ModernBERT-distil-clinc-oos
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: 0.2192
- Accuracy: 0.9490
- F1: 0.9484
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 | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 318 | 0.4494 | 0.8948 | 0.8919 |
| 1.2053 | 2.0 | 636 | 0.2855 | 0.9294 | 0.9283 |
| 1.2053 | 3.0 | 954 | 0.2339 | 0.9419 | 0.9412 |
| 0.0545 | 4.0 | 1272 | 0.2218 | 0.9458 | 0.9451 |
| 0.0057 | 5.0 | 1590 | 0.2192 | 0.9490 | 0.9484 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.3.0
- Tokenizers 0.22.1
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Model tree for Marcus-KO/ModernBERT-distil-clinc-oos
Base model
answerdotai/ModernBERT-base