yelp_review_classifier
This model is a fine-tuned version of google-bert/bert-base-cased on Yelp/yelp_review_full dataset. It achieves the following results on the evaluation set:
- Loss: 0.7121
- Accuracy: 0.6864
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- 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: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3664 | 0.0985 | 500 | 0.8323 | 0.6359 |
| 0.8124 | 0.1969 | 1000 | 0.7954 | 0.6487 |
| 0.7915 | 0.2954 | 1500 | 0.7846 | 0.6562 |
| 0.7693 | 0.3938 | 2000 | 0.7509 | 0.6699 |
| 0.7591 | 0.4923 | 2500 | 0.7425 | 0.6719 |
| 0.7456 | 0.5907 | 3000 | 0.7323 | 0.6773 |
| 0.744 | 0.6892 | 3500 | 0.7282 | 0.6806 |
| 0.7347 | 0.7876 | 4000 | 0.7181 | 0.6838 |
| 0.7277 | 0.8861 | 4500 | 0.7158 | 0.6841 |
| 0.719 | 0.9845 | 5000 | 0.7121 | 0.6864 |
Framework versions
- Transformers 4.55.4
- Pytorch 2.7.0+gitf717b2a
- Datasets 3.6.0
- Tokenizers 0.21.4