Model: sekarmulyani/indobertweet-ulasan-beauty-products
Author: sekarmulyani
Pipeline: text-classification
Library: transformers
Tags: transformers, pytorch, bert, text-classification, rating classification, e-commerce, id, dataset:sekarmulyani/ulasan-beauty-products, doi:10.57967/hf/1033, license:apache-2.0, endpoints_compatible, region:us
Card metadata: license: apache-2.0
datasets: sekarmulyani/ulasan-beauty-products
language: id
metrics: f1, roc_auc, accuracy
pipeline_tag: text-classification
widget: text: mengecewakan, sebulan baru sampai, botolnya pecah
example_title: Contoh 1, text: kulit saya jadi kering dan bruntusan
example_title: Contoh 2, text: barang sudah datang tapi kurirnya lemot
example_title: Contoh 3, text: lipbalm oke, sesuai harga
example_title: Contoh 4, text: recommended buat yang pengen keliatan cantik
example_title: Contoh 5
library_name: transformers
tags: rating classification, e-commerce
Likes: 0 | All-time downloads: 547
Created: 2023-08-25 11:49:22