--- license: apache-2.0 base_model: facebook/deit-tiny-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: hushem_40x_deit_tiny_deneme_f2 results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: test args: default metrics: - name: Accuracy type: accuracy value: 0.8 --- # hushem_40x_deit_tiny_deneme_f2 This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 1.3750 - Accuracy: 0.8 ## 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: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.1308 | 1.0 | 107 | 0.7189 | 0.8 | | 0.0468 | 2.0 | 214 | 1.0561 | 0.7556 | | 0.0127 | 2.99 | 321 | 1.2955 | 0.7333 | | 0.0392 | 4.0 | 429 | 1.0074 | 0.8222 | | 0.0002 | 5.0 | 536 | 1.2425 | 0.8222 | | 0.0 | 6.0 | 643 | 1.3825 | 0.7778 | | 0.0 | 6.99 | 750 | 1.3699 | 0.7778 | | 0.0 | 8.0 | 858 | 1.3717 | 0.7778 | | 0.0 | 9.0 | 965 | 1.3739 | 0.8 | | 0.0 | 9.98 | 1070 | 1.3750 | 0.8 | ### Framework versions - Transformers 4.35.0 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1