--- license: apache-2.0 base_model: microsoft/beit-base-patch16-224-pt22k-ft22k tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-large-patch16_fold1 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: 0.6413250067879446 --- # Boya1_RMSProp_1-e5_20Epoch_09Momentum_Beit-large-patch16_fold1 This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 1.4588 - Accuracy: 0.6413 ## 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: 1e-05 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.372 | 1.0 | 924 | 1.3390 | 0.5422 | | 1.0566 | 2.0 | 1848 | 1.1838 | 0.5808 | | 0.8724 | 3.0 | 2772 | 1.1155 | 0.6248 | | 0.3326 | 4.0 | 3696 | 1.2344 | 0.6397 | | 0.254 | 5.0 | 4620 | 1.4588 | 0.6413 | ### Framework versions - Transformers 4.35.0 - Pytorch 2.1.0 - Datasets 2.14.6 - Tokenizers 0.14.1