--- license: apache-2.0 base_model: microsoft/swin-tiny-patch4-window7-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: swin-tiny-patch4-window7-224-Mid-NonMidMarket-Classification results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.3924731182795699 --- # swin-tiny-patch4-window7-224-Mid-NonMidMarket-Classification 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 imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 2.0567 - Accuracy: 0.3925 ## 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: 64 - eval_batch_size: 64 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 256 - 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 | 0.8889 | 6 | 2.8975 | 0.1398 | | 2.9658 | 1.9259 | 13 | 2.6866 | 0.2204 | | 2.6529 | 2.9630 | 20 | 2.4370 | 0.3011 | | 2.6529 | 4.0 | 27 | 2.2516 | 0.3495 | | 2.3311 | 4.8889 | 33 | 2.1685 | 0.3710 | | 2.1441 | 5.9259 | 40 | 2.0987 | 0.3656 | | 2.1441 | 6.9630 | 47 | 2.0567 | 0.3925 | | 2.0507 | 8.0 | 54 | 2.0416 | 0.3871 | | 1.988 | 8.8889 | 60 | 2.0368 | 0.3763 | ### Framework versions - Transformers 4.41.2 - Pytorch 1.13.1+cu117 - Datasets 2.19.2 - Tokenizers 0.19.1