---
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-masked-50-10epochs-v1
  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-masked-50-10epochs-v1

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: 0.2509
- Precision: 0.6313
- Recall: 0.6762
- F1: 0.6530

## 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: 8
- eval_batch_size: 16
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.1581        | 1.0   | 142  | 0.1510          | 0.5315    | 0.5127 | 0.5220 |
| 0.111         | 2.0   | 284  | 0.1111          | 0.6396    | 0.6706 | 0.6548 |
| 0.0796        | 3.0   | 426  | 0.1118          | 0.6527    | 0.6647 | 0.6587 |
| 0.0606        | 4.0   | 568  | 0.1195          | 0.6464    | 0.7228 | 0.6824 |
| 0.0396        | 5.0   | 710  | 0.1538          | 0.6654    | 0.6714 | 0.6684 |
| 0.0179        | 6.0   | 852  | 0.1918          | 0.6476    | 0.6587 | 0.6531 |
| 0.0078        | 7.0   | 994  | 0.1946          | 0.6375    | 0.6961 | 0.6655 |
| 0.0054        | 8.0   | 1136 | 0.2340          | 0.6321    | 0.6794 | 0.6549 |
| 0.0021        | 9.0   | 1278 | 0.2475          | 0.6317    | 0.6782 | 0.6541 |
| 0.0019        | 10.0  | 1420 | 0.2509          | 0.6313    | 0.6762 | 0.6530 |


### Framework versions

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