--- license: apache-2.0 base_model: microsoft/beit-base-patch16-224-pt22k tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: finetuned-Leukemia-cell 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: 0.9624060150375939 --- # finetuned-Leukemia-cell This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.0946 - Accuracy: 0.9624 ## 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: 0.0002 - train_batch_size: 32 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 20 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.9733 | 2.94 | 100 | 0.8894 | 0.7256 | | 0.7184 | 5.88 | 200 | 0.7876 | 0.7293 | | 0.5299 | 8.82 | 300 | 0.5183 | 0.8609 | | 0.3991 | 11.76 | 400 | 0.3121 | 0.8947 | | 0.2263 | 14.71 | 500 | 0.1337 | 0.9549 | | 0.1782 | 17.65 | 600 | 0.0946 | 0.9624 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu118 - Datasets 2.15.0 - Tokenizers 0.15.0