modernBERT-large-claim-agent_v3
This model is a fine-tuned version of answerdotai/ModernBERT-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3218
- Accuracy: 0.9397
- Precision: 0.8961
- Recall: 0.8846
- F1: 0.8903
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.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_steps: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3822 | 1.0 | 145 | 0.2593 | 0.8830 | 0.7320 | 0.9103 | 0.8114 |
| 0.1976 | 2.0 | 290 | 0.2381 | 0.9149 | 0.8971 | 0.7821 | 0.8356 |
| 0.0530 | 3.0 | 435 | 0.3218 | 0.9397 | 0.8961 | 0.8846 | 0.8903 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2