fold_4
This model is a fine-tuned version of answerdotai/ModernBERT-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9750
- F1: 0.8671
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: 32
- 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
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
0.4161 | 1.0 | 300 | 0.3895 | 0.8468 |
0.2737 | 2.0 | 600 | 0.3850 | 0.8483 |
0.1507 | 3.0 | 900 | 0.4366 | 0.8527 |
0.101 | 4.0 | 1200 | 0.4940 | 0.8651 |
0.0613 | 5.0 | 1500 | 0.6864 | 0.8578 |
0.029 | 6.0 | 1800 | 0.7927 | 0.8602 |
0.0263 | 7.0 | 2100 | 0.8139 | 0.8581 |
0.0059 | 8.0 | 2400 | 0.8550 | 0.8669 |
0.0028 | 9.0 | 2700 | 0.9667 | 0.8648 |
0.001 | 10.0 | 3000 | 0.9750 | 0.8671 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0
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Base model
answerdotai/ModernBERT-base