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pedramyazdipoor
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persian_xlm_roberta_large

Question Answering
Transformers
PyTorch
xlm-roberta
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@@ -32,10 +32,16 @@ weight_decay = 0.01,
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  ## Performance
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  Evaluated on the PQuAD Persian test set with the [official PQuAD link](https://huggingface.co/datasets/newsha/PQuAD/blob/main/Test_v8.0.json).
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  I trained for more than 1 epoch as well, but I get worse results.
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- ```
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- "exact_match": 66.85,
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- "f1": 87.56
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- ```
 
 
 
 
 
 
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  ## How to use
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  ```python
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  from transformers import AutoTokenizer, AutoModelForQuestionAnswering
 
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  ## Performance
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  Evaluated on the PQuAD Persian test set with the [official PQuAD link](https://huggingface.co/datasets/newsha/PQuAD/blob/main/Test_v8.0.json).
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  I trained for more than 1 epoch as well, but I get worse results.
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+ ### Question Answering On Test Set of PQuAD Dataset
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+
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+ | Metric | Our XLM-Roberta | Our Pars Bert |
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+ |:----------------:|:---------------:|:-------------:|
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+ | Exact Match | 66.56* | 47.44 |
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+ | F1 | 87.31* | 81.96 |
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  ## How to use
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  ```python
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  from transformers import AutoTokenizer, AutoModelForQuestionAnswering