Question Answering
Transformers
Safetensors
French
roberta
Inference Endpoints
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@@ -40,10 +40,10 @@ Our methodology is described in a blog post available in [English](https://blog.
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  ## Results (french QA test split)
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  | Model | Exact_match | F1-score | Answer_f1 | NoAnswer_f1 |
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  | ----------- | ----------- | ----------- | ----------- | ----------- |
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- | [QAmembert](https://huggingface.co/CATIE-AQ/QAmembert) (110M) | 77.14 | 86.88 | 75.66 | 98.11
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- | QAmembert2 (112M) (this version) | 76.47 | 88.25 | 78.66 | 97.84
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- | [QAmembert-large](https://huggingface.co/CATIE-AQ/QAmembert-large) (336M) | 77.14 | 88.74 | 78.83 | **98.65**
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- | [QAmemberta](https://huggingface.co/CATIE-AQ/QAmemberta) (111M) | **78.18** | **89.53** | **81.40** | 97.64
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  ### Usage
 
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  ## Results (french QA test split)
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  | Model | Exact_match | F1-score | Answer_f1 | NoAnswer_f1 |
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  | ----------- | ----------- | ----------- | ----------- | ----------- |
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+ | [QAmembert](https://huggingface.co/CATIE-AQ/QAmembert) (110M, 512 tokens) | 77.14 | 86.88 | 75.66 | 98.11
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+ | [QAmembert2](https://huggingface.co/CATIE-AQ/QAmembert2) (112M, 1024 tokens) | 76.47 | 88.25 | 78.66 | 97.84
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+ | [QAmembert-large](https://huggingface.co/CATIE-AQ/QAmembert-large) (336M, 512 tokens) | 77.14 | 88.74 | 78.83 | **98.65**
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+ | QAmemberta (111M, 1024 tokens) (this version) | **78.18** | **89.53** | **81.40** | 97.64
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  ### Usage