Model: JavicR22/SpamVision
Author: JavicR22
Pipeline: text-classification
Library: transformers
Tags: transformers, safetensors, bert, text-classification, spam-detection, sms, beto, spanish, pytorch, es, dataset:sms_spam, base_model:dccuchile/bert-base-spanish-wwm-cased, base_model:finetune:dccuchile/bert-base-spanish-wwm-cased, license:mit, model-index, endpoints_compatible, region:us
Base models (finetune): id: dccuchile/bert-base-spanish-wwm-cased
Card metadata: language: es
license: mit
library_name: transformers
tags: spam-detection, sms, text-classification, beto, bert, spanish, pytorch
datasets: sms_spam
metrics: accuracy, f1, precision, recall
base_model: dccuchile/bert-base-spanish-wwm-cased
pipeline_tag: text-classification
widget: text: ¡FELICIDADES! Ganaste un premio de $1000. Haz clic aquí para reclamarlo
example_title: Spam - Premio falso, text: ¡Increíble! Ha ganado un viaje con todos los gastos pagados a Cancún. Llame al 1-800-VIAJES
example_title: Spam - Oferta fraudulenta, text: URGENTE: Su cuenta ha sido suspendida. Haga clic aquí para reactivarla
example_title: Spam - Phishing bancario, text: Hola mamá, llegaré tarde a casa. Nos vemos en la cena
example_title: Legítimo - Mensaje familiar, text: Buenos días, confirmo la reunión de mañana a las 3pm
example_title: Legítimo - Mensaje de trabajo
model-index: name: spamvision-beto
results: task: type: text-classification
name: Text Classification
dataset: name: Spanish SMS Spam Detection
type: sms_spam
metrics: type: accuracy
value: 0.962
name: Accuracy
verified: no, type: f1
value: 0.951
name: F1 Score
verified: no, type: precision
value: 0.948
name: Precision
verified: no, type: recall
value: 0.955
name: Recall
verified: no
Likes: 0 | All-time downloads: 32
Created: 2025-11-21 05:53:22