modernbert-clinc
This model is a fine-tuned version of answerdotai/ModernBERT-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5574
- Accuracy: 0.8953
- F1: 0.8899
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: 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 | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 313 | 0.6196 | 0.8673 | 0.8591 |
| 0.6312 | 2.0 | 626 | 0.6403 | 0.8785 | 0.8717 |
| 0.6312 | 3.0 | 939 | 0.5658 | 0.8925 | 0.8877 |
| 0.047 | 4.0 | 1252 | 0.5597 | 0.8938 | 0.8886 |
| 0.0065 | 5.0 | 1565 | 0.5574 | 0.8953 | 0.8899 |
Framework versions
- Transformers 4.55.4
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4