| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - image_folder | |
| model-index: | |
| - name: vc-bantai-vit-withoutAMBI | |
| results: [] | |
| <!-- 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. --> | |
| # vc-bantai-vit-withoutAMBI | |
| 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: | |
| - eval_loss: 0.2578 | |
| - eval_accuracy: 0.9533 | |
| - eval_runtime: 31.6691 | |
| - eval_samples_per_second: 130.443 | |
| - eval_steps_per_second: 2.052 | |
| - epoch: 270.26 | |
| - step: 10000 | |
| ## 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: 64 | |
| - eval_batch_size: 64 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 4 | |
| - total_train_batch_size: 256 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_ratio: 0.1 | |
| - num_epochs: 500 | |
| ### Framework versions | |
| - Transformers 4.19.2 | |
| - Pytorch 1.11.0+cu113 | |
| - Datasets 2.2.2 | |
| - Tokenizers 0.12.1 | |