--- tags: - image-classification - timm - generated_from_trainer datasets: - beans metrics: - accuracy model_index: - name: timm-resnet18-beans-test results: - task: name: Image Classification type: image-classification dataset: name: beans type: beans args: default metric: name: Accuracy type: accuracy value: 0.3609022556390977 --- # timm-resnet18-beans-test This model is a fine-tuned version of [resnet18](https://huggingface.co/resnet18) on the beans dataset. It achieves the following results on the evaluation set: - Loss: 1.2126 - Accuracy: 0.3609 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - training_steps: 10 ### Training results ### Framework versions - Transformers 4.9.1 - Pytorch 1.9.0 - Datasets 1.11.1.dev0 - Tokenizers 0.10.3