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xlm-roberta-base-pcm-noaug
Kuongan/xlm-roberta-base-pcm-noaug
xlm-roberta-base-pcm-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
- 2e711fc3
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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-pcm-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: 0.5261
- F1: 0.4912
- Roc Auc: 0.6688
- Accuracy: 0.3065
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 |
|---|---|---|---|---|---|---|
| 0.4984 | 1.0 | 117 | 0.4862 | 0.1155 | 0.5131 | 0.2081 |
| 0.456 | 2.0 | 234 | 0.4323 | 0.2110 | 0.5565 | 0.2145 |
| 0.4207 | 3.0 | 351 | 0.4142 | 0.2856 | 0.5909 | 0.2903 |
| 0.3932 | 4.0 | 468 | 0.4189 | 0.3215 | 0.6145 | 0.2984 |
| 0.3576 | 5.0 | 585 | 0.4417 | 0.3400 | 0.6254 | 0.3048 |
| 0.324 | 6.0 | 702 | 0.4158 | 0.4024 | 0.6332 | 0.3129 |
| 0.3011 | 7.0 | 819 | 0.4176 | 0.4393 | 0.6516 | 0.3016 |
| 0.2675 | 8.0 | 936 | 0.4433 | 0.4546 | 0.6663 | 0.3290 |
| 0.2436 | 9.0 | 1053 | 0.4513 | 0.4435 | 0.6547 | 0.3258 |
| 0.2169 | 10.0 | 1170 | 0.4674 | 0.4624 | 0.6641 | 0.3177 |
| 0.2241 | 11.0 | 1287 | 0.4843 | 0.4706 | 0.6649 | 0.2984 |
| 0.1853 | 12.0 | 1404 | 0.4866 | 0.4646 | 0.6601 | 0.3323 |
| 0.1751 | 13.0 | 1521 | 0.5068 | 0.4555 | 0.6557 | 0.3081 |
| 0.1596 | 14.0 | 1638 | 0.4991 | 0.4640 | 0.6571 | 0.3145 |
| 0.1458 | 15.0 | 1755 | 0.5174 | 0.4784 | 0.6667 | 0.3210 |
| 0.1446 | 16.0 | 1872 | 0.5261 | 0.4912 | 0.6688 | 0.3065 |
| 0.1502 | 17.0 | 1989 | 0.5211 | 0.4876 | 0.6669 | 0.3242 |
| 0.1309 | 18.0 | 2106 | 0.5219 | 0.4823 | 0.6646 | 0.3242 |
| 0.1419 | 19.0 | 2223 | 0.5247 | 0.4767 | 0.6626 | 0.3258 |
| 0.138 | 20.0 | 2340 | 0.5241 | 0.4793 | 0.6631 | 0.3242 |
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