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--- |
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library_name: transformers |
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license: cc-by-nc-sa-4.0 |
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base_model: microsoft/layoutlmv3-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: Layoutlmv3InvoiceCzech |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Layoutlmv3InvoiceCzech |
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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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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 2 |
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- seed: 42 |
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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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- Transformers 4.57.6 |
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- Pytorch 2.9.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.2 |
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