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yelp_review_classifer
NguyenDuyPhuc/yelp_review_classifer
yelp_review_classifer is a text classification model from NguyenDuyPhuc. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Jul 18, 2025
- Updated
- Sep 21, 2025
- SHA
- 03724956
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
yelp_review_classifer
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8079
- Accuracy: 0.6889
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: 64
- eval_batch_size: 64
- 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: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7629 | 1.0 | 10157 | 0.7076 | 0.6904 |
| 0.6565 | 2.0 | 20314 | 0.6933 | 0.6959 |
| 0.586 | 3.0 | 30471 | 0.7066 | 0.6968 |
| 0.5176 | 4.0 | 40628 | 0.7503 | 0.6931 |
| 0.4616 | 5.0 | 50785 | 0.8079 | 0.6889 |
Framework versions
- Transformers 4.56.2
- Pytorch 2.8.0+cu126
- Datasets 4.1.1
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jul 18, 2025
- Updated
- Sep 21, 2025