update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- bc2gm_corpus
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bc2gm_corpus-Bio_ClinicalBERT-finetuned-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: bc2gm_corpus
+      type: bc2gm_corpus
+      args: bc2gm_corpus
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.7853881278538812
+    - name: Recall
+      type: recall
+      value: 0.8158102766798419
+    - name: F1
+      type: f1
+      value: 0.8003101977510663
+    - name: Accuracy
+      type: accuracy
+      value: 0.9758965601366187
+---
+
+<!-- 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. -->
+
+# bc2gm_corpus-Bio_ClinicalBERT-finetuned-ner
+
+This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the bc2gm_corpus dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1505
+- Precision: 0.7854
+- Recall: 0.8158
+- F1: 0.8003
+- Accuracy: 0.9759
+
+## 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: 2e-05
+- 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0981        | 1.0   | 782  | 0.0712          | 0.7228    | 0.7948 | 0.7571 | 0.9724   |
+| 0.0509        | 2.0   | 1564 | 0.0687          | 0.7472    | 0.8199 | 0.7818 | 0.9746   |
+| 0.0121        | 3.0   | 2346 | 0.0740          | 0.7725    | 0.8011 | 0.7866 | 0.9747   |
+| 0.0001        | 4.0   | 3128 | 0.1009          | 0.7618    | 0.8251 | 0.7922 | 0.9741   |
+| 0.0042        | 5.0   | 3910 | 0.1106          | 0.7757    | 0.8185 | 0.7965 | 0.9754   |
+| 0.0015        | 6.0   | 4692 | 0.1182          | 0.7812    | 0.8111 | 0.7958 | 0.9758   |
+| 0.0001        | 7.0   | 5474 | 0.1283          | 0.7693    | 0.8275 | 0.7973 | 0.9753   |
+| 0.0072        | 8.0   | 6256 | 0.1376          | 0.7863    | 0.8158 | 0.8008 | 0.9762   |
+| 0.0045        | 9.0   | 7038 | 0.1468          | 0.7856    | 0.8180 | 0.8015 | 0.9761   |
+| 0.0           | 10.0  | 7820 | 0.1505          | 0.7854    | 0.8158 | 0.8003 | 0.9759   |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.12.0+cu113
+- Datasets 2.3.2
+- Tokenizers 0.12.1