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End of training

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@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0927
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  - Precision: 1.0
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  - Recall: 1.0
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  - F1: 1.0
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- - Accuracy: 0.9770
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  ## Model description
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@@ -55,21 +55,21 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 0.2618 | 100 | 0.8328 | 0.9560 | 0.9542 | 0.9551 | 0.6809 |
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- | No log | 0.5236 | 200 | 0.6762 | 0.9539 | 0.9485 | 0.9512 | 0.7220 |
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- | No log | 0.7853 | 300 | 0.4139 | 0.9981 | 0.9981 | 0.9981 | 0.9046 |
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- | No log | 1.0471 | 400 | 0.1853 | 0.9962 | 0.9962 | 0.9962 | 0.9655 |
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- | 0.6198 | 1.3089 | 500 | 0.0927 | 1.0 | 1.0 | 1.0 | 0.9770 |
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- | 0.6198 | 1.5707 | 600 | 0.0518 | 1.0 | 1.0 | 1.0 | 0.9885 |
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- | 0.6198 | 1.8325 | 700 | 0.0414 | 1.0 | 1.0 | 1.0 | 0.9868 |
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- | 0.6198 | 2.0942 | 800 | 0.0330 | 1.0 | 1.0 | 1.0 | 0.9951 |
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- | 0.6198 | 2.3560 | 900 | 0.0282 | 1.0 | 1.0 | 1.0 | 0.9984 |
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- | 0.0565 | 2.6178 | 1000 | 0.0260 | 1.0 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
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- - Transformers 4.43.2
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  - Pytorch 2.1.0+cu118
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  - Datasets 2.20.0
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  - Tokenizers 0.19.1
 
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  This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0209
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  - Precision: 1.0
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  - Recall: 1.0
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  - F1: 1.0
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+ - Accuracy: 1.0
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 0.0290 | 100 | 0.8242 | 0.9549 | 0.9520 | 0.9534 | 0.7171 |
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+ | No log | 0.0579 | 200 | 0.5708 | 0.9636 | 0.9772 | 0.9703 | 0.7951 |
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+ | No log | 0.0869 | 300 | 0.3493 | 0.9993 | 0.9993 | 0.9993 | 0.8839 |
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+ | No log | 0.1158 | 400 | 0.1466 | 0.9998 | 0.9998 | 0.9998 | 0.9752 |
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+ | 0.6024 | 0.1448 | 500 | 0.0689 | 0.9965 | 0.9972 | 0.9969 | 0.9823 |
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+ | 0.6024 | 0.1738 | 600 | 0.0442 | 1.0 | 1.0 | 1.0 | 0.9946 |
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+ | 0.6024 | 0.2027 | 700 | 0.0360 | 1.0 | 1.0 | 1.0 | 0.9847 |
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+ | 0.6024 | 0.2317 | 800 | 0.0280 | 1.0 | 1.0 | 1.0 | 0.9972 |
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+ | 0.6024 | 0.2606 | 900 | 0.0247 | 1.0 | 1.0 | 1.0 | 0.9953 |
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+ | 0.0516 | 0.2896 | 1000 | 0.0209 | 1.0 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
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+ - Transformers 4.43.3
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  - Pytorch 2.1.0+cu118
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  - Datasets 2.20.0
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  - Tokenizers 0.19.1