--- license: apache-2.0 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy - f1 - recall - precision model-index: - name: Brain_Tumor_Class_swin 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: 0.9936204146730463 - name: F1 type: f1 value: 0.9936204146730463 - name: Recall type: recall value: 0.9936204146730463 - name: Precision type: precision value: 0.9936204146730463 --- # Brain_Tumor_Class_swin This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.0220 - Accuracy: 0.9936 - F1: 0.9936 - Recall: 0.9936 - Precision: 0.9936 ## 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: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| | 0.1248 | 1.0 | 220 | 0.0610 | 0.9767 | 0.9767 | 0.9767 | 0.9767 | | 0.0887 | 2.0 | 440 | 0.0300 | 0.9920 | 0.9920 | 0.9920 | 0.9920 | | 0.0449 | 3.0 | 660 | 0.0220 | 0.9936 | 0.9936 | 0.9936 | 0.9936 | ### Framework versions - Transformers 4.23.1 - Pytorch 1.12.1 - Datasets 2.6.1 - Tokenizers 0.13.1