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---
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
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