--- license: apache-2.0 base_model: google/vit-base-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: vit-base-patch16-224-RU3-10 results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: validation args: default metrics: - name: Accuracy type: accuracy value: 0.7833333333333333 --- # vit-base-patch16-224-RU3-10 This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.6241 - Accuracy: 0.7833 ## 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: 5.5e-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: 0.05 - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.3698 | 0.99 | 19 | 1.1845 | 0.65 | | 1.1232 | 1.97 | 38 | 0.9393 | 0.65 | | 0.8168 | 2.96 | 57 | 0.9117 | 0.6333 | | 0.5992 | 4.0 | 77 | 0.8330 | 0.7333 | | 0.4258 | 4.99 | 96 | 0.7471 | 0.7 | | 0.3283 | 5.97 | 115 | 0.6241 | 0.7833 | | 0.2543 | 6.96 | 134 | 0.5916 | 0.7833 | | 0.2345 | 8.0 | 154 | 0.6783 | 0.7833 | | 0.2027 | 8.99 | 173 | 0.6577 | 0.7833 | | 0.1733 | 9.87 | 190 | 0.6589 | 0.7833 | ### Framework versions - Transformers 4.36.2 - Pytorch 2.1.2+cu118 - Datasets 2.16.1 - Tokenizers 0.15.0