metadata
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-v1
results: []
modernbert-en-disease-v1
This model is a fine-tuned version of thomas-sounack/BioClinical-ModernBERT-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1537
- Precision: 0.4896
- Recall: 0.6376
- F1: 0.5539
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 |
|---|---|---|---|---|---|---|
| 0.1459 | 1.0 | 71 | 0.1773 | 0.4080 | 0.5263 | 0.4596 |
| 0.0925 | 2.0 | 142 | 0.1971 | 0.4175 | 0.6651 | 0.5130 |
| 0.0701 | 3.0 | 213 | 0.1537 | 0.4896 | 0.6376 | 0.5539 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.10.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2