--- license: cc-by-nc-sa-4.0 base_model: microsoft/layoutlmv3-base tags: - generated_from_trainer datasets: - generated metrics: - precision - recall - f1 - accuracy model-index: - name: document-data-extraction-layoutlmv3 results: - task: name: Token Classification type: token-classification dataset: name: generated type: generated config: sroie split: test args: sroie metrics: - name: Precision type: precision value: 1.0 - name: Recall type: recall value: 1.0 - name: F1 type: f1 value: 1.0 - name: Accuracy type: accuracy value: 1.0 --- # document-data-extraction-layoutlmv3 This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the generated dataset. It achieves the following results on the evaluation set: - Loss: 0.0015 - Precision: 1.0 - Recall: 1.0 - F1: 1.0 - Accuracy: 1.0 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 1e-05 - train_batch_size: 1 - eval_batch_size: 1 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - training_steps: 2000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 100 | 0.1114 | 0.95 | 0.9635 | 0.9567 | 0.9947 | | No log | 2.0 | 200 | 0.0286 | 0.972 | 0.9858 | 0.9789 | 0.9971 | | No log | 3.0 | 300 | 0.0184 | 0.972 | 0.9858 | 0.9789 | 0.9971 | | No log | 4.0 | 400 | 0.0163 | 0.972 | 0.9858 | 0.9789 | 0.9971 | | 0.1385 | 5.0 | 500 | 0.0141 | 0.972 | 0.9858 | 0.9789 | 0.9971 | | 0.1385 | 6.0 | 600 | 0.0123 | 0.972 | 0.9858 | 0.9789 | 0.9971 | | 0.1385 | 7.0 | 700 | 0.0122 | 0.972 | 0.9858 | 0.9789 | 0.9971 | | 0.1385 | 8.0 | 800 | 0.0108 | 0.972 | 0.9858 | 0.9789 | 0.9971 | | 0.1385 | 9.0 | 900 | 0.0104 | 0.972 | 0.9858 | 0.9789 | 0.9971 | | 0.0119 | 10.0 | 1000 | 0.0113 | 0.972 | 0.9858 | 0.9789 | 0.9971 | | 0.0119 | 11.0 | 1100 | 0.0080 | 0.974 | 0.9878 | 0.9809 | 0.9973 | | 0.0119 | 12.0 | 1200 | 0.0089 | 0.9856 | 0.9736 | 0.9796 | 0.9973 | | 0.0119 | 13.0 | 1300 | 0.0034 | 0.9959 | 0.9959 | 0.9959 | 0.9994 | | 0.0119 | 14.0 | 1400 | 0.0037 | 0.9980 | 0.9939 | 0.9959 | 0.9994 | | 0.006 | 15.0 | 1500 | 0.0024 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | | 0.006 | 16.0 | 1600 | 0.0019 | 0.9980 | 1.0 | 0.9990 | 0.9998 | | 0.006 | 17.0 | 1700 | 0.0022 | 0.9960 | 0.9980 | 0.9970 | 0.9996 | | 0.006 | 18.0 | 1800 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.006 | 19.0 | 1900 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0027 | 20.0 | 2000 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 | ### Framework versions - Transformers 4.36.0.dev0 - Pytorch 2.1.1+cu121 - Datasets 2.15.0 - Tokenizers 0.15.0