| license: apache-2.0 | |
| tags: | |
| - image-classification | |
| - vision | |
| - generated_from_trainer | |
| datasets: | |
| - mnist | |
| metrics: | |
| - accuracy | |
| base_model: google/vit-base-patch16-224-in21k | |
| model-index: | |
| - name: mnist-digit-classification-2022-09-04 | |
| results: | |
| - task: | |
| type: image-classification | |
| name: Image Classification | |
| dataset: | |
| name: mnist | |
| type: mnist | |
| config: mnist | |
| split: train | |
| args: mnist | |
| metrics: | |
| - type: accuracy | |
| value: 0.9923333333333333 | |
| name: Accuracy | |
| <!-- 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. --> | |
| # mnist-digit-classification-2022-09-04 | |
| 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 mnist dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0319 | |
| - Accuracy: 0.9923 | |
| ## 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: 2e-05 | |
| - train_batch_size: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 5.0 | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.22.0.dev0 | |
| - Pytorch 1.12.1+cu102 | |
| - Datasets 2.4.0 | |
| - Tokenizers 0.12.1 | |