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@@ -59,7 +59,28 @@ It achieves the following results on the evaluation set:
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  - Precision: 0.8584
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  - Recall: 0.8584
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  - F1: 0.8584
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- - Accuracy: 0.8584
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## References
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  - Precision: 0.8584
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  - Recall: 0.8584
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  - F1: 0.8584
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+ - Tokens Accuracy: 0.8584
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+ - Line Accuracy: 0.9197
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+
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+ ## Accuracy at line level
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+ - Line Accuracy: 91.97%
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+ - Accuracy by label
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+ - Caption: 79.42%
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+ - Footnote: 68.21%
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+ - Formula: 98.02%
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+ - List-item: 82.72%
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+ - Page-footer: 99.17%
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+ - Page-header: 84.18%
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+ - Picture: 83.2%
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+ - Section-header: 76.92%
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+ - Table: 97.65%
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+ - Text: 91.17%
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+ - Title: 77.46%
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+ ![Lines labels vs accuracy (%) of the dataset DocLayNet base of test (model: LiLT base finetuned on DocLayNet base))](https://huggingface.co/pierreguillou/lilt-xlm-roberta-base-finetuned-with-DocLayNet-base-at-linelevel-ml384/resolve/main/docs/lines_labels_accuracy_DocLayNet_base_test_LiLT_base_line_level_384.png)
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+ ![Confusion matrix of the labeled lines of the dataset DocLayNet base of test (model: LiLT base finetuned on DocLayNet base)](https://huggingface.co/pierreguillou/lilt-xlm-roberta-base-finetuned-with-DocLayNet-base-at-linelevel-ml384/resolve/main/docs/confusion_matrix_labeled_lines_DocLayNet_base_test_LiLT_base_line_level_384.png)
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  ## References
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