--- license: apache-2.0 tags: - generated_from_trainer datasets: - image_folder metrics: - accuracy model-index: - name: swin-tiny-patch4-window7-224-finetuned-image_quality results: - task: name: Image Classification type: image-classification dataset: name: image_folder type: image_folder args: default metrics: - name: Accuracy type: accuracy value: 0.9090909090909091 --- # swin-tiny-patch4-window7-224-finetuned-image_quality This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the image_folder dataset. It achieves the following results on the evaluation set: - Loss: 0.5242 - Accuracy: 0.9091 ## 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: 5e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 1 | 0.6762 | 0.6364 | | No log | 2.0 | 2 | 0.6309 | 0.7273 | | No log | 3.0 | 3 | 0.6095 | 0.6364 | | No log | 4.0 | 4 | 0.5775 | 0.6364 | | No log | 5.0 | 5 | 0.5443 | 0.8182 | | No log | 6.0 | 6 | 0.5242 | 0.9091 | | No log | 7.0 | 7 | 0.5149 | 0.8182 | | No log | 8.0 | 8 | 0.5094 | 0.8182 | | No log | 9.0 | 9 | 0.5038 | 0.8182 | | 0.4095 | 10.0 | 10 | 0.4992 | 0.8182 | ### Framework versions - Transformers 4.19.4 - Pytorch 1.11.0+cu113 - Datasets 2.2.2 - Tokenizers 0.12.1