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End of training

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  1. README.md +14 -15
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@@ -15,19 +15,19 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0859
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- - Nswer Precision: 1.0
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- - Nswer Recall: 1.0
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- - Nswer F1: 1.0
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  - Nswer Number: 82
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- - Uestion Precision: 1.0
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  - Uestion Recall: 1.0
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- - Uestion F1: 1.0
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  - Uestion Number: 82
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- - Overall Precision: 1.0
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- - Overall Recall: 1.0
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- - Overall F1: 1.0
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- - Overall Accuracy: 1.0
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 3e-05
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- - train_batch_size: 8
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- - eval_batch_size: 4
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 2
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Nswer Precision | Nswer Recall | Nswer F1 | Nswer Number | Uestion Precision | Uestion Recall | Uestion F1 | Uestion Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------:|:--------:|:------------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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- | 0.2545 | 1.0 | 41 | 0.0986 | 1.0 | 1.0 | 1.0 | 82 | 1.0 | 1.0 | 1.0 | 82 | 1.0 | 1.0 | 1.0 | 1.0 |
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- | 0.1017 | 2.0 | 82 | 0.0859 | 1.0 | 1.0 | 1.0 | 82 | 1.0 | 1.0 | 1.0 | 82 | 1.0 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1332
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+ - Nswer Precision: 0.9759
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+ - Nswer Recall: 0.9878
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+ - Nswer F1: 0.9818
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  - Nswer Number: 82
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+ - Uestion Precision: 0.9880
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  - Uestion Recall: 1.0
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+ - Uestion F1: 0.9939
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  - Uestion Number: 82
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+ - Overall Precision: 0.9819
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+ - Overall Recall: 0.9939
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+ - Overall F1: 0.9879
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+ - Overall Accuracy: 0.9959
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 3e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 1
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Nswer Precision | Nswer Recall | Nswer F1 | Nswer Number | Uestion Precision | Uestion Recall | Uestion F1 | Uestion Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------:|:--------:|:------------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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+ | 0.2778 | 1.0 | 41 | 0.1332 | 0.9759 | 0.9878 | 0.9818 | 82 | 0.9880 | 1.0 | 0.9939 | 82 | 0.9819 | 0.9939 | 0.9879 | 0.9959 |
 
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  ### Framework versions