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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
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