---
library_name: transformers
license: mit
base_model: thomas-sounack/BioClinical-ModernBERT-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: modernbert-en-disease-mask
  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. -->

# modernbert-en-disease-mask

This model is a fine-tuned version of [thomas-sounack/BioClinical-ModernBERT-base](https://huggingface.co/thomas-sounack/BioClinical-ModernBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1581
- Precision: 0.4638
- Recall: 0.6221
- F1: 0.5314

## 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: 32
- seed: 42
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.1519        | 1.0   | 71   | 0.1876          | 0.3822    | 0.4726 | 0.4226 |
| 0.0926        | 2.0   | 142  | 0.1988          | 0.4005    | 0.6547 | 0.4970 |
| 0.0719        | 3.0   | 213  | 0.1581          | 0.4638    | 0.6221 | 0.5314 |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.10.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2