update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- bc2gm_corpus
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: biobert-base-cased-v1.2-bc2gm-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: bc2gm_corpus
+      type: bc2gm_corpus
+      config: bc2gm_corpus
+      split: train
+      args: bc2gm_corpus
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.7988356059445381
+    - name: Recall
+      type: recall
+      value: 0.8243478260869566
+    - name: F1
+      type: f1
+      value: 0.8113912231559292
+    - name: Accuracy
+      type: accuracy
+      value: 0.9772069842818806
+---
+
+<!-- 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. -->
+
+# biobert-base-cased-v1.2-bc2gm-ner
+
+This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) on the bc2gm_corpus dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1528
+- Precision: 0.7988
+- Recall: 0.8243
+- F1: 0.8114
+- Accuracy: 0.9772
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.057         | 1.0   | 782  | 0.0670          | 0.7446    | 0.8051 | 0.7736 | 0.9738   |
+| 0.0586        | 2.0   | 1564 | 0.0689          | 0.7689    | 0.8106 | 0.7892 | 0.9755   |
+| 0.0123        | 3.0   | 2346 | 0.0715          | 0.7846    | 0.8076 | 0.7959 | 0.9750   |
+| 0.0002        | 4.0   | 3128 | 0.0896          | 0.7942    | 0.8199 | 0.8068 | 0.9767   |
+| 0.0004        | 5.0   | 3910 | 0.1119          | 0.7971    | 0.8201 | 0.8084 | 0.9765   |
+| 0.0004        | 6.0   | 4692 | 0.1192          | 0.7966    | 0.8337 | 0.8147 | 0.9768   |
+| 0.013         | 7.0   | 5474 | 0.1274          | 0.7932    | 0.8266 | 0.8095 | 0.9773   |
+| 0.0236        | 8.0   | 6256 | 0.1419          | 0.7976    | 0.8213 | 0.8093 | 0.9771   |
+| 0.0004        | 9.0   | 7038 | 0.1519          | 0.8004    | 0.8261 | 0.8130 | 0.9772   |
+| 0.0           | 10.0  | 7820 | 0.1528          | 0.7988    | 0.8243 | 0.8114 | 0.9772   |
+
+
+### Framework versions
+
+- Transformers 4.23.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.6.1
+- Tokenizers 0.13.1