Initial Commit

config.json

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+{
+  "_name_or_path": "dmis-lab/biobert-base-cased-v1.1",
+  "architectures": [
+    "BertForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "B-Anatomy",
+    "1": "B-Chemical",
+    "2": "B-Disease",
+    "3": "I-Anatomy",
+    "4": "I-Chemical",
+    "5": "I-Disease",
+    "6": "O"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-Anatomy": 0,
+    "B-Chemical": 1,
+    "B-Disease": 2,
+    "I-Anatomy": 3,
+    "I-Chemical": 4,
+    "I-Disease": 5,
+    "O": 6
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "transformers_version": "4.8.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 28996
+}

eval_results.txt

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+eval_loss = 0.1652524173259735
+eval_precision = 0.8504558443325623
+eval_recall = 0.8611187655001378
+eval_f1 = 0.8557540905045526
+eval_accuracy = 0.975697565751413
+eval_matrix = [[3901, 4, 60, 102, 1, 10, 538], [0, 4949, 15, 0, 42, 1, 371], [56, 18, 3770, 1, 0, 207, 372], [101, 0, 2, 2779, 0, 26, 335], [0, 32, 0, 0, 1383, 0, 213], [6, 4, 113, 28, 4, 2247, 335], [354, 467, 574, 247, 369, 453, 200220]]
+eval_classification_report =               precision    recall  f1-score   support
+
+     Anatomy       0.85      0.83      0.84      4649
+    Chemical       0.89      0.91      0.90      5402
+     Disease       0.80      0.84      0.82      4465
+
+   micro avg       0.85      0.86      0.86     14516
+   macro avg       0.85      0.86      0.85     14516
+weighted avg       0.85      0.86      0.86     14516
+
+eval_runtime = 16.1004
+eval_samples_per_second = 152.977
+eval_steps_per_second = 0.621
+epoch = 35.0

pytorch_model.bin

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+size 430983665

special_tokens_map.json

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+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

tokenizer_config.json

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+{"unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]"}

training_args.bin

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