| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: distilbert-base-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: distilbert-prompt-classifier |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # distilbert-prompt-classifier |
|
|
| This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0380 |
| - Accuracy: 0.9916 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - 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: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:------:|:---------------:|:--------:| |
| | 0.0722 | 1.0 | 16935 | 0.0490 | 0.9831 | |
| | 0.0509 | 2.0 | 33870 | 0.0559 | 0.9870 | |
| | 0.0337 | 3.0 | 50805 | 0.0518 | 0.9871 | |
| | 0.0228 | 4.0 | 67740 | 0.0452 | 0.9891 | |
| | 0.0207 | 5.0 | 84675 | 0.0521 | 0.9898 | |
| | 0.0154 | 6.0 | 101610 | 0.0450 | 0.9900 | |
| | 0.0131 | 7.0 | 118545 | 0.0555 | 0.9905 | |
| | 0.0112 | 8.0 | 135480 | 0.0468 | 0.9908 | |
| | 0.0116 | 9.0 | 152415 | 0.0578 | 0.9906 | |
| | 0.0073 | 10.0 | 169350 | 0.0612 | 0.9908 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.2 |
| |
