--- license: apache-2.0 base_model: microsoft/beit-base-patch16-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: S1_M1_R2_beit_42507358 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: 0.5117813383600377 --- # S1_M1_R2_beit_42507358 This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: nan - Accuracy: 0.5118 ## 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: 16 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.0 | 0.99 | 66 | nan | 0.5118 | | 0.0 | 2.0 | 133 | nan | 0.5118 | | 0.0 | 2.99 | 199 | nan | 0.5118 | | 0.0 | 4.0 | 266 | nan | 0.5118 | | 0.0 | 4.96 | 330 | nan | 0.5118 | ### Framework versions - Transformers 4.36.2 - Pytorch 1.11.0+cu102 - Datasets 2.16.0 - Tokenizers 0.15.0