--- license: apache-2.0 base_model: google/vit-base-patch16-224 tags: - generated_from_trainer metrics: - accuracy model-index: - name: vit-base-patch16-224-finetuned-covid_ct_set_full results: [] --- # vit-base-patch16-224-finetuned-covid_ct_set_full 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: 0.1225 - Accuracy: 0.9627 ## 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: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.4343 | 0.99 | 29 | 0.1945 | 0.9298 | | 0.2353 | 1.98 | 58 | 0.2052 | 0.9290 | | 0.1395 | 2.97 | 87 | 0.2567 | 0.9075 | | 0.1399 | 4.0 | 117 | 0.1225 | 0.9627 | | 0.1186 | 4.96 | 145 | 0.1531 | 0.9521 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4 - Tokenizers 0.13.3