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distilbert-base-uncased-distilled-clinc
Shaurya-Shsin/distilbert-base-uncased-distilled-clinc
distilbert-base-uncased-distilled-clinc is a text classification model from Shaurya-Shsin. 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
- distilbert
- Access
- Public
- Created
- Oct 11, 2024
- Updated
- Oct 17, 2024
- SHA
- c8e49c21
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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. -->
distilbert-base-uncased-distilled-clinc
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2846
- Accuracy: 0.9494
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: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.8274 | 1.0 | 318 | 2.0336 | 0.7442 |
| 1.5283 | 2.0 | 636 | 0.9644 | 0.8735 |
| 0.7339 | 3.0 | 954 | 0.5207 | 0.9219 |
| 0.4104 | 4.0 | 1272 | 0.3852 | 0.9371 |
| 0.2922 | 5.0 | 1590 | 0.3389 | 0.9452 |
| 0.2433 | 6.0 | 1908 | 0.3266 | 0.9423 |
| 0.2211 | 7.0 | 2226 | 0.3079 | 0.9497 |
| 0.208 | 8.0 | 2544 | 0.3068 | 0.9490 |
| 0.2006 | 9.0 | 2862 | 0.3003 | 0.9497 |
| 0.1955 | 10.0 | 3180 | 0.2963 | 0.9503 |
| 0.1917 | 11.0 | 3498 | 0.2938 | 0.95 |
| 0.1885 | 12.0 | 3816 | 0.2913 | 0.9487 |
| 0.1862 | 13.0 | 4134 | 0.2903 | 0.9503 |
| 0.1846 | 14.0 | 4452 | 0.2927 | 0.9474 |
| 0.1829 | 15.0 | 4770 | 0.2927 | 0.9490 |
| 0.1823 | 16.0 | 5088 | 0.2894 | 0.9484 |
| 0.1807 | 17.0 | 5406 | 0.2894 | 0.9455 |
| 0.1795 | 18.0 | 5724 | 0.2884 | 0.9477 |
| 0.1788 | 19.0 | 6042 | 0.2862 | 0.9494 |
| 0.1781 | 20.0 | 6360 | 0.2868 | 0.9494 |
| 0.1775 | 21.0 | 6678 | 0.2871 | 0.9484 |
| 0.1767 | 22.0 | 6996 | 0.2908 | 0.9490 |
| 0.1758 | 23.0 | 7314 | 0.2845 | 0.95 |
| 0.1758 | 24.0 | 7632 | 0.2893 | 0.9497 |
| 0.1756 | 25.0 | 7950 | 0.2855 | 0.9490 |
| 0.175 | 26.0 | 8268 | 0.2867 | 0.9481 |
| 0.1748 | 27.0 | 8586 | 0.2846 | 0.9477 |
| 0.1745 | 28.0 | 8904 | 0.2847 | 0.9490 |
| 0.1742 | 29.0 | 9222 | 0.2842 | 0.9490 |
| 0.1743 | 30.0 | 9540 | 0.2846 | 0.9494 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Oct 11, 2024
- Updated
- Oct 17, 2024