| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: vit-base-patch16-224-pure-ViT |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.8714733542319749 |
| --- |
| |
| <!-- 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-pure-ViT |
|
|
| This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3270 |
| - Accuracy: 0.8715 |
|
|
| ## 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: 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.4676 | 1.0 | 202 | 0.4042 | 0.8095 | |
| | 0.4605 | 2.0 | 404 | 0.3675 | 0.8377 | |
| | 0.4012 | 3.0 | 606 | 0.3486 | 0.8506 | |
| | 0.3727 | 4.0 | 808 | 0.3413 | 0.8481 | |
| | 0.3482 | 5.0 | 1010 | 0.3339 | 0.8614 | |
| | 0.354 | 6.0 | 1212 | 0.3436 | 0.8561 | |
| | 0.3212 | 7.0 | 1414 | 0.3415 | 0.8534 | |
| | 0.3263 | 8.0 | 1616 | 0.3281 | 0.8642 | |
| | 0.285 | 9.0 | 1818 | 0.3263 | 0.8673 | |
| | 0.2779 | 10.0 | 2020 | 0.3270 | 0.8715 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.38.2 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
|
|
