modernbert-large_clinc
This model is a fine-tuned version of answerdotai/ModernBERT-large on a CLINC150 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1766
- Accuracy: 0.9619
- F1: 0.9618
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
- lr_scheduler_warmup_steps: 500
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.3612 | 1.0 | 318 | 0.5035 | 0.8745 | 0.8711 |
| 0.15 | 2.0 | 636 | 0.1766 | 0.9619 | 0.9618 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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Model tree for pradervonsky/modernbert-large_clinc
Base model
answerdotai/ModernBERT-large