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--- |
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tags: |
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- generated_from_trainer |
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datasets: |
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- pierreguillou/DocLayNet-large |
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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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base_model: microsoft/layoutlmv3-base |
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model-index: |
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- name: layoutlmv3-finetuned-doclaynet |
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results: |
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- task: |
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type: token-classification |
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name: Token Classification |
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dataset: |
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name: pierreguillou/DocLayNet-large |
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type: pierreguillou/DocLayNet-large |
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args: doclaynet |
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metrics: |
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- type: precision |
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value: 0.847 |
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name: Precision |
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- type: recall |
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value: 0.893 |
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name: Recall |
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- type: f1 |
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value: 0.870 |
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name: F1 |
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- type: accuracy |
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value: 0.957 |
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name: Accuracy |
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--- |
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# layoutlmv3-finetuned-funsd |
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This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the pierreguillou/DocLayNet-large using bounding boxes and |
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categories for lines (not for for paragraphs). |
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It achieves the following results on the evaluation set: |
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- Loss: 0.33888205885887146, |
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- Precision: 0.8478835766832817, |
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- Recall: 0.8934488524091807, |
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- F1: 0.8700700634847538, |
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- Accuracy: 0.9574140990541197 |
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The script for training can be found here: https://github.com/huggingface/transformers/tree/main/examples/research_projects/layoutlmv3 |
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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: 2 |
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- eval_batch_size: 2 |
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- training_steps: 100000 |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 1.11.0+cu115 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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