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fintuned-bert-disfluency
kapilchauhan/fintuned-bert-disfluency
fintuned-bert-disfluency is a text classification model from kapilchauhan. 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 14, 2022
- Updated
- Dec 29, 2022
- SHA
- 8456642b
Try a prompt
Datasets
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. -->
fintuned-bert-disfluency
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.0814
- Train Sparse Categorical Accuracy: 0.9795
- Validation Loss: 0.0816
- Validation Sparse Categorical Accuracy: 0.9795
- 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 |
|---|---|---|---|---|
| 0.1105 | 0.9694 | 0.0821 | 0.9800 | 0 |
| 0.0942 | 0.9759 | 0.0987 | 0.9765 | 1 |
| 0.0814 | 0.9795 | 0.0816 | 0.9795 | 2 |
Framework versions
- Transformers 4.21.3
- TensorFlow 2.8.2
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Sep 14, 2022
- Updated
- Dec 29, 2022