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BERT-ASTD Balanced

Arabic version bert model fine tuned on ASTD dataset balanced version to identify twitter sentiments in Arabic language MSA dialect .

Data

The model were fine-tuned on ~1330 tweet in Arabic language.

Results

class precision recall f1-score Support
0 0.9328 0.9398 0.9363 133
1 0.9394 0.9323 0.9358 133
Accuracy 0.9361 266

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-ASTD"
model = AutoModelForSequenceClassification.from_pretrained(model_name,num_labels=2)
tokenizer = AutoTokenizer.from_pretrained(model_name)
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