--- license: cc-by-nc-sa-4.0 tags: - generated_from_trainer model-index: - name: lmv2ubiai-pan8doc-06-11 results: [] --- # lmv2ubiai-pan8doc-06-11 This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.9633 - Dob Precision: 1.0 - Dob Recall: 1.0 - Dob F1: 1.0 - Dob Number: 2 - Fname Precision: 0.6667 - Fname Recall: 1.0 - Fname F1: 0.8 - Fname Number: 2 - Name Precision: 1.0 - Name Recall: 1.0 - Name F1: 1.0 - Name Number: 2 - Pan Precision: 1.0 - Pan Recall: 1.0 - Pan F1: 1.0 - Pan Number: 2 - Overall Precision: 0.8889 - Overall Recall: 1.0 - Overall F1: 0.9412 - Overall Accuracy: 0.9821 ## 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: 4e-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: constant - num_epochs: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | Dob Precision | Dob Recall | Dob F1 | Dob Number | Fname Precision | Fname Recall | Fname F1 | Fname Number | Name Precision | Name Recall | Name F1 | Name Number | Pan Precision | Pan Recall | Pan F1 | Pan Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |:-------------:|:-----:|:----:|:---------------:|:-------------:|:----------:|:------:|:----------:|:---------------:|:------------:|:--------:|:------------:|:--------------:|:-----------:|:-------:|:-----------:|:-------------:|:----------:|:------:|:----------:|:-----------------:|:--------------:|:----------:|:----------------:| | 2.1195 | 1.0 | 6 | 1.7519 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 0.7857 | | 1.6994 | 2.0 | 12 | 1.5117 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 0.7857 | | 1.5521 | 3.0 | 18 | 1.4130 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 0.7857 | | 1.4726 | 4.0 | 24 | 1.3410 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 0.7857 | | 1.395 | 5.0 | 30 | 1.2693 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 0.7857 | | 1.3131 | 6.0 | 36 | 1.2079 | 1.0 | 1.0 | 1.0 | 2 | 0.1667 | 0.5 | 0.25 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.0 | 0.0 | 0.0 | 2 | 0.3 | 0.375 | 0.3333 | 0.8929 | | 1.2474 | 7.0 | 42 | 1.1495 | 1.0 | 1.0 | 1.0 | 2 | 0.2 | 0.5 | 0.2857 | 2 | 0.0 | 0.0 | 0.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.4167 | 0.625 | 0.5 | 0.9286 | | 1.1869 | 8.0 | 48 | 1.0942 | 1.0 | 1.0 | 1.0 | 2 | 0.2 | 0.5 | 0.2857 | 2 | 0.0 | 0.0 | 0.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.4167 | 0.625 | 0.5 | 0.9286 | | 1.1369 | 9.0 | 54 | 1.0453 | 1.0 | 1.0 | 1.0 | 2 | 0.4 | 1.0 | 0.5714 | 2 | 0.0 | 0.0 | 0.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5455 | 0.75 | 0.6316 | 0.9464 | | 1.0882 | 10.0 | 60 | 1.0054 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 1.0 | 0.6667 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.7 | 0.875 | 0.7778 | 0.9643 | | 1.0482 | 11.0 | 66 | 0.9633 | 1.0 | 1.0 | 1.0 | 2 | 0.6667 | 1.0 | 0.8 | 2 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.8889 | 1.0 | 0.9412 | 0.9821 | | 1.017 | 12.0 | 72 | 0.9368 | 1.0 | 1.0 | 1.0 | 2 | 0.6667 | 1.0 | 0.8 | 2 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.8889 | 1.0 | 0.9412 | 0.9643 | | 0.9825 | 13.0 | 78 | 0.9139 | 1.0 | 1.0 | 1.0 | 2 | 0.6667 | 1.0 | 0.8 | 2 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.8889 | 1.0 | 0.9412 | 0.9821 | | 0.9459 | 14.0 | 84 | 0.8837 | 1.0 | 1.0 | 1.0 | 2 | 0.6667 | 1.0 | 0.8 | 2 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.8889 | 1.0 | 0.9412 | 0.9643 | | 0.9155 | 15.0 | 90 | 0.8472 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | | 0.8819 | 16.0 | 96 | 0.8231 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | | 0.8523 | 17.0 | 102 | 0.7957 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.6667 | 1.0 | 0.8 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.8889 | 1.0 | 0.9412 | 0.9821 | | 0.8251 | 18.0 | 108 | 0.7681 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | | 0.7982 | 19.0 | 114 | 0.7533 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | | 0.7762 | 20.0 | 120 | 0.7283 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | | 0.7558 | 21.0 | 126 | 0.7114 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | | 0.7346 | 22.0 | 132 | 0.6889 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | | 0.7116 | 23.0 | 138 | 0.6697 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | | 0.6898 | 24.0 | 144 | 0.6593 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | | 0.6748 | 25.0 | 150 | 0.6356 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | | 0.6487 | 26.0 | 156 | 0.6142 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | | 0.6312 | 27.0 | 162 | 0.6008 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | | 0.6156 | 28.0 | 168 | 0.5855 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | | 0.5961 | 29.0 | 174 | 0.5625 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | | 0.5781 | 30.0 | 180 | 0.5553 | 1.0 | 1.0 | 1.0 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.5 | 0.5 | 0.5 | 2 | 1.0 | 1.0 | 1.0 | 2 | 0.875 | 0.875 | 0.875 | 0.9643 | ### Framework versions - Transformers 4.20.0.dev0 - Pytorch 1.11.0+cu113 - Datasets 2.2.2 - Tokenizers 0.12.1