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distilbert-base-uncased-finetuned-cola
suey2580/distilbert-base-uncased-finetuned-cola
distilbert-base-uncased-finetuned-cola is a text classification model from suey2580. 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
- Apr 6, 2022
- Updated
- Aug 31, 2022
- SHA
- bac46396
Try a prompt
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-cola
This model is a fine-tuned version of distilbert-base-uncased on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 1.0766
- Matthews Correlation: 0.5238
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: 2.403175733231667e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 33
- 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 | Matthews Correlation |
|---|---|---|---|---|
| 0.4954 | 1.0 | 1069 | 0.4770 | 0.4589 |
| 0.3627 | 2.0 | 2138 | 0.5464 | 0.4998 |
| 0.2576 | 3.0 | 3207 | 0.8439 | 0.4933 |
| 0.1488 | 4.0 | 4276 | 1.0184 | 0.5035 |
| 0.1031 | 5.0 | 5345 | 1.0766 | 0.5238 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Apr 6, 2022
- Updated
- Aug 31, 2022