--- library_name: transformers 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-ap7_11_stitched_16_batch_4e5 results: [] --- # layoutlmv3-ap7_11_stitched_16_batch_4e5 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: 0.0229 - Precision: 0.9565 - Recall: 0.7857 - F1: 0.8627 - Accuracy: 0.9975 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - training_steps: 1000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | 0.2919 | 50.0 | 250 | 0.0264 | 0.68 | 0.6071 | 0.6415 | 0.9963 | | 0.0045 | 100.0 | 500 | 0.0229 | 0.9565 | 0.7857 | 0.8627 | 0.9975 | | 0.0012 | 150.0 | 750 | 0.0282 | 0.7059 | 0.8571 | 0.7742 | 0.9961 | | 0.0008 | 200.0 | 1000 | 0.0244 | 0.8214 | 0.8214 | 0.8214 | 0.9970 | ### Framework versions - Transformers 4.49.0 - Pytorch 2.6.0+cu124 - Datasets 3.4.1 - Tokenizers 0.21.1