--- license: mit base_model: naver-clova-ix/donut-base tags: - generated_from_trainer datasets: - imagefolder model-index: - name: donut-base2-sroie results: [] --- # donut-base2-sroie This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 1.3234 ## 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: 2e-05 - train_batch_size: 2 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 4.1171 | 1.0 | 73 | 3.5216 | | 2.6172 | 2.0 | 146 | 1.8420 | | 2.1784 | 3.0 | 219 | 1.3622 | | 1.0188 | 4.0 | 292 | 1.2344 | | 0.8844 | 5.0 | 365 | 1.2448 | | 0.4622 | 6.0 | 438 | 1.1840 | | 0.8648 | 7.0 | 511 | 1.2136 | | 0.4117 | 8.0 | 584 | 1.2452 | | 0.2687 | 9.0 | 657 | 1.2622 | | 0.4633 | 10.0 | 730 | 1.2959 | | 0.4606 | 11.0 | 803 | 1.3234 | ### Framework versions - Transformers 4.34.1 - Pytorch 2.1.0+cu118 - Datasets 2.14.5 - Tokenizers 0.14.1