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bert-base-multilingual-uncased-yelp_review_full
pbwt/bert-base-multilingual-uncased-yelp_review_full
bert-base-multilingual-uncased-yelp_review_full is a text classification model from pbwt. 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.
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
- Sep 15, 2022
- Updated
- Sep 15, 2022
- SHA
- e7399cd0
Try a prompt
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
pbwt/bert-base-multilingual-uncased-yelp_review_full
This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0019
- Train Sparse Categorical Accuracy: 1.0
- Validation Loss: 0.0011
- Validation Sparse Categorical Accuracy: 1.0
- Epoch: 2
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:
- optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
|---|---|---|---|---|
| 0.1465 | 0.9730 | 0.0034 | 1.0 | 0 |
| 0.0033 | 1.0 | 0.0018 | 1.0 | 1 |
| 0.0019 | 1.0 | 0.0011 | 1.0 | 2 |
Framework versions
- Transformers 4.18.0
- TensorFlow 2.6.2
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Sep 15, 2022
- Updated
- Sep 15, 2022