--- 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: 0.58125 --- # 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: 1.1599 - Accuracy: 0.5813 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 13 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 40 | 1.8887 | 0.35 | | No log | 2.0 | 80 | 1.5494 | 0.425 | | No log | 3.0 | 120 | 1.4015 | 0.5188 | | No log | 4.0 | 160 | 1.2919 | 0.55 | | No log | 5.0 | 200 | 1.2205 | 0.5813 | | No log | 6.0 | 240 | 1.2246 | 0.575 | | No log | 7.0 | 280 | 1.2053 | 0.5312 | | No log | 8.0 | 320 | 1.1487 | 0.5687 | | No log | 9.0 | 360 | 1.1727 | 0.5437 | | No log | 10.0 | 400 | 1.1459 | 0.55 | | No log | 11.0 | 440 | 1.1313 | 0.5813 | | No log | 12.0 | 480 | 1.0990 | 0.6062 | | 1.1138 | 13.0 | 520 | 1.1020 | 0.6188 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu121 - Datasets 2.16.1 - Tokenizers 0.15.1