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distilbert-base-uncased-finetuned-clinc
kkt4828/distilbert-base-uncased-finetuned-clinc
distilbert-base-uncased-finetuned-clinc is a text classification model from kkt4828. 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 7, 2023
- Updated
- Oct 7, 2023
- SHA
- 401f13b7
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Base models
Datasets
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 the clinc_oos dataset. It achieves the following results on the evaluation set:
- Loss: 0.4448
- Accuracy: 0.9352
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 477 | 2.7396 | 0.7597 |
| 3.9584 | 2.0 | 954 | 1.2422 | 0.8842 |
| 1.8774 | 3.0 | 1431 | 0.6816 | 0.9206 |
| 0.8644 | 4.0 | 1908 | 0.4935 | 0.9306 |
| 0.4947 | 5.0 | 2385 | 0.4448 | 0.9352 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Oct 7, 2023
- Updated
- Oct 7, 2023