review_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: 0.1539
- Accuracy: 0.9792
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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.083 | 1.0 | 2022 | 0.1911 | 0.9520 |
| 0.0381 | 2.0 | 4044 | 0.1443 | 0.9677 |
| 0.0208 | 3.0 | 6066 | 0.0948 | 0.9781 |
| 0.0054 | 4.0 | 8088 | 0.1651 | 0.9755 |
| 0.0003 | 5.0 | 10110 | 0.1539 | 0.9792 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.21.0
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Model tree for jacobea/review_classifier_amazon
Base model
distilbert/distilbert-base-uncased