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)
- Downloads last month
- 13
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.