---
library_name: transformers
license: mit
base_model: emilyalsentzer/Bio_ClinicalBERT
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: finetuned_BioClinicalBERT
  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. -->

# finetuned_BioClinicalBERT

This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4147
- F1: 0.9143

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.5879        | 1.0   | 24   | 0.4997          | 0.8767 |
| 0.52          | 2.0   | 48   | 0.4386          | 0.8889 |
| 0.3865        | 3.0   | 72   | 0.4487          | 0.7797 |
| 0.4456        | 4.0   | 96   | 0.5242          | 0.8    |
| 0.2789        | 5.0   | 120  | 0.4147          | 0.9143 |
| 0.2035        | 6.0   | 144  | 0.5301          | 0.8710 |
| 0.124         | 7.0   | 168  | 0.6356          | 0.8923 |
| 0.1422        | 8.0   | 192  | 0.9593          | 0.8308 |
| 0.123         | 9.0   | 216  | 2.0378          | 0.5833 |
| 0.0296        | 10.0  | 240  | 1.1534          | 0.8197 |
| 0.0047        | 11.0  | 264  | 0.6878          | 0.9254 |
| 0.0739        | 12.0  | 288  | 1.2483          | 0.8387 |
| 0.0016        | 13.0  | 312  | 1.9790          | 0.7143 |
| 0.0017        | 14.0  | 336  | 0.9967          | 0.8615 |
| 0.0015        | 15.0  | 360  | 2.0558          | 0.7143 |
| 0.0008        | 16.0  | 384  | 1.2408          | 0.8696 |
| 0.0006        | 17.0  | 408  | 1.6653          | 0.8    |
| 0.0003        | 18.0  | 432  | 1.1586          | 0.875  |
| 0.0002        | 19.0  | 456  | 1.1180          | 0.8955 |
| 0.0002        | 20.0  | 480  | 1.1362          | 0.8955 |
| 0.0002        | 21.0  | 504  | 1.1670          | 0.8955 |
| 0.0002        | 22.0  | 528  | 1.1915          | 0.8955 |
| 0.0002        | 23.0  | 552  | 1.2127          | 0.8955 |
| 0.0002        | 24.0  | 576  | 1.2162          | 0.8955 |
| 0.0002        | 25.0  | 600  | 1.2291          | 0.8955 |
| 0.0002        | 26.0  | 624  | 1.2454          | 0.8955 |
| 0.0002        | 27.0  | 648  | 1.2608          | 0.8955 |
| 0.0002        | 28.0  | 672  | 1.2348          | 0.8923 |
| 0.0002        | 29.0  | 696  | 1.2444          | 0.8923 |
| 0.0001        | 30.0  | 720  | 1.2437          | 0.8923 |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0