--- license: cc-by-nc-sa-4.0 base_model: microsoft/layoutlmv3-base tags: - generated_from_trainer metrics: - precision - recall - f1 - accuracy model-index: - name: layoutlmv3-finetuned-language-levels-v5-4000 results: [] --- # layoutlmv3-finetuned-language-levels-v5-4000 This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0913 - Precision: 1.0 - Recall: 1.0 - F1: 1.0 - Accuracy: 0.9824 ## 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: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - training_steps: 4000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 0.2618 | 100 | 0.8184 | 0.9647 | 0.9630 | 0.9639 | 0.6971 | | No log | 0.5236 | 200 | 0.6254 | 0.9743 | 0.9815 | 0.9779 | 0.7404 | | No log | 0.7853 | 300 | 0.4760 | 0.9926 | 0.9944 | 0.9935 | 0.7981 | | No log | 1.0471 | 400 | 0.3675 | 0.9798 | 0.9889 | 0.9843 | 0.8910 | | 0.6763 | 1.3089 | 500 | 0.0913 | 1.0 | 1.0 | 1.0 | 0.9824 | | 0.6763 | 1.5707 | 600 | 0.0375 | 1.0 | 1.0 | 1.0 | 0.9904 | | 0.6763 | 1.8325 | 700 | 0.0149 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.6763 | 2.0942 | 800 | 0.0078 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.6763 | 2.3560 | 900 | 0.0047 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.037 | 2.6178 | 1000 | 0.0037 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.037 | 2.8796 | 1100 | 0.0030 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.037 | 3.1414 | 1200 | 0.0026 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.037 | 3.4031 | 1300 | 0.0022 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.037 | 3.6649 | 1400 | 0.0019 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0046 | 3.9267 | 1500 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0046 | 4.1885 | 1600 | 0.0016 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0046 | 4.4503 | 1700 | 0.0014 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0046 | 4.7120 | 1800 | 0.0013 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0046 | 4.9738 | 1900 | 0.0012 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0025 | 5.2356 | 2000 | 0.0011 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0025 | 5.4974 | 2100 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0025 | 5.7592 | 2200 | 0.0010 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0025 | 6.0209 | 2300 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0025 | 6.2827 | 2400 | 0.0009 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0017 | 6.5445 | 2500 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0017 | 6.8063 | 2600 | 0.0008 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0017 | 7.0681 | 2700 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0017 | 7.3298 | 2800 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0017 | 7.5916 | 2900 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0013 | 7.8534 | 3000 | 0.0007 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0013 | 8.1152 | 3100 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0013 | 8.3770 | 3200 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0013 | 8.6387 | 3300 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0013 | 8.9005 | 3400 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0011 | 9.1623 | 3500 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0011 | 9.4241 | 3600 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0011 | 9.6859 | 3700 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0011 | 9.9476 | 3800 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0011 | 10.2094 | 3900 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.001 | 10.4712 | 4000 | 0.0005 | 1.0 | 1.0 | 1.0 | 1.0 | ### Framework versions - Transformers 4.43.3 - Pytorch 2.1.0+cu118 - Datasets 2.20.0 - Tokenizers 0.19.1