Training in progress, epoch 0

.gitignore

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config.json

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+{
+  "_name_or_path": "michiyasunaga/BioLinkBERT-base",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
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+  "hidden_act": "gelu",
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+  "hidden_size": 768,
+  "id2label": {
+    "0": "Epidemic Forecasting",
+    "1": "Treatment",
+    "2": "Prevention",
+    "3": "Mechanism",
+    "4": "Case Report",
+    "5": "Transmission",
+    "6": "Diagnosis",
+    "7": "Long Covid",
+    "8": "General Info",
+    "9": "Communication",
+    "10": "Contact Tracing",
+    "11": "Drug Targets",
+    "12": "Education",
+    "13": "Effect on Medical Specialties",
+    "14": "Health Policy",
+    "15": "Healthcare Workers",
+    "16": "Imaging",
+    "17": "Immunology",
+    "18": "Inequality",
+    "19": "Medical Devices",
+    "20": "Misinformation",
+    "21": "Model Systems & Tools",
+    "22": "Molecular Biology",
+    "23": "Non-human",
+    "24": "Non-medical",
+    "25": "Pediatrics",
+    "26": "Prevalence",
+    "27": "Psychology",
+    "28": "Recommendations",
+    "29": "Risk Factors",
+    "30": "Surveillance",
+    "31": "Vaccines",
+    "32": "AI/ML/statistics",
+    "33": "Comorbidities",
+    "34": "Telemedicine",
+    "35": "Drug Design and Discovery"
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+    "Treatment": 1,
+    "Vaccines": 31
+  },
+  "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",
+  "problem_type": "multi_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.28.0",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 28895
+}

pytorch_model.bin

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special_tokens_map.json

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tokenizer_config.json

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+  "tokenizer_class": "BertTokenizer",
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training_args.bin

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