metadata
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: []
distilbert-prompt-classifier
This model is a fine-tuned version of 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