--- license: apache-2.0 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: blurred_landmarks results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: landmarks split: validation args: landmarks metrics: - name: Accuracy type: accuracy value: 0.9645365168539326 --- # blurred_landmarks This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 0.1152 - Accuracy: 0.9645 ## 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 - gradient_accumulation_steps: 4 - total_train_batch_size: 32 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 20 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.6588 | 1.0 | 357 | 0.6460 | 0.7707 | | 0.3752 | 2.0 | 714 | 0.2969 | 0.8933 | | 0.3275 | 3.0 | 1071 | 0.1912 | 0.9319 | | 0.2183 | 4.0 | 1429 | 0.1794 | 0.9305 | | 0.2133 | 5.0 | 1786 | 0.1638 | 0.9414 | | 0.1984 | 6.0 | 2143 | 0.1322 | 0.9484 | | 0.1409 | 7.0 | 2500 | 0.1304 | 0.9529 | | 0.1864 | 8.0 | 2858 | 0.1212 | 0.9572 | | 0.1778 | 9.0 | 3215 | 0.1216 | 0.9540 | | 0.1734 | 10.0 | 3572 | 0.1129 | 0.9593 | | 0.1349 | 11.0 | 3929 | 0.1127 | 0.9614 | | 0.1057 | 12.0 | 4287 | 0.1177 | 0.9582 | | 0.1434 | 13.0 | 4644 | 0.1153 | 0.9603 | | 0.0832 | 14.0 | 5001 | 0.1264 | 0.9593 | | 0.0963 | 15.0 | 5358 | 0.1146 | 0.9607 | | 0.0642 | 16.0 | 5716 | 0.1135 | 0.9635 | | 0.0763 | 17.0 | 6073 | 0.1210 | 0.9614 | | 0.0432 | 18.0 | 6430 | 0.1162 | 0.9645 | | 0.0618 | 19.0 | 6787 | 0.1269 | 0.9600 | | 0.049 | 19.99 | 7140 | 0.1152 | 0.9645 | ### Framework versions - Transformers 4.30.0.dev0 - Pytorch 1.13.0 - Datasets 2.10.1 - Tokenizers 0.11.0