---
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