--- license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: Tb_Dataset 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: 0.875 --- # Tb_Dataset 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: 0.4037 - Accuracy: 0.875 ## 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: 0.0002 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.0996 | 0.3067 | 100 | 1.0429 | 0.5625 | | 0.0481 | 0.6135 | 200 | 0.5665 | 0.8125 | | 0.0391 | 0.9202 | 300 | 1.0037 | 0.6875 | | 0.0711 | 1.2270 | 400 | 0.5200 | 0.875 | | 0.0258 | 1.5337 | 500 | 0.3818 | 0.9375 | | 0.0547 | 1.8405 | 600 | 0.3415 | 0.9375 | | 0.0029 | 2.1472 | 700 | 0.0637 | 0.9375 | | 0.0543 | 2.4540 | 800 | 0.7362 | 0.8125 | | 0.0265 | 2.7607 | 900 | 1.0917 | 0.75 | | 0.0017 | 3.0675 | 1000 | 0.0030 | 1.0 | | 0.0054 | 3.3742 | 1100 | 0.0364 | 1.0 | | 0.0234 | 3.6810 | 1200 | 0.2310 | 0.875 | | 0.0076 | 3.9877 | 1300 | 0.4037 | 0.875 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.20.0 - Tokenizers 0.19.1