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rafaelwt/beto-amazon-reviews-es-3clases
beto-amazon-reviews-es-3clases is a text classification model from rafaelwt. Use it when you need a label for a piece of text. The card lists the license as apache-2.0.
Fine-tuned version of dccuchile/bert-base-spanish-wwm-cased (BETO) for classifying short Spanish customer texts into three business classes: negativo, neutro, positivo. Built for Laboratorio 4 (Módulo 10, Natural Lang…
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From the Hugging Face model README
Fine-tuned version of dccuchile/bert-base-spanish-wwm-cased (BETO)
for classifying short Spanish customer texts into three business classes: negativo, neutro, positivo.
Built for Laboratorio 4 (Módulo 10, Natural Language Processing) by Grupo 5.
| id | label | source stars |
|---|---|---|
| 0 | negativo | 1-2 |
| 1 | neutro | 3 |
| 2 | positivo | 4-5 |
train split of SetFit/amazon_reviews_multi_es (200,000 reviews); official validation (5,000) and test (5,000).| model | accuracy | macro F1 | F1 negativo | F1 neutro | F1 positivo |
|---|---|---|---|---|---|
| TF-IDF + Logistic Regression (baseline) | 0.737 | 0.705 | 0.798 | 0.492 | 0.823 |
| BETO fine-tuned (this model) | 0.793 | 0.738 | 0.850 | 0.487 | 0.876 |
Most errors involve the neutro class. Sarcastic texts tend to be classified as positivo.
from transformers import pipeline
clf = pipeline("text-classification", model="rafaelwt/beto-amazon-reviews-es-3clases")
clf("Me cobraron un monto que no corresponde en mi factura.")