--- license: apache-2.0 base_model: microsoft/beit-large-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: Karma_3Class_RMSprop_1e4_20Epoch_Beit-large-224_fold5 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: 0.7145176017043725 --- # Karma_3Class_RMSprop_1e4_20Epoch_Beit-large-224_fold5 This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.6636 - Accuracy: 0.7145 ## 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: 0.0001 - train_batch_size: 16 - eval_batch_size: 16 - seed: 42 - 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 | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.8273 | 1.0 | 2468 | 0.9004 | 0.6351 | | 0.7414 | 2.0 | 4936 | 0.7419 | 0.6871 | | 0.7552 | 3.0 | 7404 | 0.7070 | 0.6918 | | 0.5357 | 4.0 | 9872 | 0.6848 | 0.7067 | | 0.6387 | 5.0 | 12340 | 0.6636 | 0.7145 | ### Framework versions - Transformers 4.32.1 - Pytorch 2.0.1 - Datasets 2.12.0 - Tokenizers 0.13.2