update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- ncbi_disease
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: BIO_GPT_NER_FINETUNED_C
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: ncbi_disease
+      type: ncbi_disease
+      config: ncbi_disease
+      split: validation
+      args: ncbi_disease
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.44176706827309237
+    - name: Recall
+      type: recall
+      value: 0.5583756345177665
+    - name: F1
+      type: f1
+      value: 0.4932735426008968
+    - name: Accuracy
+      type: accuracy
+      value: 0.958054734877935
+---
+
+<!-- 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. -->
+
+# BIO_GPT_NER_FINETUNED_C
+
+This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on the ncbi_disease dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1466
+- Precision: 0.4418
+- Recall: 0.5584
+- F1: 0.4933
+- Accuracy: 0.9581
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2989        | 1.0   | 680  | 0.1687          | 0.3350    | 0.4226 | 0.3737 | 0.9474   |
+| 0.1764        | 2.0   | 1360 | 0.1425          | 0.4289    | 0.5241 | 0.4717 | 0.9560   |
+| 0.0942        | 3.0   | 2040 | 0.1466          | 0.4418    | 0.5584 | 0.4933 | 0.9581   |
+
+
+### Framework versions
+
+- Transformers 4.28.0
+- Pytorch 2.0.0+cu118
+- Datasets 2.11.0
+- Tokenizers 0.13.3