--- library_name: peft license: apache-2.0 base_model: google/vit-large-patch16-224 tags: - image-classification - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: vit-large-patch16-224-testing-dungeons-lora-23Nov24-0010 results: - task: type: image-classification name: Image Classification dataset: name: rotated_maps type: imagefolder config: default split: validation args: default metrics: - type: accuracy value: 1.0 name: Accuracy --- # vit-large-patch16-224-testing-dungeons-lora-23Nov24-0010 This model is a fine-tuned version of [google/vit-large-patch16-224](https://huggingface.co/google/vit-large-patch16-224) on the rotated_maps dataset. It achieves the following results on the evaluation set: - Loss: 0.0977 - Accuracy: 1.0 ## 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: 0.005 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 12 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | No log | 0.6667 | 1 | 1.4309 | 0.2963 | | No log | 2.0 | 3 | 1.1590 | 0.5926 | | No log | 2.6667 | 4 | 0.7057 | 0.8148 | | No log | 4.0 | 6 | 0.4692 | 0.8148 | | No log | 4.6667 | 7 | 0.2285 | 0.9630 | | No log | 6.0 | 9 | 0.2492 | 0.8889 | | 0.7456 | 6.6667 | 10 | 0.1295 | 1.0 | | 0.7456 | 8.0 | 12 | 0.0977 | 1.0 | ### Framework versions - PEFT 0.13.2 - Transformers 4.46.2 - Pytorch 2.5.1+cu121 - Datasets 3.1.0 - Tokenizers 0.20.3