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---
language:
- es
- en
tags:
- sentiment-analysis
- xlm-roberta
- multilingual
- movies
license: apache-2.0
base_model:
- FacebookAI/xlm-roberta-base
---
# XLM-R Sentiment EN/ES (Movie Reviews)
Clasificador binario (*Positive/Negative*) para rese帽as de pel铆culas en **ingl茅s y espa帽ol**, fine-tuned desde `xlm-roberta-base` con **Rotten Tomatoes movies and critic reviews dataset** from [Kaggle](https://www.kaggle.com/datasets/stefanoleone992/rotten-tomatoes-movies-and-critic-reviews-dataset)
**M茅tricas:**
Acc **0.8519** 路 F1 **0.8876** 路 Prec **0.8646** 路 Rec **0.9119** 路 AUC **0.9260**
*Umbral recomendado:** **0.48*
## Uso r谩pido
```python
from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch
m = "Ricardouchub/xlmr-sentiment-es-en"; thr = 0.48
tok = AutoTokenizer.from_pretrained(m, use_fast=True)
mdl = AutoModelForSequenceClassification.from_pretrained(m).eval()
enc = tok(["Excelente actuaci贸n, final predecible."], truncation=True, max_length=224, padding=True, return_tensors="pt")
p = torch.softmax(mdl(**enc).logits, dim=-1)[:,1].item()
print(("POSITIVE" if p>=thr else "NEGATIVE"), round(p*100,1), "%")
```
*Notas: split por pel铆cula (evita fuga); limpieza m铆nima de texto. No apto para usos sensibles.*
**Autor: Ricardo Urdaneta** |