| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - image_folder | |
| metrics: | |
| - accuracy | |
| model-index: | |
| - name: vit-airplanes | |
| results: | |
| - task: | |
| name: Image Classification | |
| type: image-classification | |
| dataset: | |
| name: image_folder | |
| type: image_folder | |
| args: default | |
| metrics: | |
| - name: Accuracy | |
| type: accuracy | |
| value: 1.0 | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # vit-airplanes | |
| This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co./google/vit-base-patch16-224-in21k) on the image_folder dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0152 | |
| - Accuracy: 1.0 | |
| ## 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: 0.0002 | |
| - train_batch_size: 16 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 4 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| | 0.0165 | 2.38 | 100 | 0.0152 | 1.0 | | |
| ### Framework versions | |
| - Transformers 4.18.0 | |
| - Pytorch 1.10.0+cu111 | |
| - Datasets 2.0.0 | |
| - Tokenizers 0.11.6 | |