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xlm-roberta-base-swa-noaug
Kuongan/xlm-roberta-base-swa-noaug
xlm-roberta-base-swa-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
- a6b38c54
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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-swa-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: 0.3011
- F1: 0.2057
- Roc Auc: 0.5807
- Accuracy: 0.4828
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 |
|---|---|---|---|---|---|---|
| 0.3287 | 1.0 | 104 | 0.3130 | 0.0 | 0.5 | 0.4465 |
| 0.3207 | 2.0 | 208 | 0.3091 | 0.0 | 0.5 | 0.4465 |
| 0.3054 | 3.0 | 312 | 0.2919 | 0.0 | 0.5 | 0.4465 |
| 0.304 | 4.0 | 416 | 0.3045 | 0.0317 | 0.5076 | 0.4374 |
| 0.2871 | 5.0 | 520 | 0.2893 | 0.0944 | 0.5415 | 0.4537 |
| 0.2803 | 6.0 | 624 | 0.2817 | 0.1061 | 0.5453 | 0.4755 |
| 0.2638 | 7.0 | 728 | 0.2767 | 0.1102 | 0.5394 | 0.4737 |
| 0.2621 | 8.0 | 832 | 0.2788 | 0.1140 | 0.5428 | 0.4719 |
| 0.2458 | 9.0 | 936 | 0.2818 | 0.1656 | 0.5600 | 0.4918 |
| 0.2184 | 10.0 | 1040 | 0.2883 | 0.1822 | 0.5723 | 0.4991 |
| 0.2106 | 11.0 | 1144 | 0.3011 | 0.2057 | 0.5807 | 0.4828 |
| 0.2091 | 12.0 | 1248 | 0.2949 | 0.1744 | 0.5633 | 0.4791 |
| 0.1996 | 13.0 | 1352 | 0.3000 | 0.2039 | 0.5721 | 0.4828 |
| 0.1779 | 14.0 | 1456 | 0.3095 | 0.1888 | 0.5690 | 0.4592 |
| 0.1856 | 15.0 | 1560 | 0.3111 | 0.1941 | 0.5724 | 0.4701 |
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