--- license: apache-2.0 base_model: facebook/deit-base-distilled-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: S2_M1_R3_deit_42509578 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: 0.9990333494441759 --- # S2_M1_R3_deit_42509578 This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/facebook/deit-base-distilled-patch16-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.0060 - Accuracy: 0.9990 ## 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: 16 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.0149 | 1.0 | 258 | 0.0100 | 0.9973 | | 0.004 | 2.0 | 517 | 0.0058 | 0.9988 | | 0.0097 | 3.0 | 776 | 0.0074 | 0.9986 | | 0.0002 | 4.0 | 1035 | 0.0041 | 0.9993 | | 0.0 | 4.99 | 1290 | 0.0060 | 0.9990 | ### Framework versions - Transformers 4.36.2 - Pytorch 1.11.0+cu102 - Datasets 2.16.0 - Tokenizers 0.15.0