update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: ADE-Bio_ClinicalBERT-NER
+  results: []
+---
+
+<!-- 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. -->
+
+# ADE-Bio_ClinicalBERT-NER
+
+This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1926
+- Precision: 0.7830
+- Recall: 0.8811
+- F1: 0.8291
+- Accuracy: 0.9437
+
+## 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: 1e-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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2389        | 1.0   | 201  | 0.2100          | 0.7155    | 0.8292 | 0.7681 | 0.9263   |
+| 0.0648        | 2.0   | 402  | 0.1849          | 0.7716    | 0.8711 | 0.8183 | 0.9392   |
+| 0.2825        | 3.0   | 603  | 0.1856          | 0.7834    | 0.8788 | 0.8284 | 0.9422   |
+| 0.199         | 4.0   | 804  | 0.1875          | 0.7796    | 0.8781 | 0.8259 | 0.9430   |
+| 0.0404        | 5.0   | 1005 | 0.1926          | 0.7830    | 0.8811 | 0.8291 | 0.9437   |
+
+
+### Framework versions
+
+- Transformers 4.21.0
+- Pytorch 1.12.0+cu113
+- Datasets 2.4.0
+- Tokenizers 0.12.1