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xlm-roberta-large-sentiment-spanish
Kvel12/xlm-roberta-large-sentiment-spanish
xlm-roberta-large-sentiment-spanish is a text classification model from Kvel12. 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 18, 2025
- Updated
- Nov 19, 2025
- SHA
- 90beea68
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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. -->
xlm-roberta-large-sentiment-spanish
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: 0.7771
- Accuracy: 0.6905
- Precision: 0.6889
- Recall: 0.6892
- F1: 0.6891
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: 5e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: 0.3
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 1.1261 | 1.0 | 121 | 1.1002 | 0.4089 | 0.3630 | 0.3572 | 0.2534 |
| 1.0446 | 2.0 | 242 | 1.0210 | 0.4703 | 0.5078 | 0.4825 | 0.4730 |
| 0.9145 | 3.0 | 363 | 0.8860 | 0.6296 | 0.6032 | 0.6232 | 0.5959 |
| 0.7923 | 4.0 | 484 | 0.8051 | 0.6306 | 0.6207 | 0.6292 | 0.6039 |
| 0.6934 | 5.0 | 605 | 0.7455 | 0.6837 | 0.6710 | 0.6782 | 0.6638 |
| 0.611 | 6.0 | 726 | 0.7499 | 0.6899 | 0.6792 | 0.6811 | 0.6619 |
| 0.5625 | 7.0 | 847 | 0.7551 | 0.6837 | 0.6722 | 0.6815 | 0.6731 |
| 0.5115 | 8.0 | 968 | 0.7689 | 0.6982 | 0.6922 | 0.6926 | 0.6924 |
| 0.4417 | 9.0 | 1089 | 0.8142 | 0.6868 | 0.6765 | 0.6839 | 0.6782 |
| 0.4223 | 10.0 | 1210 | 0.8160 | 0.6972 | 0.6862 | 0.6920 | 0.6880 |
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 18, 2025
- Updated
- Nov 19, 2025