---
language: es
license: cc-by-nc-sa-4.0
tags:
  - text-classification
  - sentiment-analysis
  - sarcasm-detection
  - xlm-roberta
base_model: xlm-roberta-large
pipeline_tag: text-classification
datasets:
  - Ernesto-1997/Sarcastic_spanish_dataset
metrics:
  - f1
  - precision
  - recall
  - accuracy
---

# Sarcasmo XLM-ROBERTA

Fine-tuning de **`xlm-roberta-large`** sobre el dataset **Sarcastic_spanish_dataset** (Ernesto-1997).
Tarea: clasificación binaria (sarcasmo / no_sarcasmo).
Taller PLN - Maestría Ingeniería de Sistemas, Univalle.

## Métricas en test

| Batch | F1 | Precision | Recall | Accuracy |
|------:|---:|---:|---:|---:|
| bs8 ⭐ | 0.9170 | 0.9201 | 0.9139 | 0.9351 |
| bs16 | 0.9104 | 0.9232 | 0.8979 | 0.9306 |
| bs32 | 0.9081 | 0.9199 | 0.8966 | 0.9288 |


## Uso

```python
from transformers import AutoModelForSequenceClassification, AutoTokenizer, pipeline

m = AutoModelForSequenceClassification.from_pretrained("cvalenciaunivalle/sarcasmo-xlm-roberta-large", subfolder="bs8")
t = AutoTokenizer.from_pretrained("cvalenciaunivalle/sarcasmo-xlm-roberta-large", subfolder="bs8")
pipe = pipeline("text-classification", model=m, tokenizer=t)
pipe("¡Qué divertido, otro lunes de trabajo!")
```

## Detalles

- Modelo base: `xlm-roberta-large`
- Dataset: [Ernesto-1997/Sarcastic_spanish_dataset](https://huggingface.co/datasets/Ernesto-1997/Sarcastic_spanish_dataset)
- Trainer + EarlyStopping
- Hardware: Kaggle GPU
- Compañeros: Laura Valero, Cristian Valencia