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: model
+  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: 0.5537679932260796
+    - name: Recall
+      type: recall
+      value: 0.6312741312741312
+    - name: F1
+      type: f1
+      value: 0.5899864682002707
+    - name: Accuracy
+      type: accuracy
+      value: 0.9586137150414252
+---
+
+<!-- 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. -->
+
+# model
+
+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: 0.2138
+- Precision: 0.5538
+- Recall: 0.6313
+- F1: 0.5900
+- Accuracy: 0.9586
+
+## 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: 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2962        | 1.0   | 679  | 0.1463          | 0.4864    | 0.5010 | 0.4936 | 0.9532   |
+| 0.1321        | 2.0   | 1358 | 0.1482          | 0.4794    | 0.5946 | 0.5308 | 0.9549   |
+| 0.0649        | 3.0   | 2037 | 0.1570          | 0.5307    | 0.6168 | 0.5705 | 0.9577   |
+| 0.0414        | 4.0   | 2716 | 0.1799          | 0.5050    | 0.6390 | 0.5641 | 0.9564   |
+| 0.0316        | 5.0   | 3395 | 0.2138          | 0.5538    | 0.6313 | 0.5900 | 0.9586   |
+
+
+### Framework versions
+
+- Transformers 4.28.1
+- Pytorch 2.0.0+cu118
+- Datasets 2.11.0
+- Tokenizers 0.13.3