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distilbert-base-uncased-finetuned-cola
nediaz/distilbert-base-uncased-finetuned-cola
distilbert-base-uncased-finetuned-cola is a text classification model from nediaz. 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
- May 5, 2025
- Updated
- May 5, 2025
- SHA
- 3456ad22
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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-cola
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: 0.8160
- Matthews Correlation: 0.5344
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH 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 | Matthews Correlation |
|---|---|---|---|---|
| 0.5247 | 1.0 | 535 | 0.4595 | 0.4388 |
| 0.3533 | 2.0 | 1070 | 0.4804 | 0.5280 |
| 0.2399 | 3.0 | 1605 | 0.6338 | 0.4852 |
| 0.1768 | 4.0 | 2140 | 0.7678 | 0.5246 |
| 0.1337 | 5.0 | 2675 | 0.8160 | 0.5344 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- May 5, 2025
- Updated
- May 5, 2025