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Layoutlmv3InvoiceCzech

Token Classification
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layoutlmv3
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  1. README.md +26 -21
  2. model.safetensors +1 -1
README.md CHANGED
@@ -21,11 +21,11 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1148
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- - Precision: 0.7832
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- - Recall: 0.8333
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- - F1: 0.8075
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- - Accuracy: 0.9737
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  ## Model description
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@@ -51,28 +51,33 @@ The following hyperparameters were used during training:
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 15
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | No log | 1.0 | 43 | 1.3234 | 0.0 | 0.0 | 0.0 | 0.8323 |
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- | No log | 2.0 | 86 | 1.0017 | 0.0 | 0.0 | 0.0 | 0.8323 |
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- | No log | 3.0 | 129 | 0.6869 | 0.0 | 0.0 | 0.0 | 0.8326 |
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- | No log | 4.0 | 172 | 0.5545 | 0.3262 | 0.3889 | 0.3548 | 0.8904 |
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- | No log | 5.0 | 215 | 0.4323 | 0.5088 | 0.5604 | 0.5333 | 0.9220 |
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- | No log | 6.0 | 258 | 0.3487 | 0.6037 | 0.6365 | 0.6196 | 0.9335 |
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- | No log | 7.0 | 301 | 0.2900 | 0.6678 | 0.7017 | 0.6843 | 0.9447 |
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- | No log | 8.0 | 344 | 0.2355 | 0.6976 | 0.7271 | 0.7120 | 0.9517 |
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- | No log | 9.0 | 387 | 0.1894 | 0.7567 | 0.7850 | 0.7706 | 0.9630 |
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- | No log | 10.0 | 430 | 0.1578 | 0.7492 | 0.8152 | 0.7808 | 0.9694 |
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- | No log | 11.0 | 473 | 0.1396 | 0.7575 | 0.8188 | 0.7870 | 0.9708 |
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- | 0.6363 | 12.0 | 516 | 0.1271 | 0.7705 | 0.8273 | 0.7979 | 0.9724 |
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- | 0.6363 | 13.0 | 559 | 0.1208 | 0.7788 | 0.8333 | 0.8051 | 0.9732 |
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- | 0.6363 | 14.0 | 602 | 0.1161 | 0.7823 | 0.8333 | 0.8070 | 0.9736 |
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- | 0.6363 | 15.0 | 645 | 0.1148 | 0.7832 | 0.8333 | 0.8075 | 0.9737 |
 
 
 
 
 
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  ### Framework versions
 
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  This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0649
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+ - Precision: 0.8992
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+ - Recall: 0.9155
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+ - F1: 0.9072
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+ - Accuracy: 0.9862
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  ## Model description
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  - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 20
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  - mixed_precision_training: Native AMP
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  ### Training results
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 43 | 1.5391 | 0.0 | 0.0 | 0.0 | 0.8323 |
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+ | No log | 2.0 | 86 | 1.0087 | 0.0 | 0.0 | 0.0 | 0.8323 |
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+ | No log | 3.0 | 129 | 0.6795 | 0.0739 | 0.0338 | 0.0464 | 0.8375 |
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+ | No log | 4.0 | 172 | 0.5549 | 0.2447 | 0.2802 | 0.2613 | 0.8690 |
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+ | No log | 5.0 | 215 | 0.4249 | 0.4758 | 0.5821 | 0.5236 | 0.9183 |
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+ | No log | 6.0 | 258 | 0.3194 | 0.5484 | 0.6836 | 0.6086 | 0.9374 |
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+ | No log | 7.0 | 301 | 0.2431 | 0.6235 | 0.7379 | 0.6759 | 0.9502 |
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+ | No log | 8.0 | 344 | 0.1812 | 0.7525 | 0.8116 | 0.7809 | 0.9673 |
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+ | No log | 9.0 | 387 | 0.1548 | 0.7991 | 0.8357 | 0.8170 | 0.9705 |
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+ | No log | 10.0 | 430 | 0.1248 | 0.8182 | 0.8478 | 0.8327 | 0.9758 |
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+ | No log | 11.0 | 473 | 0.1104 | 0.8451 | 0.8696 | 0.8571 | 0.9786 |
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+ | 0.64 | 12.0 | 516 | 0.0965 | 0.8506 | 0.8732 | 0.8617 | 0.9804 |
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+ | 0.64 | 13.0 | 559 | 0.0909 | 0.8688 | 0.8877 | 0.8781 | 0.9820 |
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+ | 0.64 | 14.0 | 602 | 0.0819 | 0.8826 | 0.8986 | 0.8905 | 0.9837 |
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+ | 0.64 | 15.0 | 645 | 0.0779 | 0.8897 | 0.9058 | 0.8977 | 0.9850 |
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+ | 0.64 | 16.0 | 688 | 0.0734 | 0.8942 | 0.9082 | 0.9011 | 0.9852 |
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+ | 0.64 | 17.0 | 731 | 0.0700 | 0.8955 | 0.9106 | 0.9030 | 0.9856 |
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+ | 0.64 | 18.0 | 774 | 0.0666 | 0.8988 | 0.9118 | 0.9053 | 0.9861 |
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+ | 0.64 | 19.0 | 817 | 0.0655 | 0.8992 | 0.9155 | 0.9072 | 0.9862 |
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+ | 0.64 | 20.0 | 860 | 0.0649 | 0.8992 | 0.9155 | 0.9072 | 0.9862 |
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  ### Framework versions
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