---
base_model: medicalai/ClinicalBERT
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: 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. -->

# ClinicalBERT-medical-text-classification

This model is a fine-tuned version of [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4453
- Accuracy: 0.284
- Precision: 0.1812
- Recall: 0.284
- F1: 0.2132

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.9605        | 1.0   | 250  | 2.9477          | 0.221    | 0.0488    | 0.221  | 0.0800 |
| 2.5952        | 2.0   | 500  | 2.5658          | 0.341    | 0.1400    | 0.341  | 0.1958 |
| 2.5191        | 3.0   | 750  | 2.4897          | 0.355    | 0.1531    | 0.355  | 0.2046 |
| 2.414         | 4.0   | 1000 | 2.5463          | 0.323    | 0.1913    | 0.323  | 0.1902 |
| 2.2946        | 5.0   | 1250 | 2.4793          | 0.347    | 0.1461    | 0.347  | 0.2023 |
| 2.4065        | 6.0   | 1500 | 2.4471          | 0.349    | 0.1684    | 0.349  | 0.2198 |
| 2.3267        | 7.0   | 1750 | 2.4408          | 0.344    | 0.1672    | 0.344  | 0.2193 |
| 2.3173        | 8.0   | 2000 | 2.4214          | 0.358    | 0.1748    | 0.358  | 0.2286 |
| 2.1692        | 9.0   | 2250 | 2.4358          | 0.339    | 0.1638    | 0.339  | 0.2147 |
| 2.029         | 10.0  | 2500 | 2.4074          | 0.338    | 0.1658    | 0.338  | 0.2178 |
| 2.125         | 11.0  | 2750 | 2.3605          | 0.334    | 0.1756    | 0.334  | 0.2239 |
| 1.9541        | 12.0  | 3000 | 2.3997          | 0.326    | 0.1623    | 0.326  | 0.2123 |
| 2.1619        | 13.0  | 3250 | 2.4450          | 0.321    | 0.1765    | 0.321  | 0.2127 |
| 2.101         | 14.0  | 3500 | 2.4453          | 0.284    | 0.1812    | 0.284  | 0.2132 |


### Framework versions

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