| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: attraction-classifier |
| 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: 0.8242677824267782 |
| --- |
| |
| <!-- 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. --> |
|
|
| # attraction-classifier |
|
|
| 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 imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.4274 |
| - Accuracy: 0.8243 |
|
|
| ## 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: 69 |
| - gradient_accumulation_steps: 16 |
| - total_train_batch_size: 512 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.05 |
| - num_epochs: 25 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.6782 | 1.78 | 15 | 0.5922 | 0.7008 | |
| | 0.5096 | 3.56 | 30 | 0.5153 | 0.7552 | |
| | 0.4434 | 5.33 | 45 | 0.4520 | 0.7762 | |
| | 0.3844 | 7.11 | 60 | 0.4381 | 0.8013 | |
| | 0.3642 | 8.89 | 75 | 0.4359 | 0.8054 | |
| | 0.322 | 10.67 | 90 | 0.4086 | 0.8138 | |
| | 0.2845 | 12.44 | 105 | 0.4111 | 0.8201 | |
| | 0.2588 | 14.22 | 120 | 0.4100 | 0.8159 | |
| | 0.2516 | 16.0 | 135 | 0.4122 | 0.8389 | |
| | 0.2375 | 17.78 | 150 | 0.4085 | 0.8243 | |
| | 0.2309 | 19.56 | 165 | 0.4149 | 0.8117 | |
| | 0.2175 | 21.33 | 180 | 0.4274 | 0.8243 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.37.2 |
| - Pytorch 2.0.1+cu117 |
| - Datasets 2.15.0 |
| - Tokenizers 0.15.0 |
|
|
