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distilbert-base-uncased-finetuned-cola
Mandy251124/distilbert-base-uncased-finetuned-cola
distilbert-base-uncased-finetuned-cola is a text classification model from Mandy251124. 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
- Dec 24, 2025
- Updated
- Dec 24, 2025
- SHA
- afa1df03
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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: 0.5219
- Matthews Correlation: 0.5396
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: 2.363503685375581e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 11
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|---|---|---|---|---|
| No log | 1.0 | 268 | 0.4773 | 0.4438 |
| 0.446 | 2.0 | 536 | 0.4841 | 0.5244 |
| 0.446 | 3.0 | 804 | 0.5219 | 0.5396 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 2.21.0
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Dec 24, 2025
- Updated
- Dec 24, 2025