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sreejith8100
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layoutlm-funsd

Token Classification
Transformers
PyTorch
layoutlm
Generated from Trainer
Inference Endpoints
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End of training

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  1. README.md +34 -14
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -15,15 +15,27 @@ 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: 0.0875
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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
@@ -52,14 +64,22 @@ The following hyperparameters were used during training:
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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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- | 0.256 | 1.0 | 41 | 0.0998 | 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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- | 0.1026 | 2.0 | 82 | 0.0875 | 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: 0.3805
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+ - Ame Precision: 1.0
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+ - Ame Recall: 1.0
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+ - Ame F1: 1.0
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+ - Ame Number: 19
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+ - Andom number Precision: 1.0
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+ - Andom number Recall: 1.0
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+ - Andom number F1: 1.0
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+ - Andom number Number: 19
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+ - Ather Name Precision: 1.0
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+ - Ather Name Recall: 1.0
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+ - Ather Name F1: 1.0
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+ - Ather Name Number: 19
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+ - Lace Of Birth Precision: 1.0
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+ - Lace Of Birth Recall: 1.0
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+ - Lace Of Birth F1: 1.0
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+ - Lace Of Birth Number: 5
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+ - Other Name Precision: 1.0
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+ - Other Name Recall: 1.0
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+ - Other Name F1: 1.0
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+ - Other Name Number: 19
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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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  - 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: 10
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Ame Precision | Ame Recall | Ame F1 | Ame Number | Andom number Precision | Andom number Recall | Andom number F1 | Andom number Number | Ather Name Precision | Ather Name Recall | Ather Name F1 | Ather Name Number | Lace Of Birth Precision | Lace Of Birth Recall | Lace Of Birth F1 | Lace Of Birth Number | Other Name Precision | Other Name Recall | Other Name F1 | Other Name Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------------:|:----------:|:------:|:----------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:-----------------------:|:--------------------:|:----------------:|:--------------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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+ | 1.2231 | 1.0 | 41 | 0.8784 | 0.3220 | 1.0 | 0.4872 | 19 | 1.0 | 1.0 | 1.0 | 19 | 0.0 | 0.0 | 0.0 | 19 | 0.0 | 0.0 | 0.0 | 5 | 0.0 | 0.0 | 0.0 | 19 | 0.4872 | 0.4691 | 0.4780 | 0.9126 |
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+ | 0.8256 | 2.0 | 82 | 0.6942 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 5 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.6803 | 3.0 | 123 | 0.5889 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 5 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.5863 | 4.0 | 164 | 0.5189 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 5 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.5261 | 5.0 | 205 | 0.4713 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 5 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.4835 | 6.0 | 246 | 0.4369 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 5 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.4519 | 7.0 | 287 | 0.4111 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 5 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.4287 | 8.0 | 328 | 0.3938 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 5 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.4142 | 9.0 | 369 | 0.3837 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 5 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 1.0 |
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+ | 0.4079 | 10.0 | 410 | 0.3805 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 5 | 1.0 | 1.0 | 1.0 | 19 | 1.0 | 1.0 | 1.0 | 1.0 |
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  ### Framework versions
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