--- license: apache-2.0 base_model: google/vit-huge-patch14-224-in21k tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: fashion-images-perspectives-vit-huge-patch14-224-in21k 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: 0.9149976711690732 --- # fashion-images-perspectives-vit-huge-patch14-224-in21k This model is a fine-tuned version of [google/vit-huge-patch14-224-in21k](https://huggingface.co/google/vit-huge-patch14-224-in21k) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.2710 - Accuracy: 0.9150 ## 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: 8 - eval_batch_size: 8 - seed: 1337 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.5932 | 1.0 | 3042 | 0.3863 | 0.8889 | | 0.4286 | 2.0 | 6084 | 0.4201 | 0.8642 | | 0.3628 | 3.0 | 9126 | 0.2820 | 0.9101 | | 0.3183 | 4.0 | 12168 | 0.2604 | 0.9150 | | 0.2648 | 5.0 | 15210 | 0.2710 | 0.9150 | ### Framework versions - Transformers 4.33.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3