--- license: apache-2.0 tags: - image-classification - generated_from_trainer metrics: - accuracy datasets: - chest X-rays widget: - src: https://drive.google.com/uc?id=1ygVCyEn6mfsNwpT1ZvWxANg5_DvStA7M example_title: PNEUMONIA - src: https://drive.google.com/uc?id=1xjcIEDb8kuSd4wF44gCEgsc0PfRvs53m example_title: NORMAL model-index: - name: vit-finetuned-chest-xray-pneumonia results: [] --- # vit-finetuned-chest-xray-pneumonia This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the [chest-xray-pneumonia](https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia) dataset. It achieves the following results on the evaluation set: - Loss: 0.1271 - Accuracy: 0.9551 ## 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: 2e-05 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | No log | 1.0 | 326 | 0.2739 | 0.9167 | | 0.2238 | 2.0 | 652 | 0.2892 | 0.9071 | | 0.2238 | 3.0 | 978 | 0.2077 | 0.9407 | | 0.1385 | 4.0 | 1304 | 0.1349 | 0.9535 | | 0.1347 | 5.0 | 1630 | 0.1271 | 0.9551 | | 0.1347 | 6.0 | 1956 | 0.1458 | 0.9535 | | 0.1112 | 7.0 | 2282 | 0.2040 | 0.9375 | | 0.1063 | 8.0 | 2608 | 0.1423 | 0.9567 | | 0.1063 | 9.0 | 2934 | 0.1473 | 0.9535 | | 0.0944 | 10.0 | 3260 | 0.1385 | 0.9583 | ## Example Images #### Pneumonia Chest X-Ray ![Pneumonia](https://drive.google.com/uc?id=1yqnhD4Wjt4Y_NGLtijTGGaaw9GL497kQ) #### Normal Chest X-Ray ![Normal](https://drive.google.com/uc?id=1xjcIEDb8kuSd4wF44gCEgsc0PfRvs53m) ### Framework versions - Transformers 4.17.0 - Pytorch 1.10.0+cu111 - Datasets 1.18.4 - Tokenizers 0.11.6