2.41] Epoch [1064\/3000]: Train loss: 1.9173, Valid loss: 2.3065 Epoch [1065\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.11it\/s, loss=1.29] Epoch [1065\/3000]: Train loss: 1.9922, Valid loss: 1.8383 Epoch [1066\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.14it\/s, loss=2.02] Epoch [1066\/3000]: Train loss: 2.0248, Valid loss: 2.8981 Epoch [1067\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.58it\/s, loss=2.66] Epoch [1067\/3000]: Train loss: 2.4472, Valid loss: 2.1867 Epoch [1068\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.50it\/s, loss=1.59] Epoch [1068\/3000]: Train loss: 2.6691, Valid loss: 2.6492 Epoch [1069\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.48it\/s, loss=2.18] Epoch [1069\/3000]: Train loss: 2.1192, Valid loss: 2.1174 Epoch [1070\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.68it\/s, loss=1.75] Epoch [1070\/3000]: Train loss: 1.8910, Valid loss: 2.3717 Epoch [1071\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.79it\/s, loss=1.57] Epoch [1071\/3000]: Train loss: 2.1141, Valid loss: 2.6095 Epoch [1072\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.50it\/s, loss=1.87] Epoch [1072\/3000]: Train loss: 1.9414, Valid loss: 2.7032 Epoch [1073\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.47it\/s, loss=1.63] Epoch [1073\/3000]: Train loss: 1.9717, Valid loss: 2.0872 Epoch [1074\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.87it\/s, loss=2.49] Epoch [1074\/3000]: Train loss: 2.2414, Valid loss: 2.7155 Epoch [1075\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.52it\/s, loss=4.82] Epoch [1075\/3000]: Train loss: 2.7419, Valid loss: 2.4529 Epoch [1076\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.25it\/s, loss=1.91] Epoch [1076\/3000]: Train loss: 2.7485, Valid loss: 3.6566 Epoch [1077\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.63it\/s, loss=2.06] Epoch [1077\/3000]: Train loss: 1.9694, Valid loss: 2.5944 Epoch [1078\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.69it\/s, loss=2.29] Epoch [1078\/3000]: Train loss: 2.0096, Valid loss: 2.9836 Epoch [1079\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.16it\/s, loss=1.57] Epoch [1079\/3000]: Train loss: 2.3674, Valid loss: 2.6217 Epoch [1080\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.13it\/s, loss=2.29] Epoch [1080\/3000]: Train loss: 2.0295, Valid loss: 2.0952 Epoch [1081\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.52it\/s, loss=1.77] Epoch [1081\/3000]: Train loss: 2.4413, Valid loss: 2.2253 Epoch [1082\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.76it\/s, loss=2.33] Epoch [1082\/3000]: Train loss: 2.0323, Valid loss: 1.9956 Epoch [1083\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.07it\/s, loss=1.88] Epoch [1083\/3000]: Train loss: 2.1715, Valid loss: 2.3982 Epoch [1084\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.06it\/s, loss=2.69] Epoch [1084\/3000]: Train loss: 2.2746, Valid loss: 2.0398 Epoch [1085\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.87it\/s, loss=2.22] Epoch [1085\/3000]: Train loss: 1.9340, Valid loss: 2.3730 Epoch [1086\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 18.03it\/s, loss=1.85] Epoch [1086\/3000]: Train loss: 2.1744, Valid loss: 2.7053 Epoch [1087\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.16it\/s, loss=2.34] Epoch [1087\/3000]: Train loss: 2.2340, Valid loss: 1.9861 Epoch [1088\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.62it\/s, loss=2.35] Epoch [1088\/3000]: Train loss: 2.7828, Valid loss: 3.0920 Epoch [1089\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.12it\/s, loss=2.56] Epoch [1089\/3000]: Train loss: 2.4650, Valid loss: 2.3381 Epoch [1090\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.11it\/s, loss=2.1] Epoch [1090\/3000]: Train loss: 1.9480, Valid loss: 2.2243 Epoch [1091\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.69it\/s, loss=1.69] Epoch [1091\/3000]: Train loss: 2.1121, Valid loss: 2.4451 Epoch [1092\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.11it\/s, loss=2.07] Epoch [1092\/3000]: Train loss: 2.1436, Valid loss: 2.7633 Epoch [1093\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.46it\/s, loss=2.06] Epoch [1093\/3000]: Train loss: 2.2063, Valid loss: 2.5687 Epoch [1094\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.85it\/s, loss=2.61] Epoch [1094\/3000]: Train loss: 2.3274, Valid loss: 2.6123 Epoch [1095\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.93it\/s, loss=1.57] Epoch [1095\/3000]: Train loss: 2.0340, Valid loss: 1.9792 Epoch [1096\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.28it\/s, loss=2.22] Epoch [1096\/3000]: Train loss: 2.1518, Valid loss: 3.6895 Epoch [1097\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.79it\/s, loss=3.2] Epoch [1097\/3000]: Train loss: 2.4032, Valid loss: 2.5281 Epoch [1098\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.47it\/s, loss=2.59] Epoch [1098\/3000]: Train loss: 2.4501, Valid loss: 2.5950 Epoch [1099\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.19it\/s, loss=3.09] Epoch [1099\/3000]: Train loss: 2.2170, Valid loss: 3.7861 Epoch [1100\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.97it\/s, loss=2.03] Epoch [1100\/3000]: Train loss: 2.1277, Valid loss: 2.5883 Epoch [1101\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.88it\/s, loss=2.36] Epoch [1101\/3000]: Train loss: 2.1391, Valid loss: 2.2211 Epoch [1102\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.81it\/s, loss=2.5] Epoch [1102\/3000]: Train loss: 3.0798, Valid loss: 2.9283 Epoch [1103\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.40it\/s, loss=1.92] Epoch [1103\/3000]: Train loss: 2.3848, Valid loss: 3.2628 Epoch [1104\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.02it\/s, loss=2.19] Epoch [1104\/3000]: Train loss: 2.4607, Valid loss: 2.6715 Epoch [1105\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.17it\/s, loss=2.68] Epoch [1105\/3000]: Train loss: 2.3147, Valid loss: 3.6739 Epoch [1106\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.21it\/s, loss=2.35] Epoch [1106\/3000]: Train loss: 3.1438, Valid loss: 3.7574 Epoch [1107\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.06it\/s, loss=2.49] Epoch [1107\/3000]: Train loss: 2.8547, Valid loss: 2.5453 Epoch [1108\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.24it\/s, loss=1.6] Epoch [1108\/3000]: Train loss: 2.6774, Valid loss: 2.9562 Epoch [1109\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.14it\/s, loss=3.37] Epoch [1109\/3000]: Train loss: 2.8459, Valid loss: 2.5497 Epoch [1110\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.65it\/s, loss=1.94] Epoch [1110\/3000]: Train loss: 2.1749, Valid loss: 2.5980 Epoch [1111\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.73it\/s, loss=1.39] Epoch [1111\/3000]: Train loss: 2.0200, Valid loss: 2.3895 Epoch [1112\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.39it\/s, loss=1.3] Epoch [1112\/3000]: Train loss: 1.8973, Valid loss: 2.0186 Epoch [1113\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.71it\/s, loss=2.26] Epoch [1113\/3000]: Train loss: 2.2974, Valid loss: 2.2092 Epoch [1114\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.37it\/s, loss=1.6] Epoch [1114\/3000]: Train loss: 1.8537, Valid loss: 2.1920 Epoch [1115\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 60.59it\/s, loss=2.27] Epoch [1115\/3000]: Train loss: 1.9264, Valid loss: 2.4505 Epoch [1116\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.07it\/s, loss=3.38] Epoch [1116\/3000]: Train loss: 2.4390, Valid loss: 2.1021 Epoch [1117\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.55it\/s, loss=1.84] Epoch [1117\/3000]: Train loss: 2.2439, Valid loss: 4.3158 Epoch [1118\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.52it\/s, loss=2.81] Epoch [1118\/3000]: Train loss: 3.1312, Valid loss: 1.9630 Epoch [1119\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.81it\/s, loss=2.48] Epoch [1119\/3000]: Train loss: 2.0222, Valid loss: 2.5790 Epoch [1120\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.76it\/s, loss=1.56] Epoch [1120\/3000]: Train loss: 1.8984, Valid loss: 1.9421 Epoch [1121\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.05it\/s, loss=2.21] Epoch [1121\/3000]: Train loss: 2.7170, Valid loss: 3.9022 Epoch [1122\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.80it\/s, loss=2.64] Epoch [1122\/3000]: Train loss: 2.9730, Valid loss: 1.9501 Epoch [1123\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.63it\/s, loss=2.98] Epoch [1123\/3000]: Train loss: 2.3689, Valid loss: 2.0652 Epoch [1124\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.22it\/s, loss=1.35] Epoch [1124\/3000]: Train loss: 1.9819, Valid loss: 2.0387 Epoch [1125\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 64.90it\/s, loss=2.21] Epoch [1125\/3000]: Train loss: 1.9650, Valid loss: 3.0097 Epoch [1126\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.30it\/s, loss=2.67] Epoch [1126\/3000]: Train loss: 2.6931, Valid loss: 1.9548 Epoch [1127\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.68it\/s, loss=3.4] Epoch [1127\/3000]: Train loss: 2.2653, Valid loss: 2.3290 Epoch [1128\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.57it\/s, loss=1.64] Epoch [1128\/3000]: Train loss: 2.4302, Valid loss: 3.2480 Epoch [1129\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.25it\/s, loss=2.13] Epoch [1129\/3000]: Train loss: 2.2159, Valid loss: 2.2742 Epoch [1130\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.33it\/s, loss=2.49] Epoch [1130\/3000]: Train loss: 2.0426, Valid loss: 3.3686 Epoch [1131\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.06it\/s, loss=1.37] Epoch [1131\/3000]: Train loss: 2.1192, Valid loss: 2.7189 Epoch [1132\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.27it\/s, loss=3.45] Epoch [1132\/3000]: Train loss: 2.4296, Valid loss: 2.5381 Epoch [1133\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.98it\/s, loss=2.73] Epoch [1133\/3000]: Train loss: 2.3534, Valid loss: 2.6687 Epoch [1134\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.46it\/s, loss=1.81] Epoch [1134\/3000]: Train loss: 1.9058, Valid loss: 2.6501 Epoch [1135\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.37it\/s, loss=1.5] Epoch [1135\/3000]: Train loss: 2.1228, Valid loss: 2.2408 Epoch [1136\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.36it\/s, loss=1.99] Epoch [1136\/3000]: Train loss: 2.0527, Valid loss: 2.9517 Epoch [1137\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.00it\/s, loss=1.55] Epoch [1137\/3000]: Train loss: 2.4134, Valid loss: 3.2472 Epoch [1138\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 20.86it\/s, loss=2.87] Epoch [1138\/3000]: Train loss: 2.5617, Valid loss: 2.0178 Epoch [1139\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 24.10it\/s, loss=2.09] Epoch [1139\/3000]: Train loss: 2.1060, Valid loss: 2.5948 Epoch [1140\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.63it\/s, loss=3.51] Epoch [1140\/3000]: Train loss: 2.8959, Valid loss: 2.1483 Epoch [1141\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.96it\/s, loss=2.25] Epoch [1141\/3000]: Train loss: 2.0809, Valid loss: 2.8335 Epoch [1142\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.59it\/s, loss=2.83] Epoch [1142\/3000]: Train loss: 2.2137, Valid loss: 2.1483 Epoch [1143\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 44.07it\/s, loss=3.27] Epoch [1143\/3000]: Train loss: 3.2715, Valid loss: 4.4604 Epoch [1144\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 19.14it\/s, loss=5.7] Epoch [1144\/3000]: Train loss: 4.5022, Valid loss: 2.3168 Epoch [1145\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 47.91it\/s, loss=2.56] Epoch [1145\/3000]: Train loss: 2.8877, Valid loss: 2.2867 Epoch [1146\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.73it\/s, loss=2.72] Epoch [1146\/3000]: Train loss: 1.9712, Valid loss: 2.5072 Epoch [1147\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.06it\/s, loss=2.24] Epoch [1147\/3000]: Train loss: 2.1827, Valid loss: 2.1041 Epoch [1148\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.29it\/s, loss=1.59] Epoch [1148\/3000]: Train loss: 1.9945, Valid loss: 1.9968 Epoch [1149\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.62it\/s, loss=3.92] Epoch [1149\/3000]: Train loss: 2.7341, Valid loss: 3.1077 Epoch [1150\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.96it\/s, loss=2.35] Epoch [1150\/3000]: Train loss: 2.8353, Valid loss: 2.5634 Epoch [1151\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.43it\/s, loss=2.25] Epoch [1151\/3000]: Train loss: 2.0734, Valid loss: 2.0380 Epoch [1152\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 66.03it\/s, loss=1.83] Epoch [1152\/3000]: Train loss: 2.1039, Valid loss: 2.8012 Epoch [1153\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 59.81it\/s, loss=2.4] Epoch [1153\/3000]: Train loss: 2.1669, Valid loss: 2.1294 Epoch [1154\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.33it\/s, loss=1.55] Epoch [1154\/3000]: Train loss: 1.8946, Valid loss: 2.2131 Epoch [1155\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.81it\/s, loss=2.4] Epoch [1155\/3000]: Train loss: 1.9371, Valid loss: 2.2339 Epoch [1156\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.55it\/s, loss=2.53] Epoch [1156\/3000]: Train loss: 2.1178, Valid loss: 2.1705 Epoch [1157\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.15it\/s, loss=2.37] Epoch [1157\/3000]: Train loss: 1.9664, Valid loss: 2.2277 Epoch [1158\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.40it\/s, loss=2.25] Epoch [1158\/3000]: Train loss: 2.0340, Valid loss: 2.2424 Epoch [1159\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.53it\/s, loss=2.16] Epoch [1159\/3000]: Train loss: 2.0820, Valid loss: 2.5821 Epoch [1160\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.09it\/s, loss=1.97] Epoch [1160\/3000]: Train loss: 2.0145, Valid loss: 2.1060 Epoch [1161\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.61it\/s, loss=2.48] Epoch [1161\/3000]: Train loss: 2.0555, Valid loss: 2.4854 Epoch [1162\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.09it\/s, loss=1.98] Epoch [1162\/3000]: Train loss: 1.8847, Valid loss: 2.1596 Epoch [1163\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.18it\/s, loss=2.39] Epoch [1163\/3000]: Train loss: 1.9635, Valid loss: 2.3189 Epoch [1164\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.26it\/s, loss=2.27] Epoch [1164\/3000]: Train loss: 2.1244, Valid loss: 2.1817 Epoch [1165\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.40it\/s, loss=1.82] Epoch [1165\/3000]: Train loss: 1.9623, Valid loss: 2.2121 Epoch [1166\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.62it\/s, loss=2.11] Epoch [1166\/3000]: Train loss: 2.1043, Valid loss: 1.9843 Epoch [1167\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.06it\/s, loss=1.42] Epoch [1167\/3000]: Train loss: 1.8445, Valid loss: 2.3239 Epoch [1168\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.12it\/s, loss=1.69] Epoch [1168\/3000]: Train loss: 1.8607, Valid loss: 1.9228 Epoch [1169\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.14it\/s, loss=3.45] Epoch [1169\/3000]: Train loss: 2.3103, Valid loss: 2.6684 Epoch [1170\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.37it\/s, loss=3.28] Epoch [1170\/3000]: Train loss: 2.3347, Valid loss: 5.4839 Epoch [1171\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.91it\/s, loss=1.87] Epoch [1171\/3000]: Train loss: 2.5859, Valid loss: 2.6460 Epoch [1172\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 66.06it\/s, loss=2.33] Epoch [1172\/3000]: Train loss: 2.2196, Valid loss: 2.4250 Epoch [1173\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 61.56it\/s, loss=1.65] Epoch [1173\/3000]: Train loss: 1.9420, Valid loss: 2.3481 Epoch [1174\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.54it\/s, loss=2.31] Epoch [1174\/3000]: Train loss: 2.0912, Valid loss: 2.3928 Epoch [1175\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.55it\/s, loss=1.89] Epoch [1175\/3000]: Train loss: 2.0215, Valid loss: 2.1512 Epoch [1176\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.14it\/s, loss=1.97] Epoch [1176\/3000]: Train loss: 1.8648, Valid loss: 2.6259 Epoch [1177\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.03it\/s, loss=2.83] Epoch [1177\/3000]: Train loss: 1.9548, Valid loss: 2.3281 Epoch [1178\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.84it\/s, loss=1.68] Epoch [1178\/3000]: Train loss: 1.8958, Valid loss: 2.2941 Epoch [1179\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.31it\/s, loss=1.18] Epoch [1179\/3000]: Train loss: 2.2366, Valid loss: 4.0303 Epoch [1180\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.75it\/s, loss=1.51] Epoch [1180\/3000]: Train loss: 2.2681, Valid loss: 2.1389 Epoch [1181\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.85it\/s, loss=1.79] Epoch [1181\/3000]: Train loss: 1.8768, Valid loss: 1.9768 Epoch [1182\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.90it\/s, loss=2.74] Epoch [1182\/3000]: Train loss: 1.9210, Valid loss: 2.2629 Epoch [1183\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.14it\/s, loss=2.36] Epoch [1183\/3000]: Train loss: 1.9419, Valid loss: 2.0810 Epoch [1184\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.72it\/s, loss=1.81] Epoch [1184\/3000]: Train loss: 1.8356, Valid loss: 2.1134 Epoch [1185\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.31it\/s, loss=2.35] Epoch [1185\/3000]: Train loss: 1.8830, Valid loss: 2.7809 Epoch [1186\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.76it\/s, loss=2.5] Epoch [1186\/3000]: Train loss: 1.9910, Valid loss: 2.1686 Epoch [1187\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.63it\/s, loss=2.8] Epoch [1187\/3000]: Train loss: 2.1090, Valid loss: 2.2654 Epoch [1188\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.96it\/s, loss=3.27] Epoch [1188\/3000]: Train loss: 2.6013, Valid loss: 4.5275 Epoch [1189\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.49it\/s, loss=2.52] Epoch [1189\/3000]: Train loss: 2.6908, Valid loss: 2.3703 Epoch [1190\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.05it\/s, loss=1.71] Epoch [1190\/3000]: Train loss: 2.0621, Valid loss: 2.3011 Epoch [1191\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.47it\/s, loss=2.1] Epoch [1191\/3000]: Train loss: 2.0642, Valid loss: 2.2432 Epoch [1192\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.79it\/s, loss=2.47] Epoch [1192\/3000]: Train loss: 2.2150, Valid loss: 2.0781 Epoch [1193\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.38it\/s, loss=1.46] Epoch [1193\/3000]: Train loss: 2.0178, Valid loss: 2.3860 Epoch [1194\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.28it\/s, loss=1.94] Epoch [1194\/3000]: Train loss: 2.1196, Valid loss: 2.2684 Epoch [1195\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.80it\/s, loss=1.71] Epoch [1195\/3000]: Train loss: 1.9167, Valid loss: 2.3931 Epoch [1196\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.79it\/s, loss=2.03] Epoch [1196\/3000]: Train loss: 1.9488, Valid loss: 3.1122 Epoch [1197\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.15it\/s, loss=2.04] Epoch [1197\/3000]: Train loss: 2.0890, Valid loss: 2.4521 Epoch [1198\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.08it\/s, loss=2.44] Epoch [1198\/3000]: Train loss: 1.9874, Valid loss: 2.2615 Epoch [1199\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.11it\/s, loss=2.17] Epoch [1199\/3000]: Train loss: 2.3013, Valid loss: 1.9947 Epoch [1200\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.70it\/s, loss=1.95] Epoch [1200\/3000]: Train loss: 2.1663, Valid loss: 2.5180 Epoch [1201\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.05it\/s, loss=2.38] Epoch [1201\/3000]: Train loss: 2.0478, Valid loss: 2.4004 Epoch [1202\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.74it\/s, loss=2.24] Epoch [1202\/3000]: Train loss: 2.6118, Valid loss: 2.0748 Epoch [1203\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.13it\/s, loss=1.79] Epoch [1203\/3000]: Train loss: 2.1449, Valid loss: 3.1070 Epoch [1204\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.60it\/s, loss=2.43] Epoch [1204\/3000]: Train loss: 2.5425, Valid loss: 3.0045 Epoch [1205\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.06it\/s, loss=4.28] Epoch [1205\/3000]: Train loss: 4.0831, Valid loss: 2.1572 Epoch [1206\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.85it\/s, loss=2.81] Epoch [1206\/3000]: Train loss: 2.6286, Valid loss: 3.2204 Epoch [1207\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.00it\/s, loss=2.02] Epoch [1207\/3000]: Train loss: 2.1118, Valid loss: 2.0054 Epoch [1208\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.58it\/s, loss=2.11] Epoch [1208\/3000]: Train loss: 1.8677, Valid loss: 1.8192 Epoch [1209\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.98it\/s, loss=2.07] Epoch [1209\/3000]: Train loss: 1.8917, Valid loss: 2.2323 Epoch [1210\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.75it\/s, loss=1.65] Epoch [1210\/3000]: Train loss: 1.8892, Valid loss: 2.3779 Epoch [1211\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.54it\/s, loss=1.89] Epoch [1211\/3000]: Train loss: 1.9725, Valid loss: 2.2079 Epoch [1212\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.46it\/s, loss=2.88] Epoch [1212\/3000]: Train loss: 1.9325, Valid loss: 2.5892 Epoch [1213\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.53it\/s, loss=2.27] Epoch [1213\/3000]: Train loss: 2.2911, Valid loss: 1.8651 Epoch [1214\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.12it\/s, loss=1.76] Epoch [1214\/3000]: Train loss: 1.8669, Valid loss: 2.4392 Epoch [1215\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.80it\/s, loss=2.62] Epoch [1215\/3000]: Train loss: 2.1193, Valid loss: 2.5663 Epoch [1216\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.17it\/s, loss=1.87] Epoch [1216\/3000]: Train loss: 2.6517, Valid loss: 3.3593 Epoch [1217\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.63it\/s, loss=1.54] Epoch [1217\/3000]: Train loss: 2.4124, Valid loss: 4.0856 Epoch [1218\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.71it\/s, loss=3.77] Epoch [1218\/3000]: Train loss: 2.8194, Valid loss: 2.9130 Epoch [1219\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.55it\/s, loss=1.87] Epoch [1219\/3000]: Train loss: 2.2970, Valid loss: 2.6340 Epoch [1220\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.39it\/s, loss=2.27] Epoch [1220\/3000]: Train loss: 2.0610, Valid loss: 2.6346 Epoch [1221\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.91it\/s, loss=1.77] Epoch [1221\/3000]: Train loss: 2.5462, Valid loss: 1.9835 Epoch [1222\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.65it\/s, loss=1.63] Epoch [1222\/3000]: Train loss: 1.9142, Valid loss: 2.3496 Epoch [1223\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.31it\/s, loss=1.66] Epoch [1223\/3000]: Train loss: 1.8183, Valid loss: 2.0953 Epoch [1224\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.71it\/s, loss=1.5] Epoch [1224\/3000]: Train loss: 1.8634, Valid loss: 2.3626 Epoch [1225\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 100.17it\/s, loss=1.64] Epoch [1225\/3000]: Train loss: 2.1552, Valid loss: 2.3480 Epoch [1226\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.27it\/s, loss=1.43] Epoch [1226\/3000]: Train loss: 1.8915, Valid loss: 2.3615 Epoch [1227\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.00it\/s, loss=1.81] Epoch [1227\/3000]: Train loss: 1.8957, Valid loss: 2.1655 Epoch [1228\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.49it\/s, loss=1.46] Epoch [1228\/3000]: Train loss: 1.8158, Valid loss: 2.4815 Epoch [1229\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.85it\/s, loss=1.72] Epoch [1229\/3000]: Train loss: 1.8434, Valid loss: 2.1581 Epoch [1230\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.59it\/s, loss=1.9] Epoch [1230\/3000]: Train loss: 2.0947, Valid loss: 2.6708 Epoch [1231\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.01it\/s, loss=1.8] Epoch [1231\/3000]: Train loss: 2.2346, Valid loss: 2.9262 Epoch [1232\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.34it\/s, loss=2.61] Epoch [1232\/3000]: Train loss: 2.5618, Valid loss: 2.5527 Epoch [1233\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.15it\/s, loss=2.47] Epoch [1233\/3000]: Train loss: 3.0747, Valid loss: 2.2874 Epoch [1234\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.24it\/s, loss=2.19] Epoch [1234\/3000]: Train loss: 2.7520, Valid loss: 4.2693 Epoch [1235\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.70it\/s, loss=1.57] Epoch [1235\/3000]: Train loss: 2.7746, Valid loss: 4.3747 Epoch [1236\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.35it\/s, loss=3.51] Epoch [1236\/3000]: Train loss: 4.1965, Valid loss: 4.7989 Epoch [1237\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.69it\/s, loss=4.81] Epoch [1237\/3000]: Train loss: 3.7426, Valid loss: 2.4824 Epoch [1238\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.51it\/s, loss=1.68] Epoch [1238\/3000]: Train loss: 2.7717, Valid loss: 3.5696 Epoch [1239\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.90it\/s, loss=2.43] Epoch [1239\/3000]: Train loss: 2.8987, Valid loss: 2.5390 Epoch [1240\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 103.92it\/s, loss=2.22] Epoch [1240\/3000]: Train loss: 2.5268, Valid loss: 2.3522 Epoch [1241\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.38it\/s, loss=1.83] Epoch [1241\/3000]: Train loss: 1.9631, Valid loss: 2.7445 Epoch [1242\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.01it\/s, loss=2.13] Epoch [1242\/3000]: Train loss: 1.9232, Valid loss: 2.0807 Epoch [1243\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 15.44it\/s, loss=3.4] Epoch [1243\/3000]: Train loss: 2.4431, Valid loss: 2.3220 Epoch [1244\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.32it\/s, loss=2.33] Epoch [1244\/3000]: Train loss: 2.5115, Valid loss: 3.6426 Epoch [1245\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.12it\/s, loss=2.34] Epoch [1245\/3000]: Train loss: 2.5096, Valid loss: 4.6335 Epoch [1246\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.92it\/s, loss=2.25] Epoch [1246\/3000]: Train loss: 2.8978, Valid loss: 2.5039 Epoch [1247\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.37it\/s, loss=2.27] Epoch [1247\/3000]: Train loss: 2.0396, Valid loss: 2.0009 Epoch [1248\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.89it\/s, loss=1.99] Epoch [1248\/3000]: Train loss: 1.9199, Valid loss: 2.1965 Epoch [1249\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.86it\/s, loss=2.42] Epoch [1249\/3000]: Train loss: 1.8837, Valid loss: 2.7129 Epoch [1250\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 106.51it\/s, loss=2.21] Epoch [1250\/3000]: Train loss: 2.1166, Valid loss: 1.9533 Epoch [1251\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.51it\/s, loss=1.61] Epoch [1251\/3000]: Train loss: 2.7918, Valid loss: 3.4249 Epoch [1252\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.27it\/s, loss=3.72] Epoch [1252\/3000]: Train loss: 2.9671, Valid loss: 2.1194 Epoch [1253\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.92it\/s, loss=3.49] Epoch [1253\/3000]: Train loss: 2.4729, Valid loss: 2.4031 Epoch [1254\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 102.45it\/s, loss=1.91] Epoch [1254\/3000]: Train loss: 2.0174, Valid loss: 2.7978 Epoch [1255\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.87it\/s, loss=1.97] Epoch [1255\/3000]: Train loss: 2.0828, Valid loss: 2.2647 Epoch [1256\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.65it\/s, loss=2.13] Epoch [1256\/3000]: Train loss: 2.2220, Valid loss: 2.1746 Epoch [1257\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.61it\/s, loss=1.97] Epoch [1257\/3000]: Train loss: 2.0378, Valid loss: 3.8440 Epoch [1258\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.60it\/s, loss=3.2] Epoch [1258\/3000]: Train loss: 2.2132, Valid loss: 3.6054 Epoch [1259\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.47it\/s, loss=2.16] Epoch [1259\/3000]: Train loss: 2.5446, Valid loss: 2.1956 Epoch [1260\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.77it\/s, loss=1.29] Epoch [1260\/3000]: Train loss: 1.8529, Valid loss: 1.7361 Saving model with loss 1.736… Epoch [1261\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.89it\/s, loss=1.65] Epoch [1261\/3000]: Train loss: 1.9233, Valid loss: 2.1894 Epoch [1262\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.68it\/s, loss=1.58] Epoch [1262\/3000]: Train loss: 1.9187, Valid loss: 4.3078 Epoch [1263\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.60it\/s, loss=3.79] Epoch [1263\/3000]: Train loss: 3.3315, Valid loss: 2.9537 Epoch [1264\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.99it\/s, loss=2.26] Epoch [1264\/3000]: Train loss: 4.2524, Valid loss: 3.7477 Epoch [1265\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.70it\/s, loss=2.11] Epoch [1265\/3000]: Train loss: 2.2797, Valid loss: 1.8620 Epoch [1266\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.15it\/s, loss=2.45] Epoch [1266\/3000]: Train loss: 2.1937, Valid loss: 2.6261 Epoch [1267\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.46it\/s, loss=2.04] Epoch [1267\/3000]: Train loss: 2.2113, Valid loss: 2.4735 Epoch [1268\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.09it\/s, loss=2.11] Epoch [1268\/3000]: Train loss: 2.2429, Valid loss: 2.1333 Epoch [1269\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.25it\/s, loss=1.85] Epoch [1269\/3000]: Train loss: 1.9080, Valid loss: 2.0181 Epoch [1270\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.74it\/s, loss=2.16] Epoch [1270\/3000]: Train loss: 1.8767, Valid loss: 4.4842 Epoch [1271\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.71it\/s, loss=4.28] Epoch [1271\/3000]: Train loss: 3.3671, Valid loss: 2.6835 Epoch [1272\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.71it\/s, loss=1.98] Epoch [1272\/3000]: Train loss: 2.5711, Valid loss: 3.0083 Epoch [1273\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.96it\/s, loss=2.24] Epoch [1273\/3000]: Train loss: 2.4354, Valid loss: 3.9281 Epoch [1274\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.63it\/s, loss=2.26] Epoch [1274\/3000]: Train loss: 2.2361, Valid loss: 2.0439 Epoch [1275\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.05it\/s, loss=2.74] Epoch [1275\/3000]: Train loss: 2.2270, Valid loss: 2.4846 Epoch [1276\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.40it\/s, loss=1.61] Epoch [1276\/3000]: Train loss: 1.9397, Valid loss: 3.7353 Epoch [1277\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 30.97it\/s, loss=2.49] Epoch [1277\/3000]: Train loss: 2.6674, Valid loss: 2.1884 Epoch [1278\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 57.97it\/s, loss=4.12] Epoch [1278\/3000]: Train loss: 2.5379, Valid loss: 2.0322 Epoch [1279\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.53it\/s, loss=1.84] Epoch [1279\/3000]: Train loss: 2.5156, Valid loss: 2.9358 Epoch [1280\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.22it\/s, loss=1.93] Epoch [1280\/3000]: Train loss: 2.1206, Valid loss: 2.2970 Epoch [1281\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.89it\/s, loss=2.2] Epoch [1281\/3000]: Train loss: 2.0384, Valid loss: 2.3808 Epoch [1282\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.33it\/s, loss=2.18] Epoch [1282\/3000]: Train loss: 1.9600, Valid loss: 2.0981 Epoch [1283\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.65it\/s, loss=1.74] Epoch [1283\/3000]: Train loss: 1.8960, Valid loss: 1.8405 Epoch [1284\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.06it\/s, loss=1.95] Epoch [1284\/3000]: Train loss: 1.8350, Valid loss: 1.9604 Epoch [1285\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.43it\/s, loss=2.31] Epoch [1285\/3000]: Train loss: 1.9490, Valid loss: 2.3340 Epoch [1286\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.81it\/s, loss=1.82] Epoch [1286\/3000]: Train loss: 2.0533, Valid loss: 2.0748 Epoch [1287\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.72it\/s, loss=1.6] Epoch [1287\/3000]: Train loss: 1.8200, Valid loss: 2.0201 Epoch [1288\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.82it\/s, loss=2.37] Epoch [1288\/3000]: Train loss: 1.9748, Valid loss: 1.8455 Epoch [1289\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.95it\/s, loss=1.72] Epoch [1289\/3000]: Train loss: 1.9532, Valid loss: 2.0633 Epoch [1290\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.32it\/s, loss=1.55] Epoch [1290\/3000]: Train loss: 1.8187, Valid loss: 2.4763 Epoch [1291\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.18it\/s, loss=2.43] Epoch [1291\/3000]: Train loss: 2.1052, Valid loss: 4.3102 Epoch [1292\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.94it\/s, loss=2.12] Epoch [1292\/3000]: Train loss: 2.4753, Valid loss: 3.0591 Epoch [1293\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.35it\/s, loss=1.6] Epoch [1293\/3000]: Train loss: 1.9828, Valid loss: 1.9201 Epoch [1294\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.32it\/s, loss=2.19] Epoch [1294\/3000]: Train loss: 1.9205, Valid loss: 2.8604 Epoch [1295\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.27it\/s, loss=2.47] Epoch [1295\/3000]: Train loss: 2.1526, Valid loss: 1.8648 Epoch [1296\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.22it\/s, loss=2.48] Epoch [1296\/3000]: Train loss: 2.3318, Valid loss: 3.9005 Epoch [1297\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.77it\/s, loss=1.96] Epoch [1297\/3000]: Train loss: 2.3606, Valid loss: 2.3403 Epoch [1298\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.97it\/s, loss=2.06] Epoch [1298\/3000]: Train loss: 1.9398, Valid loss: 2.6302 Epoch [1299\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.42it\/s, loss=1.77] Epoch [1299\/3000]: Train loss: 1.9913, Valid loss: 2.7400 Epoch [1300\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.81it\/s, loss=3.37] Epoch [1300\/3000]: Train loss: 2.4577, Valid loss: 2.7758 Epoch [1301\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.25it\/s, loss=1.5] Epoch [1301\/3000]: Train loss: 2.3943, Valid loss: 2.7928 Epoch [1302\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.62it\/s, loss=2.83] Epoch [1302\/3000]: Train loss: 2.2338, Valid loss: 2.1923 Epoch [1303\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.84it\/s, loss=1.41] Epoch [1303\/3000]: Train loss: 2.0190, Valid loss: 1.9032 Epoch [1304\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.47it\/s, loss=1.89] Epoch [1304\/3000]: Train loss: 1.8350, Valid loss: 3.2640 Epoch [1305\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.57it\/s, loss=2.31] Epoch [1305\/3000]: Train loss: 2.4697, Valid loss: 2.4843 Epoch [1306\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.21it\/s, loss=2.3] Epoch [1306\/3000]: Train loss: 1.8795, Valid loss: 2.5678 Epoch [1307\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.59it\/s, loss=1.56] Epoch [1307\/3000]: Train loss: 1.8452, Valid loss: 1.9527 Epoch [1308\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.30it\/s, loss=1.96] Epoch [1308\/3000]: Train loss: 1.8956, Valid loss: 2.5412 Epoch [1309\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.75it\/s, loss=1.73] Epoch [1309\/3000]: Train loss: 2.0412, Valid loss: 3.4324 Epoch [1310\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.30it\/s, loss=2.15] Epoch [1310\/3000]: Train loss: 2.1652, Valid loss: 2.1577 Epoch [1311\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.01it\/s, loss=1.6] Epoch [1311\/3000]: Train loss: 2.0133, Valid loss: 2.4978 Epoch [1312\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.12it\/s, loss=1.54] Epoch [1312\/3000]: Train loss: 1.8090, Valid loss: 2.1814 Epoch [1313\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.30it\/s, loss=1.19] Epoch [1313\/3000]: Train loss: 1.7954, Valid loss: 2.4969 Epoch [1314\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.87it\/s, loss=2.31] Epoch [1314\/3000]: Train loss: 2.2149, Valid loss: 2.3382 Epoch [1315\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.76it\/s, loss=3.27] Epoch [1315\/3000]: Train loss: 2.3538, Valid loss: 2.0675 Epoch [1316\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.22it\/s, loss=2.77] Epoch [1316\/3000]: Train loss: 2.9643, Valid loss: 3.4080 Epoch [1317\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.41it\/s, loss=1.86] Epoch [1317\/3000]: Train loss: 2.0484, Valid loss: 2.4092 Epoch [1318\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.85it\/s, loss=3.01] Epoch [1318\/3000]: Train loss: 1.9960, Valid loss: 3.9009 Epoch [1319\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.44it\/s, loss=2.13] Epoch [1319\/3000]: Train loss: 2.5960, Valid loss: 2.0658 Epoch [1320\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.60it\/s, loss=1.85] Epoch [1320\/3000]: Train loss: 1.9332, Valid loss: 2.0484 Epoch [1321\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.49it\/s, loss=4.27] Epoch [1321\/3000]: Train loss: 3.0175, Valid loss: 2.6706 Epoch [1322\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.93it\/s, loss=2.13] Epoch [1322\/3000]: Train loss: 2.5909, Valid loss: 3.3656 Epoch [1323\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.71it\/s, loss=1.97] Epoch [1323\/3000]: Train loss: 2.0559, Valid loss: 2.0674 Epoch [1324\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.95it\/s, loss=1.99] Epoch [1324\/3000]: Train loss: 2.4083, Valid loss: 2.8231 Epoch [1325\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.04it\/s, loss=1.92] Epoch [1325\/3000]: Train loss: 3.1865, Valid loss: 3.9600 Epoch [1326\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.28it\/s, loss=2.1] Epoch [1326\/3000]: Train loss: 2.0640, Valid loss: 2.4133 Epoch [1327\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.92it\/s, loss=1.78] Epoch [1327\/3000]: Train loss: 1.9360, Valid loss: 2.5759 Epoch [1328\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.78it\/s, loss=2.45] Epoch [1328\/3000]: Train loss: 2.1539, Valid loss: 2.2612 Epoch [1329\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.89it\/s, loss=1.64] Epoch [1329\/3000]: Train loss: 2.0123, Valid loss: 3.2160 Epoch [1330\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.44it\/s, loss=1.83] Epoch [1330\/3000]: Train loss: 2.2375, Valid loss: 2.3288 Epoch [1331\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.62it\/s, loss=2.24] Epoch [1331\/3000]: Train loss: 1.9990, Valid loss: 1.7556 Epoch [1332\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.06it\/s, loss=2.13] Epoch [1332\/3000]: Train loss: 1.8258, Valid loss: 2.9701 Epoch [1333\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.50it\/s, loss=1.53] Epoch [1333\/3000]: Train loss: 2.0306, Valid loss: 2.3402 Epoch [1334\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.87it\/s, loss=1.58] Epoch [1334\/3000]: Train loss: 1.9361, Valid loss: 1.9383 Epoch [1335\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.14it\/s, loss=2.04] Epoch [1335\/3000]: Train loss: 1.9615, Valid loss: 2.4499 Epoch [1336\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 43.25it\/s, loss=2.46] Epoch [1336\/3000]: Train loss: 1.9759, Valid loss: 2.0309 Epoch [1337\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 58.70it\/s, loss=1.98] Epoch [1337\/3000]: Train loss: 1.9230, Valid loss: 2.3282 Epoch [1338\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.70it\/s, loss=1.74] Epoch [1338\/3000]: Train loss: 1.8709, Valid loss: 2.5205 Epoch [1339\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.52it\/s, loss=2.69] Epoch [1339\/3000]: Train loss: 1.8889, Valid loss: 1.8427 Epoch [1340\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.60it\/s, loss=2.55] Epoch [1340\/3000]: Train loss: 1.9958, Valid loss: 1.8852 Epoch [1341\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.53it\/s, loss=1.76] Epoch [1341\/3000]: Train loss: 2.0647, Valid loss: 2.3528 Epoch [1342\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.46it\/s, loss=3.29] Epoch [1342\/3000]: Train loss: 1.9637, Valid loss: 2.3976 Epoch [1343\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.66it\/s, loss=2.55] Epoch [1343\/3000]: Train loss: 1.9649, Valid loss: 2.2327 Epoch [1344\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.93it\/s, loss=2.02] Epoch [1344\/3000]: Train loss: 2.5024, Valid loss: 4.6076 Epoch [1345\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.66it\/s, loss=2.04] Epoch [1345\/3000]: Train loss: 2.9222, Valid loss: 4.3388 Epoch [1346\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.96it\/s, loss=1.87] Epoch [1346\/3000]: Train loss: 3.1732, Valid loss: 4.7783 Epoch [1347\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.67it\/s, loss=2.01] Epoch [1347\/3000]: Train loss: 2.8847, Valid loss: 2.0668 Epoch [1348\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.63it\/s, loss=2.05] Epoch [1348\/3000]: Train loss: 2.3475, Valid loss: 1.8374 Epoch [1349\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.07it\/s, loss=1.23] Epoch [1349\/3000]: Train loss: 2.0649, Valid loss: 2.7382 Epoch [1350\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.99it\/s, loss=3.54] Epoch [1350\/3000]: Train loss: 2.4712, Valid loss: 2.5885 Epoch [1351\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.11it\/s, loss=4.63] Epoch [1351\/3000]: Train loss: 3.7117, Valid loss: 3.5049 Epoch [1352\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.75it\/s, loss=2.6] Epoch [1352\/3000]: Train loss: 3.0502, Valid loss: 2.4092 Epoch [1353\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.11it\/s, loss=1.49] Epoch [1353\/3000]: Train loss: 1.9739, Valid loss: 1.9525 Epoch [1354\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.75it\/s, loss=1.99] Epoch [1354\/3000]: Train loss: 1.8493, Valid loss: 2.4063 Epoch [1355\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.34it\/s, loss=2.01] Epoch [1355\/3000]: Train loss: 1.9684, Valid loss: 2.8272 Epoch [1356\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.06it\/s, loss=1.97] Epoch [1356\/3000]: Train loss: 2.0117, Valid loss: 1.9167 Epoch [1357\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.83it\/s, loss=2.3] Epoch [1357\/3000]: Train loss: 1.8365, Valid loss: 2.1864 Epoch [1358\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.51it\/s, loss=2.13] Epoch [1358\/3000]: Train loss: 1.8579, Valid loss: 2.1921 Epoch [1359\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.78it\/s, loss=1.82] Epoch [1359\/3000]: Train loss: 1.9613, Valid loss: 2.0551 Epoch [1360\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.02it\/s, loss=1.9] Epoch [1360\/3000]: Train loss: 1.8975, Valid loss: 2.3779 Epoch [1361\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.80it\/s, loss=1.3] Epoch [1361\/3000]: Train loss: 1.9046, Valid loss: 2.6207 Epoch [1362\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.37it\/s, loss=2.24] Epoch [1362\/3000]: Train loss: 1.9432, Valid loss: 3.1318 Epoch [1363\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 100.53it\/s, loss=1.44] Epoch [1363\/3000]: Train loss: 2.0848, Valid loss: 2.4331 Epoch [1364\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.67it\/s, loss=3.6] Epoch [1364\/3000]: Train loss: 2.4125, Valid loss: 1.8900 Epoch [1365\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.30it\/s, loss=2.95] Epoch [1365\/3000]: Train loss: 2.1386, Valid loss: 1.7537 Epoch [1366\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.43it\/s, loss=1.53] Epoch [1366\/3000]: Train loss: 2.0526, Valid loss: 2.0748 Epoch [1367\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.38it\/s, loss=1.17] Epoch [1367\/3000]: Train loss: 1.9918, Valid loss: 2.6224 Epoch [1368\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.68it\/s, loss=1.57] Epoch [1368\/3000]: Train loss: 1.9957, Valid loss: 2.0422 Epoch [1369\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.03it\/s, loss=2.58] Epoch [1369\/3000]: Train loss: 1.8590, Valid loss: 2.0538 Epoch [1370\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.32it\/s, loss=1.49] Epoch [1370\/3000]: Train loss: 1.9116, Valid loss: 1.9742 Epoch [1371\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.78it\/s, loss=1.6] Epoch [1371\/3000]: Train loss: 1.8143, Valid loss: 1.8026 Epoch [1372\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.27it\/s, loss=2.96] Epoch [1372\/3000]: Train loss: 2.0325, Valid loss: 2.8860 Epoch [1373\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.58it\/s, loss=2.28] Epoch [1373\/3000]: Train loss: 2.0081, Valid loss: 1.8413 Epoch [1374\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.06it\/s, loss=2.52] Epoch [1374\/3000]: Train loss: 2.0761, Valid loss: 2.1709 Epoch [1375\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.36it\/s, loss=1.89] Epoch [1375\/3000]: Train loss: 2.1194, Valid loss: 2.2030 Epoch [1376\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.00it\/s, loss=1.55] Epoch [1376\/3000]: Train loss: 1.9200, Valid loss: 2.2540 Epoch [1377\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 105.17it\/s, loss=2.47] Epoch [1377\/3000]: Train loss: 1.9245, Valid loss: 3.1455 Epoch [1378\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 102.44it\/s, loss=2.53] Epoch [1378\/3000]: Train loss: 2.1338, Valid loss: 3.3530 Epoch [1379\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.21it\/s, loss=3.86] Epoch [1379\/3000]: Train loss: 2.7466, Valid loss: 2.0764 Epoch [1380\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.62it\/s, loss=3.01] Epoch [1380\/3000]: Train loss: 2.5435, Valid loss: 2.5357 Epoch [1381\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.65it\/s, loss=2.43] Epoch [1381\/3000]: Train loss: 2.7467, Valid loss: 3.9694 Epoch [1382\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.83it\/s, loss=2.47] Epoch [1382\/3000]: Train loss: 2.4078, Valid loss: 2.0624 Epoch [1383\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.62it\/s, loss=2.13] Epoch [1383\/3000]: Train loss: 1.9304, Valid loss: 1.9126 Epoch [1384\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.31it\/s, loss=1.6] Epoch [1384\/3000]: Train loss: 1.8169, Valid loss: 2.1678 Epoch [1385\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.82it\/s, loss=2.81] Epoch [1385\/3000]: Train loss: 2.2823, Valid loss: 2.4816 Epoch [1386\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.76it\/s, loss=1.67] Epoch [1386\/3000]: Train loss: 1.9915, Valid loss: 3.1241 Epoch [1387\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.23it\/s, loss=2.04] Epoch [1387\/3000]: Train loss: 2.2361, Valid loss: 2.0638 Epoch [1388\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.41it\/s, loss=2.25] Epoch [1388\/3000]: Train loss: 2.2257, Valid loss: 2.3404 Epoch [1389\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.22it\/s, loss=1.63] Epoch [1389\/3000]: Train loss: 1.9697, Valid loss: 2.3790 Epoch [1390\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.96it\/s, loss=2.15] Epoch [1390\/3000]: Train loss: 1.8430, Valid loss: 2.1692 Epoch [1391\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.33it\/s, loss=1.76] Epoch [1391\/3000]: Train loss: 1.8571, Valid loss: 1.9054 Epoch [1392\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.51it\/s, loss=1.92] Epoch [1392\/3000]: Train loss: 1.9352, Valid loss: 1.9517 Epoch [1393\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 66.99it\/s, loss=2.23] Epoch [1393\/3000]: Train loss: 1.9073, Valid loss: 1.9872 Epoch [1394\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.49it\/s, loss=2.01] Epoch [1394\/3000]: Train loss: 1.9488, Valid loss: 2.8826 Epoch [1395\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.53it\/s, loss=2.6] Epoch [1395\/3000]: Train loss: 2.5074, Valid loss: 3.4144 Epoch [1396\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.85it\/s, loss=2.66] Epoch [1396\/3000]: Train loss: 2.5288, Valid loss: 2.1356 Epoch [1397\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.31it\/s, loss=1.68] Epoch [1397\/3000]: Train loss: 1.9277, Valid loss: 2.2399 Epoch [1398\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 63.64it\/s, loss=1.96] Epoch [1398\/3000]: Train loss: 1.8782, Valid loss: 1.7967 Epoch [1399\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 66.98it\/s, loss=1.87] Epoch [1399\/3000]: Train loss: 1.8219, Valid loss: 2.2559 Epoch [1400\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.82it\/s, loss=2.24] Epoch [1400\/3000]: Train loss: 2.0301, Valid loss: 2.5172 Epoch [1401\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.37it\/s, loss=1.54] Epoch [1401\/3000]: Train loss: 2.0873, Valid loss: 3.5005 Epoch [1402\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.85it\/s, loss=1.99] Epoch [1402\/3000]: Train loss: 2.3570, Valid loss: 1.9657 Epoch [1403\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.66it\/s, loss=1.5] Epoch [1403\/3000]: Train loss: 1.8755, Valid loss: 2.4813 Epoch [1404\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.60it\/s, loss=2.17] Epoch [1404\/3000]: Train loss: 1.8805, Valid loss: 2.1241 Epoch [1405\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.18it\/s, loss=2.47] Epoch [1405\/3000]: Train loss: 2.0336, Valid loss: 2.3122 Epoch [1406\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.84it\/s, loss=1.71] Epoch [1406\/3000]: Train loss: 2.3469, Valid loss: 2.3885 Epoch [1407\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.46it\/s, loss=3] Epoch [1407\/3000]: Train loss: 1.9952, Valid loss: 2.3694 Epoch [1408\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.92it\/s, loss=2.2] Epoch [1408\/3000]: Train loss: 2.2650, Valid loss: 2.9175 Epoch [1409\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.36it\/s, loss=1.98] Epoch [1409\/3000]: Train loss: 2.1922, Valid loss: 2.8481 Epoch [1410\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.56it\/s, loss=1.75] Epoch [1410\/3000]: Train loss: 2.1948, Valid loss: 2.3381 Epoch [1411\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 65.21it\/s, loss=1.57] Epoch [1411\/3000]: Train loss: 1.7989, Valid loss: 2.4945 Epoch [1412\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.47it\/s, loss=1.44] Epoch [1412\/3000]: Train loss: 1.7935, Valid loss: 2.7660 Epoch [1413\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 100.00it\/s, loss=2.42] Epoch [1413\/3000]: Train loss: 1.9441, Valid loss: 2.6116 Epoch [1414\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.36it\/s, loss=1.36] Epoch [1414\/3000]: Train loss: 2.0370, Valid loss: 2.7706 Epoch [1415\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.64it\/s, loss=2.3] Epoch [1415\/3000]: Train loss: 2.1388, Valid loss: 1.9675 Epoch [1416\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.44it\/s, loss=1.76] Epoch [1416\/3000]: Train loss: 1.9934, Valid loss: 2.3639 Epoch [1417\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 102.35it\/s, loss=3.08] Epoch [1417\/3000]: Train loss: 2.2250, Valid loss: 2.1699 Epoch [1418\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.60it\/s, loss=2.19] Epoch [1418\/3000]: Train loss: 1.9421, Valid loss: 2.1491 Epoch [1419\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.06it\/s, loss=1.82] Epoch [1419\/3000]: Train loss: 1.7841, Valid loss: 2.5767 Epoch [1420\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.38it\/s, loss=2.58] Epoch [1420\/3000]: Train loss: 2.3368, Valid loss: 2.4132 Epoch [1421\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.97it\/s, loss=1.42] Epoch [1421\/3000]: Train loss: 1.9701, Valid loss: 1.9865 Epoch [1422\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.20it\/s, loss=2.02] Epoch [1422\/3000]: Train loss: 1.8392, Valid loss: 2.6109 Epoch [1423\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.98it\/s, loss=2.38] Epoch [1423\/3000]: Train loss: 1.9981, Valid loss: 1.9028 Epoch [1424\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.55it\/s, loss=4.3] Epoch [1424\/3000]: Train loss: 3.5414, Valid loss: 3.4045 Epoch [1425\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.60it\/s, loss=4.65] Epoch [1425\/3000]: Train loss: 3.2760, Valid loss: 3.8655 Epoch [1426\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.53it\/s, loss=2.26] Epoch [1426\/3000]: Train loss: 3.0602, Valid loss: 3.0161 Epoch [1427\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.74it\/s, loss=2.2] Epoch [1427\/3000]: Train loss: 2.2039, Valid loss: 2.3356 Epoch [1428\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.01it\/s, loss=1.53] Epoch [1428\/3000]: Train loss: 1.7700, Valid loss: 2.1574 Epoch [1429\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.47it\/s, loss=1.53] Epoch [1429\/3000]: Train loss: 1.8278, Valid loss: 1.9571 Epoch [1430\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.35it\/s, loss=1.56] Epoch [1430\/3000]: Train loss: 1.7658, Valid loss: 2.0184 Epoch [1431\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.62it\/s, loss=1.9] Epoch [1431\/3000]: Train loss: 2.1083, Valid loss: 2.1750 Epoch [1432\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.66it\/s, loss=1.49] Epoch [1432\/3000]: Train loss: 1.7407, Valid loss: 1.9309 Epoch [1433\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.86it\/s, loss=1.96] Epoch [1433\/3000]: Train loss: 1.9223, Valid loss: 2.2641 Epoch [1434\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.89it\/s, loss=1.98] Epoch [1434\/3000]: Train loss: 1.8429, Valid loss: 2.2858 Epoch [1435\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.14it\/s, loss=2.05] Epoch [1435\/3000]: Train loss: 2.1263, Valid loss: 2.2260 Epoch [1436\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.56it\/s, loss=1.71] Epoch [1436\/3000]: Train loss: 2.0885, Valid loss: 2.6822 Epoch [1437\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.63it\/s, loss=2.35] Epoch [1437\/3000]: Train loss: 2.2243, Valid loss: 2.9075 Epoch [1438\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.91it\/s, loss=2.99] Epoch [1438\/3000]: Train loss: 2.3991, Valid loss: 1.7881 Epoch [1439\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.01it\/s, loss=1.36] Epoch [1439\/3000]: Train loss: 2.1944, Valid loss: 2.0550 Epoch [1440\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.57it\/s, loss=2.3] Epoch [1440\/3000]: Train loss: 1.9546, Valid loss: 3.4065 Epoch [1441\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.77it\/s, loss=1.76] Epoch [1441\/3000]: Train loss: 2.5791, Valid loss: 3.6680 Epoch [1442\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.40it\/s, loss=1.79] Epoch [1442\/3000]: Train loss: 2.3723, Valid loss: 2.3597 Epoch [1443\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.77it\/s, loss=1.58] Epoch [1443\/3000]: Train loss: 1.8255, Valid loss: 1.9226 Epoch [1444\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.03it\/s, loss=1.99] Epoch [1444\/3000]: Train loss: 1.8176, Valid loss: 2.1415 Epoch [1445\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.40it\/s, loss=1.9] Epoch [1445\/3000]: Train loss: 1.7992, Valid loss: 2.0932 Epoch [1446\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.17it\/s, loss=1.62] Epoch [1446\/3000]: Train loss: 2.0280, Valid loss: 1.9356 Epoch [1447\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.56it\/s, loss=1.96] Epoch [1447\/3000]: Train loss: 1.8760, Valid loss: 2.4798 Epoch [1448\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.52it\/s, loss=1.89] Epoch [1448\/3000]: Train loss: 1.8466, Valid loss: 2.5900 Epoch [1449\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.40it\/s, loss=2.05] Epoch [1449\/3000]: Train loss: 1.8877, Valid loss: 2.1658 Epoch [1450\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.75it\/s, loss=1.72] Epoch [1450\/3000]: Train loss: 1.8062, Valid loss: 1.9109 Epoch [1451\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.25it\/s, loss=1.95] Epoch [1451\/3000]: Train loss: 1.7735, Valid loss: 1.8449 Epoch [1452\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.61it\/s, loss=2.25] Epoch [1452\/3000]: Train loss: 1.9286, Valid loss: 1.9439 Epoch [1453\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.69it\/s, loss=2.26] Epoch [1453\/3000]: Train loss: 2.0392, Valid loss: 2.2274 Epoch [1454\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.12it\/s, loss=2.03] Epoch [1454\/3000]: Train loss: 1.9431, Valid loss: 2.3631 Epoch [1455\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.47it\/s, loss=1.85] Epoch [1455\/3000]: Train loss: 1.7938, Valid loss: 1.9822 Epoch [1456\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.72it\/s, loss=1.73] Epoch [1456\/3000]: Train loss: 1.9189, Valid loss: 2.8811 Epoch [1457\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.42it\/s, loss=1.62] Epoch [1457\/3000]: Train loss: 1.9486, Valid loss: 2.5653 Epoch [1458\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.26it\/s, loss=3.1] Epoch [1458\/3000]: Train loss: 2.3422, Valid loss: 2.1087 Epoch [1459\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.43it\/s, loss=2.02] Epoch [1459\/3000]: Train loss: 2.3505, Valid loss: 1.9368 Epoch [1460\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.37it\/s, loss=1.61] Epoch [1460\/3000]: Train loss: 1.7728, Valid loss: 2.3879 Epoch [1461\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.13it\/s, loss=1.56] Epoch [1461\/3000]: Train loss: 1.8481, Valid loss: 2.0444 Epoch [1462\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.54it\/s, loss=1.39] Epoch [1462\/3000]: Train loss: 1.7806, Valid loss: 1.9871 Epoch [1463\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.08it\/s, loss=2.4] Epoch [1463\/3000]: Train loss: 1.8637, Valid loss: 2.0459 Epoch [1464\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.44it\/s, loss=1.74] Epoch [1464\/3000]: Train loss: 1.7931, Valid loss: 2.4321 Epoch [1465\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.28it\/s, loss=2.36] Epoch [1465\/3000]: Train loss: 2.4162, Valid loss: 1.8315 Epoch [1466\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.07it\/s, loss=1.74] Epoch [1466\/3000]: Train loss: 2.7091, Valid loss: 3.7150 Epoch [1467\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.34it\/s, loss=1.72] Epoch [1467\/3000]: Train loss: 2.2673, Valid loss: 2.6608 Epoch [1468\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 101.72it\/s, loss=2.71] Epoch [1468\/3000]: Train loss: 2.2264, Valid loss: 2.4199 Epoch [1469\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.28it\/s, loss=2.11] Epoch [1469\/3000]: Train loss: 1.8959, Valid loss: 2.8270 Epoch [1470\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.37it\/s, loss=2.23] Epoch [1470\/3000]: Train loss: 2.4399, Valid loss: 2.0435 Epoch [1471\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.71it\/s, loss=3.16] Epoch [1471\/3000]: Train loss: 3.0824, Valid loss: 2.0551 Epoch [1472\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.01it\/s, loss=1.95] Epoch [1472\/3000]: Train loss: 2.5393, Valid loss: 2.2539 Epoch [1473\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.86it\/s, loss=2.26] Epoch [1473\/3000]: Train loss: 1.9915, Valid loss: 2.7159 Epoch [1474\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.16it\/s, loss=1.73] Epoch [1474\/3000]: Train loss: 2.1265, Valid loss: 2.9241 Epoch [1475\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.77it\/s, loss=1.58] Epoch [1475\/3000]: Train loss: 2.2119, Valid loss: 1.7639 Epoch [1476\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.65it\/s, loss=1.38] Epoch [1476\/3000]: Train loss: 2.1557, Valid loss: 2.3285 Epoch [1477\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 64.64it\/s, loss=2.36] Epoch [1477\/3000]: Train loss: 1.9940, Valid loss: 1.9104 Epoch [1478\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.18it\/s, loss=1.86] Epoch [1478\/3000]: Train loss: 1.8922, Valid loss: 2.0420 Epoch [1479\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.65it\/s, loss=1.23] Epoch [1479\/3000]: Train loss: 1.8113, Valid loss: 2.0332 Epoch [1480\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.80it\/s, loss=1.47] Epoch [1480\/3000]: Train loss: 1.7747, Valid loss: 2.2317 Epoch [1481\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 67.08it\/s, loss=1.72] Epoch [1481\/3000]: Train loss: 1.8212, Valid loss: 1.7459 Epoch [1482\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.85it\/s, loss=1.55] Epoch [1482\/3000]: Train loss: 1.7495, Valid loss: 2.4172 Epoch [1483\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.48it\/s, loss=1.71] Epoch [1483\/3000]: Train loss: 1.7581, Valid loss: 1.6359 Saving model with loss 1.636… Epoch [1484\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.03it\/s, loss=1.4] Epoch [1484\/3000]: Train loss: 1.7602, Valid loss: 1.9959 Epoch [1485\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.35it\/s, loss=2.37] Epoch [1485\/3000]: Train loss: 1.8432, Valid loss: 3.6234 Epoch [1486\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.77it\/s, loss=2.36] Epoch [1486\/3000]: Train loss: 2.3825, Valid loss: 2.4637 Epoch [1487\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.45it\/s, loss=2.15] Epoch [1487\/3000]: Train loss: 2.3615, Valid loss: 2.4791 Epoch [1488\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.20it\/s, loss=1.99] Epoch [1488\/3000]: Train loss: 1.9124, Valid loss: 2.6676 Epoch [1489\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.94it\/s, loss=2.06] Epoch [1489\/3000]: Train loss: 1.8840, Valid loss: 2.2652 Epoch [1490\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.90it\/s, loss=1.82] Epoch [1490\/3000]: Train loss: 1.7815, Valid loss: 2.2021 Epoch [1491\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.71it\/s, loss=1.86] Epoch [1491\/3000]: Train loss: 1.8859, Valid loss: 1.8757 Epoch [1492\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.91it\/s, loss=1.43] Epoch [1492\/3000]: Train loss: 1.8026, Valid loss: 2.1383 Epoch [1493\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.25it\/s, loss=2.7] Epoch [1493\/3000]: Train loss: 1.8462, Valid loss: 2.5144 Epoch [1494\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.94it\/s, loss=2.46] Epoch [1494\/3000]: Train loss: 2.0468, Valid loss: 2.3107 Epoch [1495\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.96it\/s, loss=2.18] Epoch [1495\/3000]: Train loss: 2.0367, Valid loss: 2.8095 Epoch [1496\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.02it\/s, loss=2.12] Epoch [1496\/3000]: Train loss: 2.3440, Valid loss: 1.9301 Epoch [1497\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.31it\/s, loss=1.5] Epoch [1497\/3000]: Train loss: 1.9460, Valid loss: 1.9873 Epoch [1498\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.04it\/s, loss=2.61] Epoch [1498\/3000]: Train loss: 2.2652, Valid loss: 3.2335 Epoch [1499\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.42it\/s, loss=3.13] Epoch [1499\/3000]: Train loss: 2.3712, Valid loss: 2.8168 Epoch [1500\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.46it\/s, loss=2.02] Epoch [1500\/3000]: Train loss: 2.2357, Valid loss: 1.9161 Epoch [1501\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.79it\/s, loss=1.78] Epoch [1501\/3000]: Train loss: 1.8879, Valid loss: 1.9097 Epoch [1502\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.11it\/s, loss=1.71] Epoch [1502\/3000]: Train loss: 2.1667, Valid loss: 2.5592 Epoch [1503\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.73it\/s, loss=2.07] Epoch [1503\/3000]: Train loss: 2.0240, Valid loss: 3.2889 Epoch [1504\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.75it\/s, loss=2.22] Epoch [1504\/3000]: Train loss: 2.1863, Valid loss: 2.3669 Epoch [1505\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.94it\/s, loss=1.95] Epoch [1505\/3000]: Train loss: 2.2825, Valid loss: 1.8155 Epoch [1506\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.39it\/s, loss=1.71] Epoch [1506\/3000]: Train loss: 2.0838, Valid loss: 2.0889 Epoch [1507\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.79it\/s, loss=2.21] Epoch [1507\/3000]: Train loss: 2.3716, Valid loss: 2.1010 Epoch [1508\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.26it\/s, loss=2.21] Epoch [1508\/3000]: Train loss: 2.0013, Valid loss: 2.4628 Epoch [1509\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.54it\/s, loss=2.87] Epoch [1509\/3000]: Train loss: 2.3735, Valid loss: 2.5803 Epoch [1510\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.69it\/s, loss=2] Epoch [1510\/3000]: Train loss: 2.2499, Valid loss: 3.0123 Epoch [1511\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.52it\/s, loss=1.88] Epoch [1511\/3000]: Train loss: 2.3536, Valid loss: 1.9913 Epoch [1512\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.61it\/s, loss=1.93] Epoch [1512\/3000]: Train loss: 1.8257, Valid loss: 1.8965 Epoch [1513\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.89it\/s, loss=2.61] Epoch [1513\/3000]: Train loss: 1.8469, Valid loss: 3.8708 Epoch [1514\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.12it\/s, loss=2.08] Epoch [1514\/3000]: Train loss: 2.2800, Valid loss: 2.0704 Epoch [1515\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.49it\/s, loss=2.6] Epoch [1515\/3000]: Train loss: 2.1751, Valid loss: 1.8144 Epoch [1516\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.10it\/s, loss=1.85] Epoch [1516\/3000]: Train loss: 1.8125, Valid loss: 2.6772 Epoch [1517\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.25it\/s, loss=1.52] Epoch [1517\/3000]: Train loss: 1.7842, Valid loss: 2.5033 Epoch [1518\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.91it\/s, loss=1.58] Epoch [1518\/3000]: Train loss: 1.7835, Valid loss: 2.3692 Epoch [1519\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.77it\/s, loss=2.27] Epoch [1519\/3000]: Train loss: 1.8933, Valid loss: 1.8622 Epoch [1520\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.89it\/s, loss=2.1] Epoch [1520\/3000]: Train loss: 2.0255, Valid loss: 2.2014 Epoch [1521\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.25it\/s, loss=2.03] Epoch [1521\/3000]: Train loss: 1.8791, Valid loss: 1.8127 Epoch [1522\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.78it\/s, loss=2.03] Epoch [1522\/3000]: Train loss: 1.7867, Valid loss: 2.0195 Epoch [1523\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.06it\/s, loss=2.2] Epoch [1523\/3000]: Train loss: 1.9612, Valid loss: 4.0162 Epoch [1524\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.35it\/s, loss=1.67] Epoch [1524\/3000]: Train loss: 2.1168, Valid loss: 2.8884 Epoch [1525\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.36it\/s, loss=2.92] Epoch [1525\/3000]: Train loss: 2.3619, Valid loss: 2.0332 Epoch [1526\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.46it\/s, loss=2.11] Epoch [1526\/3000]: Train loss: 2.2389, Valid loss: 2.1876 Epoch [1527\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.83it\/s, loss=1.67] Epoch [1527\/3000]: Train loss: 1.7865, Valid loss: 1.9303 Epoch [1528\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.13it\/s, loss=1.75] Epoch [1528\/3000]: Train loss: 1.7994, Valid loss: 1.9298 Epoch [1529\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.61it\/s, loss=1.25] Epoch [1529\/3000]: Train loss: 1.7538, Valid loss: 1.9971 Epoch [1530\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.05it\/s, loss=1.49] Epoch [1530\/3000]: Train loss: 1.7401, Valid loss: 2.3428 Epoch [1531\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.31it\/s, loss=2.23] Epoch [1531\/3000]: Train loss: 2.0193, Valid loss: 3.0675 Epoch [1532\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.67it\/s, loss=1.7] Epoch [1532\/3000]: Train loss: 2.0325, Valid loss: 2.3144 Epoch [1533\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.24it\/s, loss=2.66] Epoch [1533\/3000]: Train loss: 2.2262, Valid loss: 1.8740 Epoch [1534\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.54it\/s, loss=2.92] Epoch [1534\/3000]: Train loss: 1.8978, Valid loss: 2.8343 Epoch [1535\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.80it\/s, loss=1.79] Epoch [1535\/3000]: Train loss: 2.1212, Valid loss: 1.8579 Epoch [1536\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.09it\/s, loss=1.28] Epoch [1536\/3000]: Train loss: 1.9827, Valid loss: 2.6544 Epoch [1537\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.56it\/s, loss=1.67] Epoch [1537\/3000]: Train loss: 1.9794, Valid loss: 1.8889 Epoch [1538\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.92it\/s, loss=2.25] Epoch [1538\/3000]: Train loss: 1.9632, Valid loss: 2.1197 Epoch [1539\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.35it\/s, loss=1.47] Epoch [1539\/3000]: Train loss: 2.3293, Valid loss: 2.4896 Epoch [1540\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.18it\/s, loss=1.93] Epoch [1540\/3000]: Train loss: 2.1175, Valid loss: 1.7001 Epoch [1541\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.63it\/s, loss=1.35] Epoch [1541\/3000]: Train loss: 2.2580, Valid loss: 2.4458 Epoch [1542\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.18it\/s, loss=2.26] Epoch [1542\/3000]: Train loss: 1.9113, Valid loss: 2.0253 Epoch [1543\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.04it\/s, loss=1.98] Epoch [1543\/3000]: Train loss: 1.7650, Valid loss: 2.0663 Epoch [1544\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.17it\/s, loss=1.89] Epoch [1544\/3000]: Train loss: 1.8645, Valid loss: 1.8541 Epoch [1545\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.84it\/s, loss=1.54] Epoch [1545\/3000]: Train loss: 2.0118, Valid loss: 2.5040 Epoch [1546\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.17it\/s, loss=1.58] Epoch [1546\/3000]: Train loss: 1.9575, Valid loss: 2.4562 Epoch [1547\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.11it\/s, loss=2.51] Epoch [1547\/3000]: Train loss: 2.0439, Valid loss: 2.0127 Epoch [1548\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.02it\/s, loss=2.12] Epoch [1548\/3000]: Train loss: 1.8892, Valid loss: 2.2052 Epoch [1549\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.81it\/s, loss=1.43] Epoch [1549\/3000]: Train loss: 1.8232, Valid loss: 2.0778 Epoch [1550\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 102.62it\/s, loss=2.24] Epoch [1550\/3000]: Train loss: 1.8525, Valid loss: 1.8398 Epoch [1551\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.28it\/s, loss=2.33] Epoch [1551\/3000]: Train loss: 2.0702, Valid loss: 3.0283 Epoch [1552\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.47it\/s, loss=2.14] Epoch [1552\/3000]: Train loss: 1.9990, Valid loss: 1.8584 Epoch [1553\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.85it\/s, loss=3.03] Epoch [1553\/3000]: Train loss: 2.5873, Valid loss: 2.5586 Epoch [1554\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.63it\/s, loss=3.44] Epoch [1554\/3000]: Train loss: 2.8057, Valid loss: 3.9053 Epoch [1555\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.55it\/s, loss=2.97] Epoch [1555\/3000]: Train loss: 2.4392, Valid loss: 2.4590 Epoch [1556\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.55it\/s, loss=2.48] Epoch [1556\/3000]: Train loss: 2.0208, Valid loss: 2.4204 Epoch [1557\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 17.35it\/s, loss=1.82] Epoch [1557\/3000]: Train loss: 1.8933, Valid loss: 2.4317 Epoch [1558\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.75it\/s, loss=1.69] Epoch [1558\/3000]: Train loss: 1.9639, Valid loss: 2.1402 Epoch [1559\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.07it\/s, loss=1.89] Epoch [1559\/3000]: Train loss: 1.9939, Valid loss: 1.7943 Epoch [1560\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.47it\/s, loss=1.98] Epoch [1560\/3000]: Train loss: 1.8506, Valid loss: 1.9398 Epoch [1561\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.38it\/s, loss=2.42] Epoch [1561\/3000]: Train loss: 1.9356, Valid loss: 2.1363 Epoch [1562\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.35it\/s, loss=1.85] Epoch [1562\/3000]: Train loss: 1.7958, Valid loss: 2.1787 Epoch [1563\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.07it\/s, loss=1.37] Epoch [1563\/3000]: Train loss: 1.8432, Valid loss: 2.2784 Epoch [1564\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.43it\/s, loss=1.86] Epoch [1564\/3000]: Train loss: 1.7588, Valid loss: 1.8939 Epoch [1565\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.93it\/s, loss=2.21] Epoch [1565\/3000]: Train loss: 1.8106, Valid loss: 2.0243 Epoch [1566\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.95it\/s, loss=2.1] Epoch [1566\/3000]: Train loss: 1.9520, Valid loss: 2.3542 Epoch [1567\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.44it\/s, loss=1.78] Epoch [1567\/3000]: Train loss: 2.1522, Valid loss: 1.9775 Epoch [1568\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.65it\/s, loss=1.51] Epoch [1568\/3000]: Train loss: 1.8998, Valid loss: 1.9478 Epoch [1569\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.88it\/s, loss=1.61] Epoch [1569\/3000]: Train loss: 1.8280, Valid loss: 2.0515 Epoch [1570\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.86it\/s, loss=1.7] Epoch [1570\/3000]: Train loss: 1.7619, Valid loss: 2.0711 Epoch [1571\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.61it\/s, loss=1.99] Epoch [1571\/3000]: Train loss: 1.7489, Valid loss: 1.9605 Epoch [1572\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.54it\/s, loss=1.6] Epoch [1572\/3000]: Train loss: 1.8456, Valid loss: 1.7677 Epoch [1573\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.45it\/s, loss=1.74] Epoch [1573\/3000]: Train loss: 1.8079, Valid loss: 2.3807 Epoch [1574\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.89it\/s, loss=2.14] Epoch [1574\/3000]: Train loss: 1.8286, Valid loss: 1.9004 Epoch [1575\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.63it\/s, loss=1.54] Epoch [1575\/3000]: Train loss: 1.7310, Valid loss: 2.0961 Epoch [1576\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.55it\/s, loss=1.5] Epoch [1576\/3000]: Train loss: 1.7166, Valid loss: 2.1831 Epoch [1577\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.59it\/s, loss=1.79] Epoch [1577\/3000]: Train loss: 1.7304, Valid loss: 1.9600 Epoch [1578\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.95it\/s, loss=3.07] Epoch [1578\/3000]: Train loss: 1.9095, Valid loss: 3.1441 Epoch [1579\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.54it\/s, loss=1.62] Epoch [1579\/3000]: Train loss: 1.9582, Valid loss: 2.1374 Epoch [1580\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.48it\/s, loss=2.03] Epoch [1580\/3000]: Train loss: 1.9033, Valid loss: 2.8876 Epoch [1581\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.97it\/s, loss=2.3] Epoch [1581\/3000]: Train loss: 2.1208, Valid loss: 2.7784 Epoch [1582\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.82it\/s, loss=1.8] Epoch [1582\/3000]: Train loss: 2.0217, Valid loss: 2.1407 Epoch [1583\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.97it\/s, loss=2.96] Epoch [1583\/3000]: Train loss: 2.0840, Valid loss: 2.0812 Epoch [1584\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.41it\/s, loss=2.63] Epoch [1584\/3000]: Train loss: 2.0482, Valid loss: 4.8903 Epoch [1585\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.03it\/s, loss=2.75] Epoch [1585\/3000]: Train loss: 2.6695, Valid loss: 2.6163 Epoch [1586\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.45it\/s, loss=2.87] Epoch [1586\/3000]: Train loss: 2.4946, Valid loss: 2.1293 Epoch [1587\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.76it\/s, loss=2.23] Epoch [1587\/3000]: Train loss: 2.1263, Valid loss: 3.0854 Epoch [1588\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.28it\/s, loss=1.73] Epoch [1588\/3000]: Train loss: 2.1322, Valid loss: 2.0712 Epoch [1589\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.43it\/s, loss=2.5] Epoch [1589\/3000]: Train loss: 2.4790, Valid loss: 2.7487 Epoch [1590\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.41it\/s, loss=1.92] Epoch [1590\/3000]: Train loss: 1.9396, Valid loss: 1.9790 Epoch [1591\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.31it\/s, loss=1.92] Epoch [1591\/3000]: Train loss: 2.1330, Valid loss: 2.9657 Epoch [1592\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.39it\/s, loss=2.18] Epoch [1592\/3000]: Train loss: 2.1748, Valid loss: 2.2378 Epoch [1593\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.93it\/s, loss=2.5] Epoch [1593\/3000]: Train loss: 1.8064, Valid loss: 2.5998 Epoch [1594\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.28it\/s, loss=1.46] Epoch [1594\/3000]: Train loss: 1.8044, Valid loss: 2.1791 Epoch [1595\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 65.92it\/s, loss=1.88] Epoch [1595\/3000]: Train loss: 1.9398, Valid loss: 1.9871 Epoch [1596\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.59it\/s, loss=2.07] Epoch [1596\/3000]: Train loss: 1.8853, Valid loss: 1.9405 Epoch [1597\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.93it\/s, loss=3.91] Epoch [1597\/3000]: Train loss: 2.4632, Valid loss: 2.9581 Epoch [1598\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.97it\/s, loss=1.69] Epoch [1598\/3000]: Train loss: 2.1431, Valid loss: 2.3701 Epoch [1599\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.57it\/s, loss=1.84] Epoch [1599\/3000]: Train loss: 1.8565, Valid loss: 2.3039 Epoch [1600\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.21it\/s, loss=2.07] Epoch [1600\/3000]: Train loss: 1.9072, Valid loss: 1.7635 Epoch [1601\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.85it\/s, loss=1.8] Epoch [1601\/3000]: Train loss: 1.7812, Valid loss: 2.6706 Epoch [1602\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.96it\/s, loss=1.62] Epoch [1602\/3000]: Train loss: 1.9108, Valid loss: 2.7451 Epoch [1603\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.14it\/s, loss=2.99] Epoch [1603\/3000]: Train loss: 2.1377, Valid loss: 2.6378 Epoch [1604\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.89it\/s, loss=1.42] Epoch [1604\/3000]: Train loss: 1.9698, Valid loss: 2.7311 Epoch [1605\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.20it\/s, loss=1.53] Epoch [1605\/3000]: Train loss: 1.8585, Valid loss: 1.7855 Epoch [1606\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.36it\/s, loss=1.31] Epoch [1606\/3000]: Train loss: 1.7065, Valid loss: 2.6698 Epoch [1607\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.10it\/s, loss=2.18] Epoch [1607\/3000]: Train loss: 1.9549, Valid loss: 2.6238 Epoch [1608\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.92it\/s, loss=1.41] Epoch [1608\/3000]: Train loss: 1.7670, Valid loss: 2.0225 Epoch [1609\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.12it\/s, loss=1.52] Epoch [1609\/3000]: Train loss: 1.8029, Valid loss: 2.2228 Epoch [1610\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.86it\/s, loss=2.31] Epoch [1610\/3000]: Train loss: 1.7785, Valid loss: 1.8359 Epoch [1611\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.77it\/s, loss=1.46] Epoch [1611\/3000]: Train loss: 1.7694, Valid loss: 1.8818 Epoch [1612\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.06it\/s, loss=2.03] Epoch [1612\/3000]: Train loss: 1.7682, Valid loss: 1.9360 Epoch [1613\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 101.05it\/s, loss=1.59] Epoch [1613\/3000]: Train loss: 1.7532, Valid loss: 1.8867 Epoch [1614\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.64it\/s, loss=2.14] Epoch [1614\/3000]: Train loss: 1.8121, Valid loss: 2.1662 Epoch [1615\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.13it\/s, loss=1.8] Epoch [1615\/3000]: Train loss: 1.9251, Valid loss: 1.8316 Epoch [1616\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 103.26it\/s, loss=1.79] Epoch [1616\/3000]: Train loss: 1.9909, Valid loss: 3.1004 Epoch [1617\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.25it\/s, loss=2.02] Epoch [1617\/3000]: Train loss: 2.3121, Valid loss: 2.1411 Epoch [1618\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.12it\/s, loss=1.52] Epoch [1618\/3000]: Train loss: 1.7660, Valid loss: 1.8470 Epoch [1619\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.84it\/s, loss=1.52] Epoch [1619\/3000]: Train loss: 1.7736, Valid loss: 1.8623 Epoch [1620\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.87it\/s, loss=1.35] Epoch [1620\/3000]: Train loss: 1.7021, Valid loss: 2.7180 Epoch [1621\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.31it\/s, loss=2.01] Epoch [1621\/3000]: Train loss: 2.0539, Valid loss: 3.2205 Epoch [1622\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.58it\/s, loss=2.28] Epoch [1622\/3000]: Train loss: 2.4972, Valid loss: 2.9703 Epoch [1623\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.14it\/s, loss=2.57] Epoch [1623\/3000]: Train loss: 2.3567, Valid loss: 2.0240 Epoch [1624\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.72it\/s, loss=6.08] Epoch [1624\/3000]: Train loss: 3.3099, Valid loss: 2.3716 Epoch [1625\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.59it\/s, loss=3.82] Epoch [1625\/3000]: Train loss: 2.6425, Valid loss: 3.5894 Epoch [1626\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.71it\/s, loss=2.42] Epoch [1626\/3000]: Train loss: 2.4293, Valid loss: 1.8619 Epoch [1627\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.53it\/s, loss=1.72] Epoch [1627\/3000]: Train loss: 2.0118, Valid loss: 1.9867 Epoch [1628\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.49it\/s, loss=1.92] Epoch [1628\/3000]: Train loss: 1.7274, Valid loss: 1.8241 Epoch [1629\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.61it\/s, loss=1.61] Epoch [1629\/3000]: Train loss: 1.7111, Valid loss: 1.9112 Epoch [1630\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.28it\/s, loss=1.97] Epoch [1630\/3000]: Train loss: 1.8515, Valid loss: 1.9608 Epoch [1631\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.23it\/s, loss=1.4] Epoch [1631\/3000]: Train loss: 1.8418, Valid loss: 2.8740 Epoch [1632\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.32it\/s, loss=2.11] Epoch [1632\/3000]: Train loss: 1.8738, Valid loss: 2.5272 Epoch [1633\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 102.11it\/s, loss=1.71] Epoch [1633\/3000]: Train loss: 1.8709, Valid loss: 1.7683 Epoch [1634\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.81it\/s, loss=1.93] Epoch [1634\/3000]: Train loss: 1.7578, Valid loss: 1.8983 Epoch [1635\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.61it\/s, loss=1.4] Epoch [1635\/3000]: Train loss: 1.9307, Valid loss: 2.2525 Epoch [1636\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.57it\/s, loss=1.32] Epoch [1636\/3000]: Train loss: 1.7394, Valid loss: 2.0907 Epoch [1637\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.61it\/s, loss=1.82] Epoch [1637\/3000]: Train loss: 1.7744, Valid loss: 1.9997 Epoch [1638\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.20it\/s, loss=2.1] Epoch [1638\/3000]: Train loss: 1.7574, Valid loss: 2.2107 Epoch [1639\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.19it\/s, loss=1.77] Epoch [1639\/3000]: Train loss: 1.9073, Valid loss: 1.8450 Epoch [1640\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.03it\/s, loss=1.67] Epoch [1640\/3000]: Train loss: 1.7892, Valid loss: 1.8907 Epoch [1641\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.92it\/s, loss=1.6] Epoch [1641\/3000]: Train loss: 1.7533, Valid loss: 1.7140 Epoch [1642\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.71it\/s, loss=2.51] Epoch [1642\/3000]: Train loss: 1.7962, Valid loss: 2.2691 Epoch [1643\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.95it\/s, loss=2.64] Epoch [1643\/3000]: Train loss: 2.0258, Valid loss: 3.0821 Epoch [1644\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.68it\/s, loss=3.77] Epoch [1644\/3000]: Train loss: 2.8806, Valid loss: 2.1192 Epoch [1645\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.29it\/s, loss=3.5] Epoch [1645\/3000]: Train loss: 2.5679, Valid loss: 4.9476 Epoch [1646\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.72it\/s, loss=2.14] Epoch [1646\/3000]: Train loss: 2.7831, Valid loss: 3.3640 Epoch [1647\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.28it\/s, loss=1.69] Epoch [1647\/3000]: Train loss: 2.1360, Valid loss: 2.7921 Epoch [1648\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.41it\/s, loss=3.02] Epoch [1648\/3000]: Train loss: 2.1375, Valid loss: 2.3084 Epoch [1649\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.43it\/s, loss=1.23] Epoch [1649\/3000]: Train loss: 2.0428, Valid loss: 2.7446 Epoch [1650\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.50it\/s, loss=2.42] Epoch [1650\/3000]: Train loss: 2.3734, Valid loss: 2.1730 Epoch [1651\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.15it\/s, loss=2.32] Epoch [1651\/3000]: Train loss: 2.1158, Valid loss: 4.5018 Epoch [1652\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.73it\/s, loss=1.68] Epoch [1652\/3000]: Train loss: 2.6774, Valid loss: 3.0078 Epoch [1653\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.58it\/s, loss=1.28] Epoch [1653\/3000]: Train loss: 2.0892, Valid loss: 2.3552 Epoch [1654\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.52it\/s, loss=1.62] Epoch [1654\/3000]: Train loss: 1.7167, Valid loss: 2.1982 Epoch [1655\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.36it\/s, loss=2.06] Epoch [1655\/3000]: Train loss: 1.9238, Valid loss: 2.2410 Epoch [1656\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.99it\/s, loss=1.78] Epoch [1656\/3000]: Train loss: 2.1340, Valid loss: 2.8474 Epoch [1657\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.33it\/s, loss=2.32] Epoch [1657\/3000]: Train loss: 2.0994, Valid loss: 1.8467 Epoch [1658\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.32it\/s, loss=1.74] Epoch [1658\/3000]: Train loss: 1.8354, Valid loss: 2.5434 Epoch [1659\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.20it\/s, loss=1.71] Epoch [1659\/3000]: Train loss: 2.3217, Valid loss: 2.5040 Epoch [1660\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.00it\/s, loss=3.1] Epoch [1660\/3000]: Train loss: 2.3893, Valid loss: 2.7766 Epoch [1661\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.87it\/s, loss=2.37] Epoch [1661\/3000]: Train loss: 2.2081, Valid loss: 2.0704 Epoch [1662\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.73it\/s, loss=2.69] Epoch [1662\/3000]: Train loss: 1.9777, Valid loss: 2.1450 Epoch [1663\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.53it\/s, loss=1.85] Epoch [1663\/3000]: Train loss: 1.9882, Valid loss: 2.2608 Epoch [1664\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.25it\/s, loss=1.88] Epoch [1664\/3000]: Train loss: 1.9585, Valid loss: 2.3239 Epoch [1665\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.07it\/s, loss=2.73] Epoch [1665\/3000]: Train loss: 1.8957, Valid loss: 1.7867 Epoch [1666\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 103.93it\/s, loss=1.96] Epoch [1666\/3000]: Train loss: 1.9117, Valid loss: 1.8621 Epoch [1667\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.47it\/s, loss=3.26] Epoch [1667\/3000]: Train loss: 2.1539, Valid loss: 1.7832 Epoch [1668\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.82it\/s, loss=1.85] Epoch [1668\/3000]: Train loss: 2.3010, Valid loss: 2.6368 Epoch [1669\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.91it\/s, loss=3.63] Epoch [1669\/3000]: Train loss: 2.2384, Valid loss: 3.0002 Epoch [1670\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.56it\/s, loss=3.13] Epoch [1670\/3000]: Train loss: 2.2540, Valid loss: 2.9002 Epoch [1671\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.43it\/s, loss=1.66] Epoch [1671\/3000]: Train loss: 2.2035, Valid loss: 3.8449 Epoch [1672\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.94it\/s, loss=1.95] Epoch [1672\/3000]: Train loss: 2.8258, Valid loss: 4.2761 Epoch [1673\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.48it\/s, loss=1.79] Epoch [1673\/3000]: Train loss: 2.7131, Valid loss: 2.5585 Epoch [1674\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.28it\/s, loss=1.44] Epoch [1674\/3000]: Train loss: 1.7949, Valid loss: 2.3808 Epoch [1675\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.31it\/s, loss=1.53] Epoch [1675\/3000]: Train loss: 1.7300, Valid loss: 1.6634 Epoch [1676\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.75it\/s, loss=1.81] Epoch [1676\/3000]: Train loss: 1.7921, Valid loss: 1.8544 Epoch [1677\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.57it\/s, loss=1.56] Epoch [1677\/3000]: Train loss: 1.7124, Valid loss: 2.7053 Epoch [1678\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.67it\/s, loss=1.65] Epoch [1678\/3000]: Train loss: 1.8558, Valid loss: 2.3949 Epoch [1679\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.36it\/s, loss=2.35] Epoch [1679\/3000]: Train loss: 2.0248, Valid loss: 1.9793 Epoch [1680\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.56it\/s, loss=2.35] Epoch [1680\/3000]: Train loss: 1.9474, Valid loss: 2.3983 Epoch [1681\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.24it\/s, loss=1.81] Epoch [1681\/3000]: Train loss: 1.8348, Valid loss: 2.1263 Epoch [1682\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.68it\/s, loss=1.47] Epoch [1682\/3000]: Train loss: 1.7099, Valid loss: 1.9315 Epoch [1683\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.01it\/s, loss=1.65] Epoch [1683\/3000]: Train loss: 1.7241, Valid loss: 1.9084 Epoch [1684\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.27it\/s, loss=1.66] Epoch [1684\/3000]: Train loss: 1.7381, Valid loss: 2.1181 Epoch [1685\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.99it\/s, loss=1.95] Epoch [1685\/3000]: Train loss: 1.7883, Valid loss: 3.0282 Epoch [1686\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.59it\/s, loss=1.7] Epoch [1686\/3000]: Train loss: 1.9893, Valid loss: 2.4029 Epoch [1687\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.13it\/s, loss=1.71] Epoch [1687\/3000]: Train loss: 1.7913, Valid loss: 2.0909 Epoch [1688\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.21it\/s, loss=3.1] Epoch [1688\/3000]: Train loss: 2.0122, Valid loss: 2.2991 Epoch [1689\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.81it\/s, loss=1.63] Epoch [1689\/3000]: Train loss: 1.8009, Valid loss: 1.8194 Epoch [1690\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.89it\/s, loss=1.73] Epoch [1690\/3000]: Train loss: 1.7144, Valid loss: 2.0588 Epoch [1691\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.21it\/s, loss=1.78] Epoch [1691\/3000]: Train loss: 2.2542, Valid loss: 2.7074 Epoch [1692\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 63.62it\/s, loss=1.49] Epoch [1692\/3000]: Train loss: 1.9592, Valid loss: 2.0901 Epoch [1693\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.09it\/s, loss=1.85] Epoch [1693\/3000]: Train loss: 1.8500, Valid loss: 1.8161 Epoch [1694\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.33it\/s, loss=1.28] Epoch [1694\/3000]: Train loss: 1.7123, Valid loss: 2.6583 Epoch [1695\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.48it\/s, loss=2.04] Epoch [1695\/3000]: Train loss: 1.7969, Valid loss: 2.5013 Epoch [1696\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.51it\/s, loss=1.36] Epoch [1696\/3000]: Train loss: 1.8179, Valid loss: 2.3853 Epoch [1697\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.14it\/s, loss=2.28] Epoch [1697\/3000]: Train loss: 1.9705, Valid loss: 2.1837 Epoch [1698\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.66it\/s, loss=1.76] Epoch [1698\/3000]: Train loss: 1.8738, Valid loss: 2.0754 Epoch [1699\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.05it\/s, loss=1.79] Epoch [1699\/3000]: Train loss: 1.8177, Valid loss: 2.2314 Epoch [1700\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.80it\/s, loss=2] Epoch [1700\/3000]: Train loss: 2.0417, Valid loss: 2.6844 Epoch [1701\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.59it\/s, loss=1.83] Epoch [1701\/3000]: Train loss: 2.1698, Valid loss: 2.2397 Epoch [1702\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.63it\/s, loss=1.54] Epoch [1702\/3000]: Train loss: 2.0807, Valid loss: 2.6735 Epoch [1703\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.96it\/s, loss=1.5] Epoch [1703\/3000]: Train loss: 1.8534, Valid loss: 2.0833 Epoch [1704\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.05it\/s, loss=1.87] Epoch [1704\/3000]: Train loss: 1.8018, Valid loss: 2.0200 Epoch [1705\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.38it\/s, loss=2.38] Epoch [1705\/3000]: Train loss: 1.7761, Valid loss: 2.1471 Epoch [1706\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.49it\/s, loss=1.81] Epoch [1706\/3000]: Train loss: 1.8824, Valid loss: 2.6564 Epoch [1707\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.08it\/s, loss=1.87] Epoch [1707\/3000]: Train loss: 1.9457, Valid loss: 2.5645 Epoch [1708\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.65it\/s, loss=2.2] Epoch [1708\/3000]: Train loss: 1.9748, Valid loss: 3.7334 Epoch [1709\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.63it\/s, loss=2.72] Epoch [1709\/3000]: Train loss: 2.6836, Valid loss: 1.9168 Epoch [1710\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.58it\/s, loss=1.81] Epoch [1710\/3000]: Train loss: 1.9750, Valid loss: 2.1416 Epoch [1711\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.68it\/s, loss=1.91] Epoch [1711\/3000]: Train loss: 1.7282, Valid loss: 1.8957 Epoch [1712\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.59it\/s, loss=1.49] Epoch [1712\/3000]: Train loss: 1.7779, Valid loss: 1.9085 Epoch [1713\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 17.89it\/s, loss=2.26] Epoch [1713\/3000]: Train loss: 1.7938, Valid loss: 1.8485 Epoch [1714\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.58it\/s, loss=1.87] Epoch [1714\/3000]: Train loss: 1.9048, Valid loss: 2.2314 Epoch [1715\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.09it\/s, loss=3.59] Epoch [1715\/3000]: Train loss: 2.1611, Valid loss: 1.8964 Epoch [1716\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.37it\/s, loss=1.89] Epoch [1716\/3000]: Train loss: 2.3465, Valid loss: 3.3822 Epoch [1717\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.56it\/s, loss=3.55] Epoch [1717\/3000]: Train loss: 2.4015, Valid loss: 2.0695 Epoch [1718\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.00it\/s, loss=1.78] Epoch [1718\/3000]: Train loss: 2.3666, Valid loss: 3.0982 Epoch [1719\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.20it\/s, loss=3] Epoch [1719\/3000]: Train loss: 2.3997, Valid loss: 2.6718 Epoch [1720\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.40it\/s, loss=1.71] Epoch [1720\/3000]: Train loss: 1.8184, Valid loss: 1.8167 Epoch [1721\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.67it\/s, loss=1.9] Epoch [1721\/3000]: Train loss: 1.7382, Valid loss: 1.9750 Epoch [1722\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.07it\/s, loss=1.74] Epoch [1722\/3000]: Train loss: 1.7987, Valid loss: 2.1627 Epoch [1723\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.19it\/s, loss=1.87] Epoch [1723\/3000]: Train loss: 1.8069, Valid loss: 2.3325 Epoch [1724\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.19it\/s, loss=1.24] Epoch [1724\/3000]: Train loss: 1.7283, Valid loss: 1.7911 Epoch [1725\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.01it\/s, loss=1.77] Epoch [1725\/3000]: Train loss: 2.0814, Valid loss: 1.9553 Epoch [1726\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.26it\/s, loss=2.05] Epoch [1726\/3000]: Train loss: 1.7294, Valid loss: 2.1647 Epoch [1727\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.43it\/s, loss=1.53] Epoch [1727\/3000]: Train loss: 1.7252, Valid loss: 1.9154 Epoch [1728\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 66.45it\/s, loss=1.8] Epoch [1728\/3000]: Train loss: 1.8209, Valid loss: 2.5719 Epoch [1729\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.84it\/s, loss=1.94] Epoch [1729\/3000]: Train loss: 2.2773, Valid loss: 2.4885 Epoch [1730\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.52it\/s, loss=1.72] Epoch [1730\/3000]: Train loss: 1.8180, Valid loss: 1.7266 Epoch [1731\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 71.07it\/s, loss=2.05] Epoch [1731\/3000]: Train loss: 1.9978, Valid loss: 2.6718 Epoch [1732\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.59it\/s, loss=3.25] Epoch [1732\/3000]: Train loss: 2.7860, Valid loss: 2.0311 Epoch [1733\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.58it\/s, loss=3.56] Epoch [1733\/3000]: Train loss: 2.3384, Valid loss: 3.4462 Epoch [1734\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.05it\/s, loss=1.65] Epoch [1734\/3000]: Train loss: 2.3467, Valid loss: 3.0875 Epoch [1735\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.44it\/s, loss=2.22] Epoch [1735\/3000]: Train loss: 2.1830, Valid loss: 2.3034 Epoch [1736\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.96it\/s, loss=2.11] Epoch [1736\/3000]: Train loss: 1.9485, Valid loss: 3.6680 Epoch [1737\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.18it\/s, loss=1.54] Epoch [1737\/3000]: Train loss: 2.0790, Valid loss: 2.0144 Epoch [1738\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.13it\/s, loss=2.4] Epoch [1738\/3000]: Train loss: 1.9546, Valid loss: 4.0770 Epoch [1739\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.63it\/s, loss=3.43] Epoch [1739\/3000]: Train loss: 2.8552, Valid loss: 1.8349 Epoch [1740\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.70it\/s, loss=3.24] Epoch [1740\/3000]: Train loss: 2.2148, Valid loss: 3.4226 Epoch [1741\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.53it\/s, loss=1.68] Epoch [1741\/3000]: Train loss: 2.4044, Valid loss: 2.0156 Epoch [1742\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.25it\/s, loss=1.25] Epoch [1742\/3000]: Train loss: 1.8538, Valid loss: 3.6555 Epoch [1743\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.52it\/s, loss=5.21] Epoch [1743\/3000]: Train loss: 3.1366, Valid loss: 4.4983 Epoch [1744\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.60it\/s, loss=3.28] Epoch [1744\/3000]: Train loss: 2.8178, Valid loss: 4.5207 Epoch [1745\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.23it\/s, loss=2.48] Epoch [1745\/3000]: Train loss: 2.7840, Valid loss: 2.4883 Epoch [1746\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.65it\/s, loss=5.1] Epoch [1746\/3000]: Train loss: 3.1459, Valid loss: 3.2457 Epoch [1747\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.93it\/s, loss=4.44] Epoch [1747\/3000]: Train loss: 3.0103, Valid loss: 3.0455 Epoch [1748\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.95it\/s, loss=3.64] Epoch [1748\/3000]: Train loss: 2.8527, Valid loss: 4.2625 Epoch [1749\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.29it\/s, loss=1.63] Epoch [1749\/3000]: Train loss: 2.8175, Valid loss: 2.1640 Epoch [1750\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.16it\/s, loss=1.91] Epoch [1750\/3000]: Train loss: 1.7520, Valid loss: 2.4725 Epoch [1751\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.57it\/s, loss=1.6] Epoch [1751\/3000]: Train loss: 1.6843, Valid loss: 2.2412 Epoch [1752\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.92it\/s, loss=1.26] Epoch [1752\/3000]: Train loss: 1.7220, Valid loss: 2.0505 Epoch [1753\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.07it\/s, loss=2.11] Epoch [1753\/3000]: Train loss: 1.8520, Valid loss: 2.2832 Epoch [1754\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.86it\/s, loss=2.35] Epoch [1754\/3000]: Train loss: 2.0996, Valid loss: 2.2042 Epoch [1755\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.58it\/s, loss=2.16] Epoch [1755\/3000]: Train loss: 1.9704, Valid loss: 2.2128 Epoch [1756\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.85it\/s, loss=2.13] Epoch [1756\/3000]: Train loss: 1.9124, Valid loss: 2.2844 Epoch [1757\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.66it\/s, loss=2.34] Epoch [1757\/3000]: Train loss: 2.0219, Valid loss: 1.8104 Epoch [1758\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.42it\/s, loss=1.62] Epoch [1758\/3000]: Train loss: 1.8329, Valid loss: 1.9653 Epoch [1759\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.49it\/s, loss=1.69] Epoch [1759\/3000]: Train loss: 1.8299, Valid loss: 2.1930 Epoch [1760\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.49it\/s, loss=1.31] Epoch [1760\/3000]: Train loss: 1.8253, Valid loss: 2.7391 Epoch [1761\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.27it\/s, loss=1.99] Epoch [1761\/3000]: Train loss: 2.0026, Valid loss: 2.5022 Epoch [1762\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.64it\/s, loss=1.85] Epoch [1762\/3000]: Train loss: 2.1086, Valid loss: 2.1323 Epoch [1763\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.77it\/s, loss=2.06] Epoch [1763\/3000]: Train loss: 1.7686, Valid loss: 2.2677 Epoch [1764\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 102.61it\/s, loss=2.23] Epoch [1764\/3000]: Train loss: 1.7635, Valid loss: 2.0022 Epoch [1765\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.47it\/s, loss=1.86] Epoch [1765\/3000]: Train loss: 1.6924, Valid loss: 2.4483 Epoch [1766\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.17it\/s, loss=1.59] Epoch [1766\/3000]: Train loss: 1.8932, Valid loss: 2.0243 Epoch [1767\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.81it\/s, loss=1.52] Epoch [1767\/3000]: Train loss: 1.7580, Valid loss: 2.1385 Epoch [1768\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.43it\/s, loss=1.33] Epoch [1768\/3000]: Train loss: 1.8018, Valid loss: 2.4045 Epoch [1769\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.72it\/s, loss=1.52] Epoch [1769\/3000]: Train loss: 1.6957, Valid loss: 1.8364 Epoch [1770\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 56.96it\/s, loss=2] Epoch [1770\/3000]: Train loss: 1.7713, Valid loss: 2.4319 Epoch [1771\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.10it\/s, loss=1.68] Epoch [1771\/3000]: Train loss: 1.7621, Valid loss: 2.2091 Epoch [1772\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 69.08it\/s, loss=2.21] Epoch [1772\/3000]: Train loss: 1.8429, Valid loss: 2.2950 Epoch [1773\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 63.35it\/s, loss=1.81] Epoch [1773\/3000]: Train loss: 1.7828, Valid loss: 2.0372 Epoch [1774\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.61it\/s, loss=1.45] Epoch [1774\/3000]: Train loss: 1.6780, Valid loss: 2.1388 Epoch [1775\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.96it\/s, loss=1.79] Epoch [1775\/3000]: Train loss: 1.7608, Valid loss: 1.7971 Epoch [1776\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.61it\/s, loss=2.03] Epoch [1776\/3000]: Train loss: 1.7029, Valid loss: 2.3967 Epoch [1777\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.81it\/s, loss=1.98] Epoch [1777\/3000]: Train loss: 1.7743, Valid loss: 2.1900 Epoch [1778\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.75it\/s, loss=1.16] Epoch [1778\/3000]: Train loss: 1.7816, Valid loss: 2.3341 Epoch [1779\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.77it\/s, loss=1.98] Epoch [1779\/3000]: Train loss: 1.7738, Valid loss: 1.9802 Epoch [1780\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.44it\/s, loss=1.99] Epoch [1780\/3000]: Train loss: 1.8406, Valid loss: 2.3580 Epoch [1781\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.13it\/s, loss=1.39] Epoch [1781\/3000]: Train loss: 1.8831, Valid loss: 1.9362 Epoch [1782\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.85it\/s, loss=1.34] Epoch [1782\/3000]: Train loss: 1.6840, Valid loss: 1.8515 Epoch [1783\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.01it\/s, loss=1.59] Epoch [1783\/3000]: Train loss: 1.8073, Valid loss: 2.3497 Epoch [1784\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.01it\/s, loss=1.93] Epoch [1784\/3000]: Train loss: 1.8920, Valid loss: 2.5247 Epoch [1785\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.31it\/s, loss=1.18] Epoch [1785\/3000]: Train loss: 2.0567, Valid loss: 3.2216 Epoch [1786\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.85it\/s, loss=2.77] Epoch [1786\/3000]: Train loss: 2.3354, Valid loss: 1.8499 Epoch [1787\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.92it\/s, loss=2.32] Epoch [1787\/3000]: Train loss: 1.9405, Valid loss: 2.0570 Epoch [1788\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.77it\/s, loss=2.05] Epoch [1788\/3000]: Train loss: 2.1229, Valid loss: 2.5977 Epoch [1789\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.34it\/s, loss=1.87] Epoch [1789\/3000]: Train loss: 1.9962, Valid loss: 1.9209 Epoch [1790\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.86it\/s, loss=2.53] Epoch [1790\/3000]: Train loss: 1.8101, Valid loss: 1.6983 Epoch [1791\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.48it\/s, loss=1.44] Epoch [1791\/3000]: Train loss: 1.8675, Valid loss: 2.4540 Epoch [1792\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.37it\/s, loss=1.4] Epoch [1792\/3000]: Train loss: 1.9875, Valid loss: 2.3621 Epoch [1793\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.69it\/s, loss=1.74] Epoch [1793\/3000]: Train loss: 1.8451, Valid loss: 1.9315 Epoch [1794\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.30it\/s, loss=1.23] Epoch [1794\/3000]: Train loss: 1.6580, Valid loss: 2.0409 Epoch [1795\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.32it\/s, loss=1.77] Epoch [1795\/3000]: Train loss: 1.7784, Valid loss: 1.8857 Epoch [1796\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 86.79it\/s, loss=2.26] Epoch [1796\/3000]: Train loss: 1.7426, Valid loss: 2.2903 Epoch [1797\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.73it\/s, loss=1.72] Epoch [1797\/3000]: Train loss: 1.8879, Valid loss: 2.1926 Epoch [1798\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.20it\/s, loss=1.53] Epoch [1798\/3000]: Train loss: 1.8299, Valid loss: 2.2412 Epoch [1799\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.04it\/s, loss=1.5] Epoch [1799\/3000]: Train loss: 1.6810, Valid loss: 1.7766 Epoch [1800\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.71it\/s, loss=1.77] Epoch [1800\/3000]: Train loss: 1.7582, Valid loss: 1.8483 Epoch [1801\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.92it\/s, loss=1.49] Epoch [1801\/3000]: Train loss: 1.7332, Valid loss: 2.1276 Epoch [1802\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.89it\/s, loss=2] Epoch [1802\/3000]: Train loss: 1.7199, Valid loss: 2.1894 Epoch [1803\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.80it\/s, loss=2.18] Epoch [1803\/3000]: Train loss: 1.8881, Valid loss: 2.0088 Epoch [1804\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.39it\/s, loss=1.56] Epoch [1804\/3000]: Train loss: 1.7021, Valid loss: 1.7238 Epoch [1805\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.65it\/s, loss=2] Epoch [1805\/3000]: Train loss: 1.7605, Valid loss: 1.9461 Epoch [1806\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.26it\/s, loss=1.75] Epoch [1806\/3000]: Train loss: 1.8082, Valid loss: 2.0280 Epoch [1807\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.17it\/s, loss=2.83] Epoch [1807\/3000]: Train loss: 2.3438, Valid loss: 3.4190 Epoch [1808\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 101.66it\/s, loss=2.14] Epoch [1808\/3000]: Train loss: 2.1685, Valid loss: 2.3237 Epoch [1809\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 100.33it\/s, loss=2.68] Epoch [1809\/3000]: Train loss: 2.2180, Valid loss: 1.9743 Epoch [1810\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.53it\/s, loss=1.54] Epoch [1810\/3000]: Train loss: 1.7403, Valid loss: 1.7901 Epoch [1811\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.07it\/s, loss=2.23] Epoch [1811\/3000]: Train loss: 1.7658, Valid loss: 1.9818 Epoch [1812\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.40it\/s, loss=1.7] Epoch [1812\/3000]: Train loss: 1.7117, Valid loss: 3.3281 Epoch [1813\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.62it\/s, loss=2.12] Epoch [1813\/3000]: Train loss: 1.9530, Valid loss: 2.3462 Epoch [1814\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.60it\/s, loss=1.41] Epoch [1814\/3000]: Train loss: 1.7501, Valid loss: 1.8736 Epoch [1815\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.51it\/s, loss=2.49] Epoch [1815\/3000]: Train loss: 1.7926, Valid loss: 3.8171 Epoch [1816\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.71it\/s, loss=1.35] Epoch [1816\/3000]: Train loss: 2.2384, Valid loss: 2.3143 Epoch [1817\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.93it\/s, loss=2.28] Epoch [1817\/3000]: Train loss: 2.3413, Valid loss: 1.9592 Epoch [1818\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.92it\/s, loss=2.29] Epoch [1818\/3000]: Train loss: 2.1966, Valid loss: 1.9950 Epoch [1819\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.48it\/s, loss=1.32] Epoch [1819\/3000]: Train loss: 1.6781, Valid loss: 1.9216 Epoch [1820\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.91it\/s, loss=2.65] Epoch [1820\/3000]: Train loss: 1.7918, Valid loss: 2.6208 Epoch [1821\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.80it\/s, loss=1.68] Epoch [1821\/3000]: Train loss: 1.8470, Valid loss: 2.4178 Epoch [1822\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.06it\/s, loss=1.7] Epoch [1822\/3000]: Train loss: 1.8325, Valid loss: 2.0918 Epoch [1823\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.19it\/s, loss=1.16] Epoch [1823\/3000]: Train loss: 1.6975, Valid loss: 1.6507 Epoch [1824\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.22it\/s, loss=1.94] Epoch [1824\/3000]: Train loss: 1.6781, Valid loss: 1.8269 Epoch [1825\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.33it\/s, loss=2.01] Epoch [1825\/3000]: Train loss: 1.7411, Valid loss: 2.7476 Epoch [1826\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.98it\/s, loss=1.59] Epoch [1826\/3000]: Train loss: 2.0219, Valid loss: 3.7337 Epoch [1827\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.64it\/s, loss=2.19] Epoch [1827\/3000]: Train loss: 2.6852, Valid loss: 2.1300 Epoch [1828\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.98it\/s, loss=1.43] Epoch [1828\/3000]: Train loss: 2.4030, Valid loss: 3.7055 Epoch [1829\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.18it\/s, loss=1.94] Epoch [1829\/3000]: Train loss: 2.2389, Valid loss: 2.2461 Epoch [1830\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 89.76it\/s, loss=2.07] Epoch [1830\/3000]: Train loss: 2.0272, Valid loss: 2.0315 Epoch [1831\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.00it\/s, loss=1.9] Epoch [1831\/3000]: Train loss: 1.9035, Valid loss: 2.9073 Epoch [1832\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.57it\/s, loss=2.61] Epoch [1832\/3000]: Train loss: 2.3719, Valid loss: 1.9161 Epoch [1833\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.08it\/s, loss=1.79] Epoch [1833\/3000]: Train loss: 1.9386, Valid loss: 2.6087 Epoch [1834\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.09it\/s, loss=1.36] Epoch [1834\/3000]: Train loss: 1.8712, Valid loss: 1.8814 Epoch [1835\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.05it\/s, loss=1.42] Epoch [1835\/3000]: Train loss: 1.8609, Valid loss: 2.6253 Epoch [1836\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 82.13it\/s, loss=1.55] Epoch [1836\/3000]: Train loss: 1.9096, Valid loss: 2.5609 Epoch [1837\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.67it\/s, loss=1.44] Epoch [1837\/3000]: Train loss: 1.7893, Valid loss: 1.8837 Epoch [1838\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.74it\/s, loss=2.07] Epoch [1838\/3000]: Train loss: 1.7838, Valid loss: 2.2173 Epoch [1839\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 72.27it\/s, loss=1.65] Epoch [1839\/3000]: Train loss: 2.0829, Valid loss: 2.9302 Epoch [1840\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 68.80it\/s, loss=1.69] Epoch [1840\/3000]: Train loss: 2.0561, Valid loss: 2.0653 Epoch [1841\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 70.52it\/s, loss=2.81] Epoch [1841\/3000]: Train loss: 2.2365, Valid loss: 2.4566 Epoch [1842\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.31it\/s, loss=3.3] Epoch [1842\/3000]: Train loss: 2.3003, Valid loss: 2.0956 Epoch [1843\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.52it\/s, loss=1.8] Epoch [1843\/3000]: Train loss: 1.8570, Valid loss: 1.8148 Epoch [1844\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.18it\/s, loss=2.12] Epoch [1844\/3000]: Train loss: 1.7058, Valid loss: 2.1728 Epoch [1845\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.57it\/s, loss=2.43] Epoch [1845\/3000]: Train loss: 2.0487, Valid loss: 2.2364 Epoch [1846\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.67it\/s, loss=2.61] Epoch [1846\/3000]: Train loss: 1.8009, Valid loss: 2.9554 Epoch [1847\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 92.88it\/s, loss=2.46] Epoch [1847\/3000]: Train loss: 2.4345, Valid loss: 2.8518 Epoch [1848\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.69it\/s, loss=2] Epoch [1848\/3000]: Train loss: 2.5101, Valid loss: 1.7942 Epoch [1849\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.90it\/s, loss=1.43] Epoch [1849\/3000]: Train loss: 1.8856, Valid loss: 1.9274 Epoch [1850\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.64it\/s, loss=3.04] Epoch [1850\/3000]: Train loss: 1.8811, Valid loss: 1.9019 Epoch [1851\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 100.83it\/s, loss=1.58] Epoch [1851\/3000]: Train loss: 2.0788, Valid loss: 2.1126 Epoch [1852\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.10it\/s, loss=1.97] Epoch [1852\/3000]: Train loss: 2.0494, Valid loss: 2.4189 Epoch [1853\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 100.92it\/s, loss=1.78] Epoch [1853\/3000]: Train loss: 1.9440, Valid loss: 2.1216 Epoch [1854\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 97.57it\/s, loss=1.66] Epoch [1854\/3000]: Train loss: 1.7824, Valid loss: 2.2230 Epoch [1855\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.87it\/s, loss=1.52] Epoch [1855\/3000]: Train loss: 1.7804, Valid loss: 1.9304 Epoch [1856\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 79.44it\/s, loss=1.64] Epoch [1856\/3000]: Train loss: 1.8078, Valid loss: 2.1192 Epoch [1857\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.35it\/s, loss=1.66] Epoch [1857\/3000]: Train loss: 1.7606, Valid loss: 1.8641 Epoch [1858\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 76.27it\/s, loss=1.45] Epoch [1858\/3000]: Train loss: 1.6712, Valid loss: 1.9567 Epoch [1859\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.41it\/s, loss=2] Epoch [1859\/3000]: Train loss: 1.7483, Valid loss: 1.9753 Epoch [1860\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 80.73it\/s, loss=2.01] Epoch [1860\/3000]: Train loss: 1.7882, Valid loss: 1.8361 Epoch [1861\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 74.33it\/s, loss=1.48] Epoch [1861\/3000]: Train loss: 1.7081, Valid loss: 1.8749 Epoch [1862\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 73.60it\/s, loss=1.66] Epoch [1862\/3000]: Train loss: 1.6476, Valid loss: 1.9812 Epoch [1863\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 91.32it\/s, loss=1.76] Epoch [1863\/3000]: Train loss: 1.7002, Valid loss: 2.3348 Epoch [1864\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.54it\/s, loss=1.3] Epoch [1864\/3000]: Train loss: 1.6817, Valid loss: 2.5445 Epoch [1865\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 90.97it\/s, loss=1.48] Epoch [1865\/3000]: Train loss: 1.7115, Valid loss: 2.0931 Epoch [1866\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 96.50it\/s, loss=2.5] Epoch [1866\/3000]: Train loss: 1.8895, Valid loss: 3.3578 Epoch [1867\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 81.15it\/s, loss=1.67] Epoch [1867\/3000]: Train loss: 1.9581, Valid loss: 2.0097 Epoch [1868\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 94.33it\/s, loss=1.59] Epoch [1868\/3000]: Train loss: 1.8670, Valid loss: 2.2680 Epoch [1869\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 101.77it\/s, loss=2.02] Epoch [1869\/3000]: Train loss: 1.7086, Valid loss: 1.9175 Epoch [1870\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 19.28it\/s, loss=2.32] Epoch [1870\/3000]: Train loss: 1.7351, Valid loss: 2.6859 Epoch [1871\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 85.22it\/s, loss=1.44] Epoch [1871\/3000]: Train loss: 1.7463, Valid loss: 1.9215 Epoch [1872\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 78.48it\/s, loss=1.62] Epoch [1872\/3000]: Train loss: 1.7139, Valid loss: 3.3058 Epoch [1873\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.67it\/s, loss=2.29] Epoch [1873\/3000]: Train loss: 2.2590, Valid loss: 1.8458 Epoch [1874\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 95.64it\/s, loss=1.55] Epoch [1874\/3000]: Train loss: 1.8726, Valid loss: 2.0887 Epoch [1875\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 77.95it\/s, loss=1.56] Epoch [1875\/3000]: Train loss: 1.8976, Valid loss: 2.5682 Epoch [1876\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 75.75it\/s, loss=2.26] Epoch [1876\/3000]: Train loss: 2.0842, Valid loss: 2.1515 Epoch [1877\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 83.69it\/s, loss=2.49] Epoch [1877\/3000]: Train loss: 2.6879, Valid loss: 2.3412 Epoch [1878\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 84.08it\/s, loss=2.04] Epoch [1878\/3000]: Train loss: 1.8745, Valid loss: 2.3562 Epoch [1879\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 93.72it\/s, loss=2.54] Epoch [1879\/3000]: Train loss: 1.9726, Valid loss: 2.3072 Epoch [1880\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 99.96it\/s, loss=1.7] Epoch [1880\/3000]: Train loss: 1.7009, Valid loss: 1.9785 Epoch [1881\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 87.92it\/s, loss=2.22] Epoch [1881\/3000]: Train loss: 1.8828, Valid loss: 2.3367 Epoch [1882\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 98.55it\/s, loss=1.74] Epoch [1882\/3000]: Train loss: 1.8242, Valid loss: 2.1308 Epoch [1883\/3000]: 100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 9\/9 [00:00<00:00, 104.95it\/s, loss=1.98] Epoch [1883\/3000]: Train loss: 1.7934, Valid loss: 2.3699 Model is not improving, so we halt the training session.<\/p>\n\n\n\n
\u7ed8\u5236\u56fe\u50cf<\/p>\n\n\n\n
# \u7ed8\u5236\u56fe\u50cf\n%reload_ext tensorboard\n%tensorboard --logdir=.\/runs\/<\/code><\/pre>\n\n\n\n
\"\"<\/div><\/figure>\n\n\n\n
\u6d4b\u8bd5<\/p>\n\n\n\n
# \u6d4b\u8bd5\ndef save_pred(preds, file):\n    ''' Save predictions to specified file '''\n    with open(file, 'w') as fp:\n        writer = csv.writer(fp)\n        writer.writerow(['id', 'tested_positive'])\n        for i, p in enumerate(preds):\n            writer.writerow([i, p])\n\nmodel = My_Model(input_dim=x_train.shape[1]).to(device)\nmodel.load_state_dict(torch.load(config['save_path']))\npreds = predict(test_loader, model, device)\nsave_pred(preds, 'pred.csv')<\/code><\/pre>\n\n\n\n
100%|\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588\u2588| 5\/5 [00:00<00:00, 551.00it\/s]<\/p>\n\n\n\n
\n\n\n\n
\u4ee5\u4e0a\u5c31\u662f\u4f5c\u4e1a1\u7684\u5185\u5bb9\uff0c\u8fd9\u662f\u4e00\u4e2a\u5f88\u5e9f\u7684model\uff0c\u4e4b\u540e\u7b49\u6211\u80fd\u529b\u63d0\u5347\u4e00\u5b9a\u4f1a\u518d\u56de\u6765\u6539\u62101.0\u7248\uff01<\/p>\n","protected":false},"excerpt":{"rendered":"
\u3010HW1\u3011Regression0.1\u674e\u5b8f\u6bc52021\/2022\u6625\u673a\u5668\u5b66\u4e60\u8bfe\u7a0b\u7b14\u8bb0EP5(P11-P12) \u4ece\u4eca\u5929 […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[15,3,7,9,8],"class_list":["post-213","post","type-post","status-publish","format-standard","hentry","category-lhyjqxxbj","tag-homework","tag-xxbj","tag-jjxx","tag-lhy","tag-deeplearning"],"_links":{"self":[{"href":"https:\/\/tobykskgd.life\/index.php\/wp-json\/wp\/v2\/posts\/213","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/tobykskgd.life\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/tobykskgd.life\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/tobykskgd.life\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/tobykskgd.life\/index.php\/wp-json\/wp\/v2\/comments?post=213"}],"version-history":[{"count":9,"href":"https:\/\/tobykskgd.life\/index.php\/wp-json\/wp\/v2\/posts\/213\/revisions"}],"predecessor-version":[{"id":1867,"href":"https:\/\/tobykskgd.life\/index.php\/wp-json\/wp\/v2\/posts\/213\/revisions\/1867"}],"wp:attachment":[{"href":"https:\/\/tobykskgd.life\/index.php\/wp-json\/wp\/v2\/media?parent=213"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/tobykskgd.life\/index.php\/wp-json\/wp\/v2\/categories?post=213"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/tobykskgd.life\/index.php\/wp-json\/wp\/v2\/tags?post=213"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}