--- library_name: transformers base_model: sxdave/plant_classification_model_1 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: results results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: train[:80%] args: default metrics: - name: Accuracy type: accuracy value: 0.9170731707317074 --- # results This model is a fine-tuned version of [sxdave/plant_classification_model_1](https://huggingface.co/sxdave/plant_classification_model_1) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.3907 - Accuracy: 0.9171 ## 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: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 4 ### Training results ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cu121 - Datasets 3.0.0 - Tokenizers 0.19.1