--- license: apache-2.0 base_model: google/vit-base-patch16-224 tags: - generated_from_trainer metrics: - accuracy model-index: - name: vit-base-patch16-224-MSC-dmae results: [] datasets: - Augusto777/dmae-dataset-DA --- # vit-base-patch16-224-MSC-dmae This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.6300 - Accuracy: 0.95 ## 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 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 12 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 0.67 | 1 | 1.2258 | 0.5 | | No log | 2.0 | 3 | 1.0536 | 0.7 | | No log | 2.67 | 4 | 0.9143 | 0.75 | | No log | 4.0 | 6 | 0.6899 | 0.9 | | No log | 4.67 | 7 | 0.6300 | 0.95 | | No log | 6.0 | 9 | 0.5069 | 0.9 | | 0.8554 | 6.67 | 10 | 0.4671 | 0.9 | | 0.8554 | 8.0 | 12 | 0.4312 | 0.9 | ### Framework versions - Transformers 4.33.2 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.13.3