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--- |
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language: |
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- ar |
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datasets: |
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- ASTD |
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tags: |
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- ASTD |
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widget: |
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- text: "العنف والقتل في محيط العالم في زياده يوميا" |
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- text: "الصداقه تزرع الحياه ازهارا" |
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--- |
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# BERT-ASTD Balanced |
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Arabic version bert model fine tuned on ASTD dataset balanced version to identify twitter sentiments in Arabic language MSA dialect . |
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## Data |
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The model were fine-tuned on ~1330 tweet in Arabic language. |
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## Results |
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| class | precision | recall | f1-score | Support | |
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|----------|-----------|--------|----------|---------| |
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| 0 | 0.9328 | 0.9398 | 0.9363 | 133 | |
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| 1 | 0.9394 | 0.9323 | 0.9358 | 133 | |
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| Accuracy | | | 0.9361 | 266 | |
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## How to use |
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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: |
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```python |
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from transformers import AutoModelForSequenceClassification, AutoTokenizer |
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model_name="mofawzy/BERT-ASTD" |
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model = AutoModelForSequenceClassification.from_pretrained(model_name,num_labels=2) |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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``` |
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