customer_support_model
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0004
- Accuracy: 0.9999
- F1 Score: 0.9999
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: 8
- eval_batch_size: 8
- 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: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
|---|---|---|---|---|---|
| 0.0261 | 0.4 | 1000 | 0.0186 | 0.996 | 0.9960 |
| 0.0410 | 0.8 | 2000 | 0.0142 | 0.996 | 0.9960 |
| 0.0015 | 1.2 | 3000 | 0.0031 | 0.9993 | 0.9993 |
| 0.0043 | 1.6 | 4000 | 0.0017 | 0.9997 | 0.9997 |
| 0.0004 | 2.0 | 5000 | 0.0004 | 0.9999 | 0.9999 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2