metadata
language:
- ar
datasets:
- labr
tags:
- labr
widget:
- text: كتاب ممل جدا تضييع وقت
- text: اسلوب ممتع وشيق في الكتاب استمعت بالاحداث
BERT-LABR unbalanced
Arabic version bert model fine tuned on LABR dataset
Data
The model were fine-tuned on ~63000 book reviews in arabic using bert large arabic
Results
| class | precision | recall | f1-score | Support |
|---|---|---|---|---|
| 0 | 0.8109 | 0.6832 | 0.7416 | 1670 |
| 1 | 0.9399 | 0.9689 | 0.9542 | 8541 |
| Accuracy | 0.9221 | 10211 |
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-labr-unbalanced"
model = AutoModelForSequenceClassification.from_pretrained(model_name,num_labels=2)
tokenizer = AutoTokenizer.from_pretrained(model_name)