distilbert-imdb
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4960
- Accuracy: 0.806
- Precision: 0.7363
- Recall: 0.9385
- F1: 0.8252
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.4227 | 1.0 | 625 | 0.4960 | 0.806 | 0.7363 | 0.9385 | 0.8252 |
| 0.2544 | 2.0 | 1250 | 0.5036 | 0.85 | 0.8225 | 0.8832 | 0.8518 |
| 0.1286 | 3.0 | 1875 | 0.6741 | 0.857 | 0.8350 | 0.8811 | 0.8574 |
Framework versions
- Transformers 5.15.1
- Pytorch 2.11.0+cu128
- Datasets 5.0.1
- Tokenizers 0.22.2