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BERT-ASTD
mofawzy/BERT-ASTD
BERT-ASTD is a text classification model from mofawzy. Use it when you need a label for a piece of text. It is set up for transformers.
Arabic version bert model fine tuned on ASTD dataset balanced version to identify twitter sentiments in Arabic language MSA dialect .
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Repo size
6.7 GB
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Feb 18, 2022
- SHA
- e0b1163d
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Datasets
Model card
From the Hugging Face model README
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)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- ar
- Created
- Mar 2, 2022
- Updated
- Feb 18, 2022