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kevin-junior-sentiment-roberta-es-2025-II
kevnjordn/kevin-junior-sentiment-roberta-es-2025-II
kevin-junior-sentiment-roberta-es-2025-II is a text classification model from kevnjordn. 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
- Nov 19, 2025
- Updated
- Nov 19, 2025
- SHA
- ccebb78a
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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. -->
sentiment-roberta-es-2025-II
This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1261
- F1 Macro: 0.6714
- F1 Weighted: 0.6733
- Precision Macro: 0.6697
- Recall Macro: 0.6751
- Accuracy: 0.6770
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | Precision Macro | Recall Macro | Accuracy |
|---|---|---|---|---|---|---|---|---|
| 1.0981 | 1.0 | 241 | 1.0390 | 0.4469 | 0.4554 | 0.3927 | 0.5369 | 0.5588 |
| 0.8394 | 2.0 | 482 | 0.7404 | 0.6780 | 0.6832 | 0.6829 | 0.6750 | 0.6826 |
| 0.6608 | 3.0 | 723 | 0.8494 | 0.6603 | 0.6635 | 0.6645 | 0.6762 | 0.6722 |
| 0.5192 | 4.0 | 964 | 0.7772 | 0.6869 | 0.6891 | 0.6889 | 0.6853 | 0.6889 |
| 0.4056 | 5.0 | 1205 | 0.8797 | 0.6879 | 0.6888 | 0.6969 | 0.6869 | 0.6847 |
| 0.327 | 6.0 | 1446 | 1.0902 | 0.6962 | 0.6998 | 0.6960 | 0.6980 | 0.7024 |
| 0.2616 | 7.0 | 1687 | 1.0482 | 0.6899 | 0.6923 | 0.6940 | 0.6874 | 0.6899 |
| 0.1981 | 8.0 | 1928 | 1.2889 | 0.6818 | 0.6834 | 0.6824 | 0.6897 | 0.6847 |
| 0.1452 | 9.0 | 2169 | 1.4574 | 0.6852 | 0.6876 | 0.6845 | 0.6874 | 0.6868 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Nov 19, 2025
- Updated
- Nov 19, 2025