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sentiment-roberta-es-2025_II
Danmo16/sentiment-roberta-es-2025_II
sentiment-roberta-es-2025_II is a text classification model from Danmo16. 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 20, 2025
- Updated
- Nov 20, 2025
- SHA
- c3723e9b
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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 xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0916
- Accuracy: 0.3947
- Precision: 0.3806
- Recall: 0.3405
- F1 Macro: 0.2015
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Macro |
|---|---|---|---|---|---|---|---|
| 1.1116 | 1.0 | 31 | 1.0940 | 0.3885 | 0.1295 | 0.3333 | 0.1865 |
| 1.1025 | 2.0 | 62 | 1.0900 | 0.3885 | 0.1295 | 0.3333 | 0.1865 |
| 1.1003 | 3.0 | 93 | 1.0934 | 0.3722 | 0.1915 | 0.3210 | 0.1987 |
| 1.0943 | 4.0 | 124 | 1.0906 | 0.3926 | 0.4634 | 0.3375 | 0.1954 |
| 1.1003 | 5.0 | 155 | 1.0916 | 0.3947 | 0.3806 | 0.3405 | 0.2015 |
| 1.0964 | 6.0 | 186 | 1.0971 | 0.3906 | 0.4631 | 0.3354 | 0.1910 |
| 1.1015 | 7.0 | 217 | 1.0951 | 0.3865 | 0.1291 | 0.3316 | 0.1858 |
| 1.0944 | 8.0 | 248 | 1.0921 | 0.3865 | 0.1291 | 0.3316 | 0.1858 |
| 1.0957 | 9.0 | 279 | 1.0930 | 0.3865 | 0.1291 | 0.3316 | 0.1858 |
| 1.099 | 10.0 | 310 | 1.0938 | 0.3865 | 0.1291 | 0.3316 | 0.1858 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.1+cu130
- Datasets 4.4.1
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Nov 20, 2025
- Updated
- Nov 20, 2025