Text Classification
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use raulgdp/xml-roberta-sarcasmo-spanish-2026 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raulgdp/xml-roberta-sarcasmo-spanish-2026 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="raulgdp/xml-roberta-sarcasmo-spanish-2026")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("raulgdp/xml-roberta-sarcasmo-spanish-2026") model = AutoModelForSequenceClassification.from_pretrained("raulgdp/xml-roberta-sarcasmo-spanish-2026", device_map="auto") - Notebooks
- Google Colab
- Kaggle
xml-roberta-sarcasmo-spanish-2026
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: 0.4024
- Accuracy: 0.9361
- Precision: 0.9360
- Recall: 0.9361
- F1: 0.9360
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.3613 | 1.0 | 955 | 0.3642 | 0.8743 | 0.8776 | 0.8743 | 0.8718 |
| 0.264 | 2.0 | 1910 | 0.2176 | 0.9217 | 0.9216 | 0.9217 | 0.9214 |
| 0.184 | 3.0 | 2865 | 0.3219 | 0.9322 | 0.9325 | 0.9322 | 0.9318 |
| 0.1421 | 4.0 | 3820 | 0.3517 | 0.9348 | 0.9347 | 0.9348 | 0.9346 |
| 0.0658 | 5.0 | 4775 | 0.4024 | 0.9361 | 0.9360 | 0.9361 | 0.9360 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.7.1+cu118
- Datasets 4.2.0
- Tokenizers 0.22.1
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Model tree for raulgdp/xml-roberta-sarcasmo-spanish-2026
Base model
FacebookAI/xlm-roberta-large