--- license: apache-2.0 base_model: facebook/convnext-tiny-224 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: convnext-tiny-224-finetuned-eurosat-albumentations 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: 0.9818518518518519 --- # convnext-tiny-224-finetuned-eurosat-albumentations This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.0604 - Accuracy: 0.9819 ## 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: 32 - eval_batch_size: 32 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.1496 | 1.0 | 190 | 0.1372 | 0.9693 | | 0.0785 | 2.0 | 380 | 0.0715 | 0.9807 | | 0.0617 | 3.0 | 570 | 0.0604 | 0.9819 | ### Framework versions - Transformers 4.40.0.dev0 - Pytorch 2.1.0+cu121 - Datasets 2.18.0 - Tokenizers 0.15.0