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distilbert-base-uncased-finetuned-cola
ybkim95-mit/distilbert-base-uncased-finetuned-cola
distilbert-base-uncased-finetuned-cola is a text classification model from ybkim95-mit. 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, 2022
- Updated
- Oct 7, 2022
- SHA
- 9de70d73
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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: 0.7784
- Matthews Correlation: 0.5499
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: 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 |
|---|---|---|---|---|
| 0.5248 | 1.0 | 535 | 0.5367 | 0.4142 |
| 0.3488 | 2.0 | 1070 | 0.5116 | 0.5083 |
| 0.2343 | 3.0 | 1605 | 0.5575 | 0.5485 |
| 0.1766 | 4.0 | 2140 | 0.7784 | 0.5499 |
| 0.1238 | 5.0 | 2675 | 0.8351 | 0.5487 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.2
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Oct 7, 2022
- Updated
- Oct 7, 2022