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kevin-junior-sentiment-roberta-es-2025-II
JordnK/kevin-junior-sentiment-roberta-es-2025-II
kevin-junior-sentiment-roberta-es-2025-II is a text classification model from JordnK. 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
- f5048df5
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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: 1.1089
- F1 Macro: 0.6660
- F1 Weighted: 0.6679
- Precision Macro: 0.6635
- Recall Macro: 0.6708
- Accuracy: 0.6717
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 |
|---|---|---|---|---|---|---|---|---|
| 1.0923 | 1.0 | 241 | 1.0461 | 0.4237 | 0.4345 | 0.4794 | 0.4653 | 0.4870 |
| 0.9618 | 2.0 | 482 | 0.8033 | 0.6533 | 0.6596 | 0.6623 | 0.6494 | 0.6597 |
| 0.7652 | 3.0 | 723 | 0.7354 | 0.6842 | 0.6861 | 0.6843 | 0.6854 | 0.6847 |
| 0.6205 | 4.0 | 964 | 0.7766 | 0.6931 | 0.6941 | 0.6944 | 0.7000 | 0.6941 |
| 0.5054 | 5.0 | 1205 | 0.7738 | 0.6929 | 0.6930 | 0.6997 | 0.6961 | 0.6899 |
| 0.3829 | 6.0 | 1446 | 0.9374 | 0.6863 | 0.6904 | 0.6847 | 0.6899 | 0.6930 |
| 0.2818 | 7.0 | 1687 | 1.0925 | 0.6998 | 0.7031 | 0.6996 | 0.7010 | 0.7055 |
| 0.2268 | 8.0 | 1928 | 1.1923 | 0.6952 | 0.6998 | 0.6956 | 0.6949 | 0.7003 |
| 0.17 | 9.0 | 2169 | 1.4177 | 0.6929 | 0.6972 | 0.6914 | 0.6955 | 0.6982 |
| 0.1479 | 10.0 | 2410 | 1.5393 | 0.6934 | 0.6980 | 0.6920 | 0.6956 | 0.6993 |
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