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distilbert-base-uncased-new-distilled-clinc
adlv/distilbert-base-uncased-new-distilled-clinc
distilbert-base-uncased-new-distilled-clinc is a text classification model from adlv. 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 12, 2024
- Updated
- Oct 13, 2024
- SHA
- 22f826cc
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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-new-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: 0.0911
- 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 |
|---|---|---|---|---|
| 0.9907 | 1.0 | 318 | 0.6136 | 0.7335 |
| 0.4594 | 2.0 | 636 | 0.2760 | 0.8981 |
| 0.242 | 3.0 | 954 | 0.1703 | 0.9287 |
| 0.1634 | 4.0 | 1272 | 0.1335 | 0.9406 |
| 0.131 | 5.0 | 1590 | 0.1184 | 0.9374 |
| 0.1148 | 6.0 | 1908 | 0.1110 | 0.9394 |
| 0.105 | 7.0 | 2226 | 0.1067 | 0.9410 |
| 0.0988 | 8.0 | 2544 | 0.1024 | 0.9439 |
| 0.0944 | 9.0 | 2862 | 0.0995 | 0.9445 |
| 0.0909 | 10.0 | 3180 | 0.0989 | 0.9465 |
| 0.0883 | 11.0 | 3498 | 0.0976 | 0.9471 |
| 0.0862 | 12.0 | 3816 | 0.0972 | 0.9458 |
| 0.0846 | 13.0 | 4134 | 0.0961 | 0.9448 |
| 0.0829 | 14.0 | 4452 | 0.0954 | 0.9458 |
| 0.0818 | 15.0 | 4770 | 0.0948 | 0.9458 |
| 0.0807 | 16.0 | 5088 | 0.0935 | 0.9474 |
| 0.0798 | 17.0 | 5406 | 0.0930 | 0.9461 |
| 0.0789 | 18.0 | 5724 | 0.0936 | 0.9494 |
| 0.0784 | 19.0 | 6042 | 0.0927 | 0.9481 |
| 0.0777 | 20.0 | 6360 | 0.0925 | 0.9474 |
| 0.0773 | 21.0 | 6678 | 0.0931 | 0.9481 |
| 0.0767 | 22.0 | 6996 | 0.0927 | 0.9481 |
| 0.0761 | 23.0 | 7314 | 0.0920 | 0.9490 |
| 0.0759 | 24.0 | 7632 | 0.0914 | 0.9487 |
| 0.0757 | 25.0 | 7950 | 0.0917 | 0.9494 |
| 0.0753 | 26.0 | 8268 | 0.0918 | 0.95 |
| 0.075 | 27.0 | 8586 | 0.0914 | 0.9494 |
| 0.0749 | 28.0 | 8904 | 0.0912 | 0.9490 |
| 0.0746 | 29.0 | 9222 | 0.0911 | 0.9490 |
| 0.0744 | 30.0 | 9540 | 0.0911 | 0.9494 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Oct 12, 2024
- Updated
- Oct 13, 2024