--- tags: - generated_from_trainer datasets: - generated metrics: - precision - recall - f1 - accuracy model-index: - name: layoutlmv3-finetuned-invoice 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 --- # layoutlmv3-finetuned-invoice This model was trained from scratch on the generated dataset. It achieves the following results on the evaluation set: - Loss: 0.0000 - 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: 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: 750 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 2.0 | 100 | 0.0092 | 0.9959 | 0.9919 | 0.9939 | 0.9992 | | No log | 4.0 | 200 | 0.0069 | 0.9959 | 0.9919 | 0.9939 | 0.9992 | | No log | 6.0 | 300 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | | No log | 8.0 | 400 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0005 | 10.0 | 500 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0005 | 12.0 | 600 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0005 | 14.0 | 700 | 0.0000 | 1.0 | 1.0 | 1.0 | 1.0 | ### Framework versions - Transformers 4.32.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.3 - Tokenizers 0.13.3