metadata

language:
  - ar
datasets:
  - HARD
tags:
  - HARD
widget:
  - text: جيد. المكان جميل وهاديء. كل شي جيد ونظيف
  - text: استغرب تقييم الفندق كخمس نجوم”. لا شي. يستحق

BERT-ASTD Balanced

Arabic version bert model fine tuned on Hotel Arabic Reviews dataset from booking.com (HARD) dataset balanced version to identify sentiments opinion in Arabic language.

Data

The model were fine-tuned on ~93000 book reviews in arabic using bert large arabic

Results

class	precision	recall	f1-score	Support
0	0.9655	0.9601	0.9628	10570
1	0.9603	0.9657	0.9630	10570
Accuracy			0.9629	21140

How to use

You can use these models by installing torch or tensorflow and Huggingface library transformers. And you can use it directly by initializing it like this:

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model_name="mofawzy/Bert-hard-balanced"
model = AutoModelForSequenceClassification.from_pretrained(model_name,num_labels=2)
tokenizer = AutoTokenizer.from_pretrained(model_name)