--- library_name: transformers license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: Image-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: 0.46875 --- # Image-Classification This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 1.4789 - Accuracy: 0.4688 ## 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 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 15 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 20 | 1.9690 | 0.2812 | | No log | 2.0 | 40 | 1.7928 | 0.4 | | No log | 3.0 | 60 | 1.6533 | 0.4313 | | No log | 4.0 | 80 | 1.5701 | 0.45 | | No log | 5.0 | 100 | 1.5244 | 0.45 | | No log | 6.0 | 120 | 1.4789 | 0.4688 | | No log | 7.0 | 140 | 1.4781 | 0.4688 | | No log | 8.0 | 160 | 1.4793 | 0.4375 | | No log | 9.0 | 180 | 1.4670 | 0.4375 | | No log | 10.0 | 200 | 1.5136 | 0.45 | | No log | 11.0 | 220 | 1.5041 | 0.45 | | No log | 12.0 | 240 | 1.5178 | 0.4437 | | No log | 13.0 | 260 | 1.5302 | 0.4437 | | No log | 14.0 | 280 | 1.5348 | 0.45 | | No log | 15.0 | 300 | 1.5386 | 0.45 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.0+cu121 - Datasets 2.21.0 - Tokenizers 0.19.1