Fashion Images Gender Age Vit Large Patch16 224 In21k v3

--- license: apache-2.0 base_model: google/vit-large-patch16-224-in21k tags: - image-classification - vision - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: fashion-images-gender-age-vit-large-patch16-224-in21k-v3 results: - task: name: Image Classification type: image-classification dataset: name: touchtech/fashion-images-gender-age type: imagefolder config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.9959630911188004 --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # fashion-images-gender-age-vit-large-patch16-224-in21k-v3 This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on the touchtech/fashion-images-gender-age dataset. It achieves the following results on the evaluation set: - Loss: 0.0223 - Accuracy: 0.9960 ## 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 | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.1868 | 1.0 | 2457 | 0.0547 | 0.9853 | | 0.1209 | 2.0 | 4914 | 0.0401 | 0.9888 | | 0.1027 | 3.0 | 7371 | 0.0262 | 0.9937 | | 0.0654 | 4.0 | 9828 | 0.0223 | 0.9960 | | 0.0542 | 5.0 | 12285 | 0.0273 | 0.9948 | ### Framework versions - Transformers 4.33.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.13.3