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End of training

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README.md CHANGED
@@ -18,15 +18,15 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5781
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- - Bleu: 0.0666
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- - Precisions: [0.7842741935483871, 0.7038724373576309, 0.6413612565445026, 0.5938461538461538]
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- - Brevity Penalty: 0.0984
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- - Length Ratio: 0.3013
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- - Translation Length: 496
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- - Reference Length: 1646
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- - Cer: 0.7601
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- - Wer: 0.8490
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  ## Model description
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@@ -58,12 +58,12 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Bleu | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Cer | Wer |
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- |:-------------:|:-----:|:----:|:---------------:|:------:|:------------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
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- | 3.6546 | 1.0 | 253 | 1.6338 | 0.0048 | [0.46774193548387094, 0.19365079365079366, 0.10424710424710425, 0.04926108374384237] | 0.0326 | 0.2260 | 372 | 1646 | 0.8468 | 0.9279 |
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- | 1.4087 | 2.0 | 506 | 0.8228 | 0.0443 | [0.6833333333333333, 0.5390070921985816, 0.44808743169398907, 0.3883495145631068] | 0.0881 | 0.2916 | 480 | 1646 | 0.7716 | 0.8817 |
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- | 0.8213 | 3.0 | 759 | 0.6331 | 0.0652 | [0.7858585858585858, 0.6917808219178082, 0.6272965879265092, 0.5802469135802469] | 0.0978 | 0.3007 | 495 | 1646 | 0.7612 | 0.8498 |
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- | 0.6256 | 4.0 | 1012 | 0.5781 | 0.0666 | [0.7842741935483871, 0.7038724373576309, 0.6413612565445026, 0.5938461538461538] | 0.0984 | 0.3013 | 496 | 1646 | 0.7601 | 0.8490 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4919
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+ - Bleu: 0.0652
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+ - Precisions: [0.7938775510204081, 0.7020785219399538, 0.6462765957446809, 0.6050156739811913]
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+ - Brevity Penalty: 0.0955
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+ - Length Ratio: 0.2986
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+ - Translation Length: 490
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+ - Reference Length: 1641
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+ - Cer: 0.7510
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+ - Wer: 0.8349
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Bleu | Precisions | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Cer | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:--------------------------------------------------------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:------:|
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+ | 4.0081 | 1.0 | 253 | 1.6452 | 0.0 | [0.4795539033457249, 0.14622641509433962, 0.03205128205128205, 0.0] | 0.0061 | 0.1639 | 269 | 1641 | 0.8712 | 0.9425 |
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+ | 1.2573 | 2.0 | 506 | 0.6901 | 0.0379 | [0.6787234042553192, 0.5036319612590799, 0.4044943820224719, 0.3177257525083612] | 0.0828 | 0.2864 | 470 | 1641 | 0.7727 | 0.8821 |
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+ | 0.9461 | 3.0 | 759 | 0.5654 | 0.0600 | [0.7469635627530364, 0.631578947368421, 0.5684210526315789, 0.5232198142414861] | 0.0981 | 0.3010 | 494 | 1641 | 0.7547 | 0.8479 |
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+ | 0.669 | 4.0 | 1012 | 0.4919 | 0.0652 | [0.7938775510204081, 0.7020785219399538, 0.6462765957446809, 0.6050156739811913] | 0.0955 | 0.2986 | 490 | 1641 | 0.7510 | 0.8349 |
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  ### Framework versions
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