--- license: apache-2.0 base_model: microsoft/beit-large-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: Boya2_3Class_RMSprop_1e5_20Epoch_Beit-large-224_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: 0.8600823045267489 --- # Boya2_3Class_RMSprop_1e5_20Epoch_Beit-large-224_fold1 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: 0.8616 - Accuracy: 0.8601 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.3225 | 1.0 | 914 | 0.3649 | 0.8442 | | 0.3719 | 2.0 | 1828 | 0.3320 | 0.8700 | | 0.2462 | 3.0 | 2742 | 0.4391 | 0.8565 | | 0.086 | 4.0 | 3656 | 0.7110 | 0.8606 | | 0.0239 | 5.0 | 4570 | 0.8616 | 0.8601 | ### Framework versions - Transformers 4.32.1 - Pytorch 2.0.1 - Datasets 2.12.0 - Tokenizers 0.13.2