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distilbert-base-uncased-finetuned-clinc
TinyTank/distilbert-base-uncased-finetuned-clinc
distilbert-base-uncased-finetuned-clinc is a text classification model from TinyTank. 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
- Sep 4, 2026
- Updated
- Sep 9, 2026
- SHA
- 9c63ed9e
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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-finetuned-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: 1.7902
- Accuracy: 0.8674
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: 96
- eval_batch_size: 96
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 4.6193 | 1.0 | 159 | 3.9833 | 0.6155 |
| 3.5281 | 2.0 | 318 | 2.9555 | 0.7819 |
| 2.6834 | 3.0 | 477 | 2.2748 | 0.8397 |
| 2.1539 | 4.0 | 636 | 1.9053 | 0.8610 |
| 1.905 | 5.0 | 795 | 1.7902 | 0.8674 |
Framework versions
- Transformers 4.57.6
- Pytorch 2.13.0+cu132
- Datasets 5.0.1
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Sep 4, 2026
- Updated
- Sep 9, 2026