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afro-xlmr-base-sun-noaug
Kuongan/afro-xlmr-base-sun-noaug
afro-xlmr-base-sun-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
- 887f5633
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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. -->
afro-xlmr-base-sun-noaug
This model is a fine-tuned version of Davlan/afro-xlmr-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3348
- F1: 0.3427
- Roc Auc: 0.6065
- Accuracy: 0.4925
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 |
|---|---|---|---|---|---|---|
| 0.6846 | 1.0 | 29 | 0.5843 | 0.1405 | 0.5 | 0.4472 |
| 0.5818 | 2.0 | 58 | 0.4117 | 0.1405 | 0.5 | 0.4472 |
| 0.4152 | 3.0 | 87 | 0.4075 | 0.1405 | 0.5 | 0.4472 |
| 0.4037 | 4.0 | 116 | 0.3993 | 0.1405 | 0.5 | 0.4472 |
| 0.3772 | 5.0 | 145 | 0.3553 | 0.2579 | 0.5785 | 0.4874 |
| 0.3503 | 6.0 | 174 | 0.3497 | 0.2511 | 0.5788 | 0.4874 |
| 0.3288 | 7.0 | 203 | 0.3626 | 0.2516 | 0.5726 | 0.4925 |
| 0.331 | 8.0 | 232 | 0.3551 | 0.2532 | 0.5978 | 0.4523 |
| 0.2938 | 9.0 | 261 | 0.3443 | 0.2647 | 0.5840 | 0.4925 |
| 0.2872 | 10.0 | 290 | 0.3438 | 0.2757 | 0.5911 | 0.4724 |
| 0.2911 | 11.0 | 319 | 0.3444 | 0.2925 | 0.5987 | 0.4623 |
| 0.2601 | 12.0 | 348 | 0.3431 | 0.3391 | 0.6240 | 0.4724 |
| 0.274 | 13.0 | 377 | 0.3499 | 0.2773 | 0.5863 | 0.4975 |
| 0.2375 | 14.0 | 406 | 0.3364 | 0.3225 | 0.6114 | 0.5126 |
| 0.2508 | 15.0 | 435 | 0.3301 | 0.3177 | 0.6042 | 0.4874 |
| 0.2368 | 16.0 | 464 | 0.3348 | 0.3427 | 0.6065 | 0.4925 |
| 0.243 | 17.0 | 493 | 0.3312 | 0.3180 | 0.6058 | 0.4975 |
| 0.237 | 18.0 | 522 | 0.3319 | 0.3197 | 0.6053 | 0.4975 |
| 0.2217 | 19.0 | 551 | 0.3327 | 0.3281 | 0.6056 | 0.4975 |
| 0.2295 | 20.0 | 580 | 0.3328 | 0.3281 | 0.6056 | 0.4975 |
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