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CoLA-FULL_FT-seed42
ekiprop/CoLA-FULL_FT-seed42
CoLA-FULL_FT-seed42 is a text classification model from ekiprop. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Aug 7, 2025
- Updated
- Aug 7, 2025
- SHA
- deb31988
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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. -->
CoLA-FULL_FT-seed42
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4992
- Matthews Correlation: 0.6439
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 |
|---|---|---|---|---|
| 0.6117 | 0.1866 | 50 | 0.5761 | 0.1545 |
| 0.4972 | 0.3731 | 100 | 0.4592 | 0.5005 |
| 0.4568 | 0.5597 | 150 | 0.5749 | 0.4608 |
| 0.4566 | 0.7463 | 200 | 0.5009 | 0.4754 |
| 0.4317 | 0.9328 | 250 | 0.5274 | 0.5403 |
| 0.3731 | 1.1194 | 300 | 0.4489 | 0.5763 |
| 0.3306 | 1.3060 | 350 | 0.4648 | 0.5829 |
| 0.3219 | 1.4925 | 400 | 0.4380 | 0.5830 |
| 0.3188 | 1.6791 | 450 | 0.4803 | 0.5522 |
| 0.2994 | 1.8657 | 500 | 0.4554 | 0.5606 |
| 0.2774 | 2.0522 | 550 | 0.4945 | 0.5933 |
| 0.1763 | 2.2388 | 600 | 0.5136 | 0.6016 |
| 0.197 | 2.4254 | 650 | 0.5140 | 0.5911 |
| 0.1964 | 2.6119 | 700 | 0.5161 | 0.5965 |
| 0.1899 | 2.7985 | 750 | 0.4992 | 0.6439 |
| 0.2096 | 2.9851 | 800 | 0.5082 | 0.6132 |
| 0.1478 | 3.1716 | 850 | 0.5955 | 0.6311 |
| 0.1216 | 3.3582 | 900 | 0.5980 | 0.6222 |
| 0.1154 | 3.5448 | 950 | 0.7706 | 0.5727 |
| 0.1038 | 3.7313 | 1000 | 0.6240 | 0.6192 |
| 0.126 | 3.9179 | 1050 | 0.6273 | 0.6176 |
| 0.1175 | 4.1045 | 1100 | 0.6762 | 0.6108 |
| 0.0859 | 4.2910 | 1150 | 0.7149 | 0.5956 |
| 0.0888 | 4.4776 | 1200 | 0.7084 | 0.5982 |
| 0.0921 | 4.6642 | 1250 | 0.7261 | 0.5981 |
| 0.0632 | 4.8507 | 1300 | 0.7419 | 0.6008 |
Framework versions
- Transformers 4.54.1
- Pytorch 2.5.1+cu121
- Datasets 4.0.0
- Tokenizers 0.21.4
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Aug 7, 2025
- Updated
- Aug 7, 2025