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CoLA-FULL_FT-seed62
ekiprop/CoLA-FULL_FT-seed62
CoLA-FULL_FT-seed62 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
- 4cf36de3
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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-seed62
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5303
- Matthews Correlation: 0.6235
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 |
|---|---|---|---|---|
| 0.6033 | 0.1866 | 50 | 0.5212 | 0.4018 |
| 0.4995 | 0.3731 | 100 | 0.4667 | 0.4906 |
| 0.464 | 0.5597 | 150 | 0.5680 | 0.4581 |
| 0.4642 | 0.7463 | 200 | 0.4341 | 0.5287 |
| 0.418 | 0.9328 | 250 | 0.4778 | 0.5577 |
| 0.3661 | 1.1194 | 300 | 0.5164 | 0.5701 |
| 0.3306 | 1.3060 | 350 | 0.4746 | 0.5830 |
| 0.3195 | 1.4925 | 400 | 0.4664 | 0.5935 |
| 0.335 | 1.6791 | 450 | 0.4475 | 0.5577 |
| 0.2958 | 1.8657 | 500 | 0.4984 | 0.5585 |
| 0.2923 | 2.0522 | 550 | 0.4731 | 0.5856 |
| 0.1981 | 2.2388 | 600 | 0.4729 | 0.5830 |
| 0.2131 | 2.4254 | 650 | 0.4961 | 0.5856 |
| 0.2161 | 2.6119 | 700 | 0.4745 | 0.5943 |
| 0.1899 | 2.7985 | 750 | 0.5303 | 0.6235 |
| 0.1989 | 2.9851 | 800 | 0.5088 | 0.5885 |
| 0.1385 | 3.1716 | 850 | 0.6206 | 0.5957 |
| 0.139 | 3.3582 | 900 | 0.5112 | 0.6092 |
| 0.1472 | 3.5448 | 950 | 0.7113 | 0.5505 |
| 0.1374 | 3.7313 | 1000 | 0.5630 | 0.6184 |
| 0.1471 | 3.9179 | 1050 | 0.5556 | 0.6194 |
| 0.1251 | 4.1045 | 1100 | 0.5938 | 0.6148 |
| 0.0809 | 4.2910 | 1150 | 0.7042 | 0.6123 |
| 0.1067 | 4.4776 | 1200 | 0.7403 | 0.6113 |
| 0.1007 | 4.6642 | 1250 | 0.7907 | 0.6058 |
| 0.0881 | 4.8507 | 1300 | 0.7846 | 0.6010 |
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