--- license: apache-2.0 base_model: microsoft/resnet-152 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: resnet-152-finetuned-cassava-leaf-disease 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: 0.3560747663551402 --- # resnet-152-finetuned-cassava-leaf-disease This model is a fine-tuned version of [microsoft/resnet-152](https://huggingface.co/microsoft/resnet-152) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 4.1197 - Accuracy: 0.3561 ## 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: 200 - eval_batch_size: 200 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 800 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 6.4984 | 0.99 | 24 | 5.4849 | 0.0771 | | 5.2526 | 1.98 | 48 | 4.2884 | 0.3290 | | 4.118 | 2.97 | 72 | 4.1197 | 0.3561 | ### Framework versions - Transformers 4.37.2 - Pytorch 2.2.1 - Datasets 2.18.0 - Tokenizers 0.15.1