security_eval
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risk-classification-bert
This model is a fine-tuned version of answerdotai/ModernBERT-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7415
- F1: 0.9452
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: 4
- 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
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 56 | 0.3137 | 0.9669 |
| 0.668 | 2.0 | 112 | 0.3447 | 0.9562 |
| 0.668 | 3.0 | 168 | 0.3255 | 0.9669 |
| 0.3365 | 4.0 | 224 | 0.5453 | 0.9562 |
| 0.3365 | 5.0 | 280 | 0.7415 | 0.9452 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for ashield-ai/risk-classification-bert
Base model
answerdotai/ModernBERT-base