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xlm-roberta-base-yor-noaug
Kuongan/xlm-roberta-base-yor-noaug
xlm-roberta-base-yor-noaug is a text classification model from Kuongan. 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
- xlm-roberta
- Access
- Public
- Created
- Feb 27, 2025
- Updated
- Feb 27, 2025
- SHA
- a4259506
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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. -->
xlm-roberta-base-yor-noaug
This model is a fine-tuned version of xlm-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2598
- F1: 0.1897
- Roc Auc: 0.5687
- Accuracy: 0.5815
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.306 | 1.0 | 94 | 0.2789 | 0.0 | 0.5 | 0.4748 |
| 0.2912 | 2.0 | 188 | 0.2793 | 0.0 | 0.5 | 0.4748 |
| 0.2806 | 3.0 | 282 | 0.2786 | 0.0 | 0.5 | 0.4748 |
| 0.2821 | 4.0 | 376 | 0.2783 | 0.0 | 0.5 | 0.4748 |
| 0.2631 | 5.0 | 470 | 0.2674 | 0.0670 | 0.5193 | 0.5151 |
| 0.2622 | 6.0 | 564 | 0.2577 | 0.0963 | 0.5344 | 0.5392 |
| 0.2509 | 7.0 | 658 | 0.2567 | 0.0984 | 0.5361 | 0.5453 |
| 0.2416 | 8.0 | 752 | 0.2507 | 0.1441 | 0.5512 | 0.5775 |
| 0.2218 | 9.0 | 846 | 0.2514 | 0.1693 | 0.5608 | 0.5755 |
| 0.2216 | 10.0 | 940 | 0.2458 | 0.1722 | 0.5606 | 0.5734 |
| 0.1995 | 11.0 | 1034 | 0.2493 | 0.1787 | 0.5648 | 0.5875 |
| 0.2041 | 12.0 | 1128 | 0.2564 | 0.1872 | 0.5681 | 0.5875 |
| 0.1811 | 13.0 | 1222 | 0.2598 | 0.1897 | 0.5687 | 0.5815 |
| 0.1774 | 14.0 | 1316 | 0.2608 | 0.1777 | 0.5666 | 0.5875 |
| 0.1637 | 15.0 | 1410 | 0.2606 | 0.1894 | 0.5653 | 0.5714 |
| 0.1665 | 16.0 | 1504 | 0.2669 | 0.1890 | 0.5696 | 0.5855 |
| 0.1618 | 17.0 | 1598 | 0.2655 | 0.1834 | 0.5672 | 0.5775 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Feb 27, 2025
- Updated
- Feb 27, 2025