modernBert-QA-classifier-v3
This model is a fine-tuned version of ModernBERT-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9225
- F1: 0.8058
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: 48
- eval_batch_size: 48
- 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
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.9755 | 1.0 | 271 | 0.9539 | 0.8016 |
| 0.9462 | 2.0 | 542 | 0.9327 | 0.8037 |
| 0.9241 | 3.0 | 813 | 0.9254 | 0.8049 |
| 0.9105 | 4.0 | 1084 | 0.9223 | 0.8060 |
| 0.9032 | 5.0 | 1355 | 0.9225 | 0.8058 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.8.0+cu126
- Datasets 4.5.0
- Tokenizers 0.22.2
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