update model card README.md

README.md

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+---
+tags:
+- generated_from_trainer
+datasets:
+- conll2003
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: BioBERT-finetuned-ner-conll2003
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2003
+      type: conll2003
+      config: conll2003
+      split: validation
+      args: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8195537004334564
+    - name: Recall
+      type: recall
+      value: 0.8591383372601817
+    - name: F1
+      type: f1
+      value: 0.8388793032618519
+    - name: Accuracy
+      type: accuracy
+      value: 0.9667691125624279
+---
+
+<!-- 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-finetuned-ner-conll2003
+
+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 conll2003 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1099
+- Precision: 0.8196
+- Recall: 0.8591
+- F1: 0.8389
+- Accuracy: 0.9668
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1335        | 1.0   | 1756 | 0.1099          | 0.8196    | 0.8591 | 0.8389 | 0.9668   |
+
+
+### Framework versions
+
+- Transformers 4.29.2
+- Pytorch 2.0.0+cu118
+- Datasets 2.12.0
+- Tokenizers 0.13.3