update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+datasets:
+- bc4chemd_ner
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bc4chemd_ner-Bio_ClinicalBERT-finetuned-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: bc4chemd_ner
+      type: bc4chemd_ner
+      args: bc4chemd
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8911526429774604
+    - name: Recall
+      type: recall
+      value: 0.8766669296930482
+    - name: F1
+      type: f1
+      value: 0.8838504375497215
+    - name: Accuracy
+      type: accuracy
+      value: 0.9906009271141061
+---
+
+<!-- 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. -->
+
+# bc4chemd_ner-Bio_ClinicalBERT-finetuned-ner
+
+This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the bc4chemd_ner dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0648
+- Precision: 0.8912
+- Recall: 0.8767
+- F1: 0.8839
+- Accuracy: 0.9906
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0088        | 1.0   | 1918  | 0.0322          | 0.8763    | 0.8506 | 0.8633 | 0.9894   |
+| 0.0079        | 2.0   | 3836  | 0.0375          | 0.8820    | 0.8571 | 0.8694 | 0.9896   |
+| 0.0085        | 3.0   | 5754  | 0.0382          | 0.8671    | 0.8820 | 0.8744 | 0.9900   |
+| 0.0011        | 4.0   | 7672  | 0.0513          | 0.8895    | 0.8520 | 0.8704 | 0.9896   |
+| 0.0016        | 5.0   | 9590  | 0.0489          | 0.8871    | 0.8721 | 0.8795 | 0.9903   |
+| 0.0002        | 6.0   | 11508 | 0.0541          | 0.8906    | 0.8751 | 0.8828 | 0.9904   |
+| 0.0001        | 7.0   | 13426 | 0.0541          | 0.8794    | 0.8828 | 0.8811 | 0.9904   |
+| 0.0001        | 8.0   | 15344 | 0.0590          | 0.8771    | 0.8881 | 0.8825 | 0.9905   |
+| 0.0           | 9.0   | 17262 | 0.0622          | 0.8901    | 0.8797 | 0.8849 | 0.9906   |
+| 0.0058        | 10.0  | 19180 | 0.0648          | 0.8912    | 0.8767 | 0.8839 | 0.9906   |
+
+
+### Framework versions
+
+- Transformers 4.20.1
+- Pytorch 1.12.0+cu113
+- Datasets 2.3.2
+- Tokenizers 0.12.1