--- license: apache-2.0 base_model: facebook/convnextv2-base-1k-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: Expert2-leaf-disease-convnextv2-base-1k-224-1_2_3 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: 0.9390862944162437 --- # Expert2-leaf-disease-convnextv2-base-1k-224-1_2_3 This model is a fine-tuned version of [facebook/convnextv2-base-1k-224](https://huggingface.co/facebook/convnextv2-base-1k-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.1892 - Accuracy: 0.9391 ## 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: 300 - eval_batch_size: 300 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 1200 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 16 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.5107 | 0.96 | 13 | 1.0756 | 0.7422 | | 1.0022 | 2.0 | 27 | 0.5781 | 0.7603 | | 0.4503 | 2.96 | 40 | 0.3902 | 0.8697 | | 0.3704 | 4.0 | 54 | 0.3101 | 0.9058 | | 0.2996 | 4.96 | 67 | 0.2573 | 0.9165 | | 0.2405 | 6.0 | 81 | 0.2647 | 0.9075 | | 0.2268 | 6.96 | 94 | 0.2259 | 0.9233 | | 0.2036 | 8.0 | 108 | 0.2126 | 0.9329 | | 0.1957 | 8.96 | 121 | 0.2149 | 0.9329 | | 0.1885 | 10.0 | 135 | 0.1974 | 0.9385 | | 0.1866 | 10.96 | 148 | 0.1983 | 0.9318 | | 0.1771 | 12.0 | 162 | 0.2066 | 0.9363 | | 0.1752 | 12.96 | 175 | 0.1975 | 0.9357 | | 0.1744 | 14.0 | 189 | 0.1893 | 0.9380 | | 0.1636 | 14.96 | 202 | 0.1889 | 0.9391 | | 0.1636 | 15.41 | 208 | 0.1892 | 0.9391 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.1 - Datasets 2.18.0 - Tokenizers 0.15.1