---
license: mit
base_model: emilyalsentzer/Bio_ClinicalBERT
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Bio_ClinicalBERT-medical-text-classification
  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. -->

# Bio_ClinicalBERT-medical-text-classification

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: 1.9963
- Accuracy: 0.221
- Precision: 0.1982
- Recall: 0.221
- F1: 0.2013

## 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: 5e-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
- lr_scheduler_warmup_steps: 500
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.4889        | 1.0   | 250  | 2.5603          | 0.353    | 0.1678    | 0.353  | 0.2178 |
| 1.885         | 2.0   | 500  | 2.0021          | 0.371    | 0.2706    | 0.371  | 0.2725 |
| 1.7769        | 3.0   | 750  | 1.8414          | 0.318    | 0.2762    | 0.318  | 0.2822 |
| 1.4955        | 4.0   | 1000 | 1.7687          | 0.315    | 0.2943    | 0.315  | 0.2870 |
| 1.3151        | 5.0   | 1250 | 1.8651          | 0.315    | 0.2527    | 0.315  | 0.2723 |
| 1.235         | 6.0   | 1500 | 1.9358          | 0.254    | 0.2298    | 0.254  | 0.2354 |
| 1.2697        | 7.0   | 1750 | 1.9963          | 0.221    | 0.1982    | 0.221  | 0.2013 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2