--- license: apache-2.0 tags: - image-classification - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: croupier-creature-classifier results: - task: name: Image Classification type: image-classification dataset: name: croupier-mtg-dataset type: imagefolder config: alkzar90--croupier-mtg-dataset split: train args: alkzar90--croupier-mtg-dataset metrics: - name: Accuracy type: accuracy value: 0.7411764705882353 --- # croupier-creature-classifier 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 croupier-mtg-dataset dataset. It achieves the following results on the evaluation set: - Loss: 0.6702 - Accuracy: 0.7412 ## 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: 6 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.8932 | 1.1 | 100 | 0.9914 | 0.6059 | | 0.6608 | 2.2 | 200 | 0.8645 | 0.6588 | | 0.6084 | 3.3 | 300 | 0.7326 | 0.7294 | | 0.5261 | 4.4 | 400 | 0.7684 | 0.6941 | | 0.2511 | 5.49 | 500 | 0.7184 | 0.7059 | ### Framework versions - Transformers 4.21.1 - Pytorch 1.12.0+cu113 - Datasets 2.4.0 - Tokenizers 0.12.1