sreejith8100
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End of training
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README.md
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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.
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- Nswer Precision:
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- Nswer Recall:
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- Nswer F1:
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- Nswer Number: 82
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- Uestion Precision:
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- Uestion Recall: 1.0
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- Uestion F1:
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- Uestion Number: 82
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- Overall Precision:
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- Overall Recall:
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- Overall F1:
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- Overall Accuracy:
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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:
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- eval_batch_size:
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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:
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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.
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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
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