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README.md
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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: layoutlmv3-invoice-parser
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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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# layoutlmv3-invoice-parser
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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: 0.5061
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- Precision: 0.8242
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- Recall: 0.8936
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- F1: 0.8575
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- Accuracy: 0.8323
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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: 2e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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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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- num_epochs: 5
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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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| 1.6703 | 1.0 | 38 | 0.7898 | 0.7234 | 0.8246 | 0.7707 | 0.7616 |
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| 0.7077 | 2.0 | 76 | 0.6175 | 0.7751 | 0.8525 | 0.8120 | 0.7997 |
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| 0.4946 | 3.0 | 114 | 0.5219 | 0.7856 | 0.8784 | 0.8294 | 0.8223 |
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| 0.3819 | 4.0 | 152 | 0.5089 | 0.8109 | 0.8824 | 0.8451 | 0.8293 |
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| 0.3178 | 5.0 | 190 | 0.5061 | 0.8242 | 0.8936 | 0.8575 | 0.8323 |
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### Framework versions
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- Transformers 5.15.0
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- Pytorch 2.11.0+cu128
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- Datasets 4.0.0
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- Tokenizers 0.22.2
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