bert-cased

README.md

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+---
+license: mit
+base_model: emilyalsentzer/Bio_ClinicalBERT
+tags:
+- generated_from_trainer
+model-index:
+- name: CliBert-20
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# CliBert-20
+
+This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 5.8847
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 5.8842        | 0.09  | 5    | 5.9152          |
+| 5.7961        | 0.18  | 10   | 5.9106          |
+| 5.7777        | 0.27  | 15   | 5.9060          |
+| 5.7638        | 0.36  | 20   | 5.9016          |
+| 5.7282        | 0.45  | 25   | 5.8980          |
+| 5.6804        | 0.55  | 30   | 5.8942          |
+| 5.6095        | 0.64  | 35   | 5.8912          |
+| 5.5418        | 0.73  | 40   | 5.8890          |
+| 5.5853        | 0.82  | 45   | 5.8864          |
+| 5.55          | 0.91  | 50   | 5.8844          |
+| 5.5284        | 1.0   | 55   | 5.8828          |
+| 5.4085        | 1.09  | 60   | 5.8818          |
+| 5.368         | 1.18  | 65   | 5.8812          |
+| 5.4048        | 1.27  | 70   | 5.8807          |
+| 5.4172        | 1.36  | 75   | 5.8802          |
+| 5.4134        | 1.45  | 80   | 5.8796          |
+| 5.4728        | 1.55  | 85   | 5.8791          |
+| 5.3326        | 1.64  | 90   | 5.8787          |
+| 5.3464        | 1.73  | 95   | 5.8789          |
+| 5.3447        | 1.82  | 100  | 5.8791          |
+| 5.3264        | 1.91  | 105  | 5.8793          |
+| 5.2265        | 2.0   | 110  | 5.8797          |
+| 5.1223        | 2.09  | 115  | 5.8803          |
+| 5.232         | 2.18  | 120  | 5.8811          |
+| 5.3772        | 2.27  | 125  | 5.8815          |
+| 5.2502        | 2.36  | 130  | 5.8821          |
+| 5.2293        | 2.45  | 135  | 5.8825          |
+| 5.1182        | 2.55  | 140  | 5.8832          |
+| 5.0885        | 2.64  | 145  | 5.8839          |
+| 5.157         | 2.73  | 150  | 5.8844          |
+| 5.3388        | 2.82  | 155  | 5.8845          |
+| 5.2609        | 2.91  | 160  | 5.8846          |
+| 5.2008        | 3.0   | 165  | 5.8847          |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1

config.json

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+{
+  "_name_or_path": "emilyalsentzer/Bio_ClinicalBERT",
+  "architectures": [
+    "BertForQuestionAnswering"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "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",
+  "torch_dtype": "float32",
+  "transformers_version": "4.34.1",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 28996
+}

pytorch_model.bin

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special_tokens_map.json

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

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 1000000000000000019884624838656,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

training_args.bin

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