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finetuning-sentiment-model-spanish
lonelyalpaca/finetuning-sentiment-model-spanish
finetuning-sentiment-model-spanish is a text classification model from lonelyalpaca. 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
- Dec 2, 2025
- Updated
- Dec 3, 2025
- SHA
- 7f559eae
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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. -->
finetuning-sentiment-model-spanish
This model is a fine-tuned version of lonelyalpaca/finetuning-sentiment-model on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1337
- Accuracy: 0.9482
- F1: 0.9483
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: 8
- 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
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.1632 | 0.4486 | 1000 | 0.1624 | 0.9414 | 0.9295 |
| 0.1361 | 0.8973 | 2000 | 0.1254 | 0.9453 | 0.9356 |
| 0.116 | 1.3459 | 3000 | 0.1451 | 0.9463 | 0.9438 |
| 0.1175 | 1.7945 | 4000 | 0.1337 | 0.9482 | 0.9483 |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 3.6.0
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Dec 2, 2025
- Updated
- Dec 3, 2025