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