deberta_movie_review2
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: 0.4908
- Accuracy: 0.935
- Precision: 0.9307
- Recall: 0.94
- F1: 0.9353
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.1311 | 1.0 | 100 | 0.1920 | 0.92 | 0.9038 | 0.94 | 0.9216 |
| 0.7179 | 2.0 | 200 | 0.2486 | 0.935 | 0.9143 | 0.96 | 0.9366 |
| 0.4583 | 3.0 | 300 | 0.3218 | 0.915 | 0.9368 | 0.89 | 0.9128 |
| 0.3615 | 4.0 | 400 | 0.4874 | 0.905 | 0.9655 | 0.84 | 0.8984 |
| 0.0714 | 5.0 | 500 | 0.3900 | 0.92 | 0.9468 | 0.89 | 0.9175 |
| 0.0088 | 6.0 | 600 | 0.4211 | 0.94 | 0.9314 | 0.95 | 0.9406 |
| 0.0087 | 7.0 | 700 | 0.4608 | 0.935 | 0.9143 | 0.96 | 0.9366 |
| 0.0007 | 8.0 | 800 | 0.4907 | 0.935 | 0.9307 | 0.94 | 0.9353 |
| 0.0497 | 9.0 | 900 | 0.4853 | 0.93 | 0.93 | 0.93 | 0.93 |
| 0.0006 | 10.0 | 1000 | 0.4908 | 0.935 | 0.9307 | 0.94 | 0.9353 |
Framework versions
- Transformers 5.13.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2