modernbert_base_clinc_oos_distilled
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: 0.3609
- Accuracy: 0.9574
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: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|
| 4.3857 | 1.0 | 477 | 0.9263 | 0.9194 |
| 0.3661 | 2.0 | 954 | 0.4845 | 0.9468 |
| 0.0924 | 3.0 | 1431 | 0.3885 | 0.9552 |
| 0.0435 | 4.0 | 1908 | 0.3743 | 0.9535 |
| 0.031 | 5.0 | 2385 | 0.3609 | 0.9574 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1