| --- |
| license: apache-2.0 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: vit-base-patch16-224 |
| 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. --> |
|
|
| # vit-base-patch16-224 |
|
|
| This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.2817 |
| - Accuracy: 0.7205 |
|
|
| ## 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: 0.001 |
| - 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: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.8025 | 0.98 | 27 | 0.6852 | 0.6407 | |
| | 0.5648 | 1.98 | 54 | 0.7587 | 0.6971 | |
| | 0.2165 | 2.98 | 81 | 0.6410 | 0.7387 | |
| | 0.0587 | 3.98 | 108 | 1.9350 | 0.5682 | |
| | 0.041 | 4.98 | 135 | 0.9925 | 0.7348 | |
| | 0.013 | 5.98 | 162 | 1.3159 | 0.6980 | |
| | 0.025 | 6.98 | 189 | 1.4855 | 0.7456 | |
| | 0.0243 | 7.98 | 216 | 1.4230 | 0.7489 | |
| | 0.0016 | 8.98 | 243 | 1.2937 | 0.7117 | |
| | 0.0026 | 9.98 | 270 | 1.2817 | 0.7205 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.25.1 |
| - Pytorch 1.13.0+cu116 |
| - Datasets 2.7.1 |
| - Tokenizers 0.13.2 |
|
|
