| | --- |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - pierreguillou/DocLayNet-large |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | base_model: microsoft/layoutlmv3-base |
| | model-index: |
| | - name: layoutlmv3-finetuned-doclaynet |
| | results: |
| | - task: |
| | type: token-classification |
| | name: Token Classification |
| | dataset: |
| | name: pierreguillou/DocLayNet-large |
| | type: pierreguillou/DocLayNet-large |
| | args: doclaynet |
| | metrics: |
| | - type: precision |
| | value: 0.847 |
| | name: Precision |
| | - type: recall |
| | value: 0.893 |
| | name: Recall |
| | - type: f1 |
| | value: 0.870 |
| | name: F1 |
| | - type: accuracy |
| | value: 0.957 |
| | name: Accuracy |
| | --- |
| | |
| | # layoutlmv3-finetuned-funsd |
| |
|
| | 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 |
| | categories for lines (not for for paragraphs). |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.33888205885887146, |
| | - Precision: 0.8478835766832817, |
| | - Recall: 0.8934488524091807, |
| | - F1: 0.8700700634847538, |
| | - Accuracy: 0.9574140990541197 |
| |
|
| | The script for training can be found here: https://github.com/huggingface/transformers/tree/main/examples/research_projects/layoutlmv3 |
| | |
| | More information needed |
| | |
| | ## Training procedure |
| | |
| | ### Training hyperparameters |
| | |
| | The following hyperparameters were used during training: |
| | - learning_rate: 1e-05 |
| | - train_batch_size: 2 |
| | - eval_batch_size: 2 |
| | - training_steps: 100000 |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.33.3 |
| | - Pytorch 1.11.0+cu115 |
| | - Datasets 2.14.5 |
| | - Tokenizers 0.13.3 |
| | |
