--- 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: TransparentBagClassifier 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: 0.9820627802690582 --- # TransparentBagClassifier 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: 0.0517 - Accuracy: 0.9821 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.0694 | 1.0 | 158 | 0.0719 | 0.9821 | | 0.0871 | 2.0 | 316 | 0.0411 | 0.9955 | | 0.0561 | 3.0 | 474 | 0.0419 | 0.9910 | | 0.0673 | 4.0 | 632 | 0.0424 | 0.9865 | | 0.0099 | 5.0 | 790 | 0.0517 | 0.9821 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cpu - Datasets 3.0.0 - Tokenizers 0.19.1