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completing ocr evaluations metric
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@ -165,7 +165,7 @@ This model is trained on data where most of the samples are in Fraktur german sc
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| Dataset | Input | CER | WER |
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| Dataset | Input | CER | WER |
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|-----------------------|:-------|:-----------|:----------|
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|-----------------------|:-------|:-----------|:----------|
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| OCR-D-GT-Archiveform | BIN | 0.02147 | 0.05685 |
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| OCR-D-GT-Archiveform | BIN | 0.02147 | 0.05685 |
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| OCR-D-GT-Archiveform | RGB | | |
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| OCR-D-GT-Archiveform | RGB | 0.01636 | 0.06285 |
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#### CNN-RNN model: model_eynollah_ocr_cnnrnn_20250904 (Default)
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#### CNN-RNN model: model_eynollah_ocr_cnnrnn_20250904 (Default)
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@ -186,7 +186,7 @@ This transformer OCR model is trained on the same data as model_eynollah_ocr_tro
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| Dataset | Input | CER | WER |
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| Dataset | Input | CER | WER |
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|-----------------------|:------------|:-----------|:----------|
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|-----------------------|:------------|:-----------|:----------|
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| OCR-D-GT-Archiveform | BIN | 0.01841 | 0.05589 |
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| OCR-D-GT-Archiveform | BIN | 0.01841 | 0.05589 |
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| OCR-D-GT-Archiveform | RGB | | |
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| OCR-D-GT-Archiveform | RGB | 0.01552 | 0.06177 |
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| BLN600 | RGB | 0.06347 | 0.13853 |
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| BLN600 | RGB | 0.06347 | 0.13853 |
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## Heuristic methods
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## Heuristic methods
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