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xlm-roberta-base-orm-noaug
Kuongan/xlm-roberta-base-orm-noaug
xlm-roberta-base-orm-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 26, 2025
- Updated
- Feb 26, 2025
- SHA
- 05277160
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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-orm-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: 0.3340
- F1: 0.4468
- Roc Auc: 0.6765
- Accuracy: 0.5226
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 |
|---|---|---|---|---|---|---|
| 0.3622 | 1.0 | 108 | 0.3550 | 0.0 | 0.5 | 0.2369 |
| 0.3379 | 2.0 | 216 | 0.3358 | 0.0942 | 0.5309 | 0.3502 |
| 0.3103 | 3.0 | 324 | 0.3205 | 0.1286 | 0.5500 | 0.4146 |
| 0.2932 | 4.0 | 432 | 0.3268 | 0.1689 | 0.5622 | 0.4303 |
| 0.2732 | 5.0 | 540 | 0.3086 | 0.1758 | 0.5631 | 0.4355 |
| 0.2489 | 6.0 | 648 | 0.3074 | 0.2167 | 0.5734 | 0.4408 |
| 0.2428 | 7.0 | 756 | 0.2987 | 0.2273 | 0.5803 | 0.4634 |
| 0.22 | 8.0 | 864 | 0.2971 | 0.2467 | 0.5888 | 0.4808 |
| 0.1866 | 9.0 | 972 | 0.3061 | 0.3799 | 0.6492 | 0.5105 |
| 0.1667 | 10.0 | 1080 | 0.3213 | 0.3645 | 0.6397 | 0.5035 |
| 0.1628 | 11.0 | 1188 | 0.3132 | 0.3835 | 0.6539 | 0.5105 |
| 0.1509 | 12.0 | 1296 | 0.3225 | 0.3915 | 0.6547 | 0.5052 |
| 0.135 | 13.0 | 1404 | 0.3189 | 0.4136 | 0.6634 | 0.5261 |
| 0.1434 | 14.0 | 1512 | 0.3221 | 0.3949 | 0.6541 | 0.5157 |
| 0.1253 | 15.0 | 1620 | 0.3331 | 0.4210 | 0.6658 | 0.5105 |
| 0.13 | 16.0 | 1728 | 0.3298 | 0.4164 | 0.6610 | 0.5139 |
| 0.1178 | 17.0 | 1836 | 0.3305 | 0.4163 | 0.6621 | 0.5174 |
| 0.1148 | 18.0 | 1944 | 0.3340 | 0.4468 | 0.6765 | 0.5226 |
| 0.1087 | 19.0 | 2052 | 0.3357 | 0.4378 | 0.6725 | 0.5209 |
| 0.1136 | 20.0 | 2160 | 0.3354 | 0.4399 | 0.6736 | 0.5226 |
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 26, 2025
- Updated
- Feb 26, 2025