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xlm-roberta-base-deu-noaug
Kuongan/xlm-roberta-base-deu-noaug
xlm-roberta-base-deu-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 25, 2025
- Updated
- Feb 25, 2025
- SHA
- f4adb4b4
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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-deu-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: 0.3548
- F1: 0.5884
- Roc Auc: 0.7436
- Accuracy: 0.465
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 |
|---|---|---|---|---|---|---|
| 0.467 | 1.0 | 82 | 0.4518 | 0.0 | 0.5 | 0.245 |
| 0.4085 | 2.0 | 164 | 0.4077 | 0.1981 | 0.5674 | 0.305 |
| 0.3667 | 3.0 | 246 | 0.3736 | 0.3240 | 0.6140 | 0.35 |
| 0.342 | 4.0 | 328 | 0.3439 | 0.4458 | 0.6762 | 0.445 |
| 0.2937 | 5.0 | 410 | 0.3457 | 0.4554 | 0.6856 | 0.465 |
| 0.2733 | 6.0 | 492 | 0.3522 | 0.4492 | 0.6843 | 0.47 |
| 0.2395 | 7.0 | 574 | 0.3377 | 0.4643 | 0.6935 | 0.49 |
| 0.2095 | 8.0 | 656 | 0.3503 | 0.4620 | 0.6913 | 0.465 |
| 0.1919 | 9.0 | 738 | 0.3611 | 0.4368 | 0.6751 | 0.445 |
| 0.1745 | 10.0 | 820 | 0.3578 | 0.4748 | 0.6944 | 0.47 |
| 0.1524 | 11.0 | 902 | 0.3517 | 0.5117 | 0.7096 | 0.48 |
| 0.1371 | 12.0 | 984 | 0.3549 | 0.5771 | 0.7363 | 0.48 |
| 0.1306 | 13.0 | 1066 | 0.3514 | 0.5706 | 0.7287 | 0.45 |
| 0.1184 | 14.0 | 1148 | 0.3548 | 0.5884 | 0.7436 | 0.465 |
| 0.1087 | 15.0 | 1230 | 0.3563 | 0.5652 | 0.7270 | 0.45 |
| 0.0987 | 16.0 | 1312 | 0.3584 | 0.5845 | 0.7417 | 0.465 |
| 0.1011 | 17.0 | 1394 | 0.3575 | 0.5812 | 0.7391 | 0.485 |
| 0.0957 | 18.0 | 1476 | 0.3622 | 0.5835 | 0.7388 | 0.465 |
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 25, 2025
- Updated
- Feb 25, 2025