| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: test_trainer |
| 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: 0.45 |
| --- |
| |
| <!-- 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. --> |
|
|
| # test_trainer |
| |
| 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: 1.7380 |
| - Accuracy: 0.45 |
| |
| ## 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: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 500 |
| - num_epochs: 25 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 10 | 2.0828 | 0.1688 | |
| | No log | 2.0 | 20 | 2.0820 | 0.1688 | |
| | No log | 3.0 | 30 | 2.0807 | 0.175 | |
| | No log | 4.0 | 40 | 2.0789 | 0.1875 | |
| | No log | 5.0 | 50 | 2.0763 | 0.1938 | |
| | No log | 6.0 | 60 | 2.0733 | 0.1875 | |
| | No log | 7.0 | 70 | 2.0697 | 0.1875 | |
| | No log | 8.0 | 80 | 2.0656 | 0.1875 | |
| | No log | 9.0 | 90 | 2.0605 | 0.2125 | |
| | No log | 10.0 | 100 | 2.0540 | 0.2313 | |
| | No log | 11.0 | 110 | 2.0462 | 0.2625 | |
| | No log | 12.0 | 120 | 2.0369 | 0.2687 | |
| | No log | 13.0 | 130 | 2.0259 | 0.2687 | |
| | No log | 14.0 | 140 | 2.0117 | 0.2687 | |
| | No log | 15.0 | 150 | 1.9947 | 0.3125 | |
| | No log | 16.0 | 160 | 1.9763 | 0.2938 | |
| | No log | 17.0 | 170 | 1.9547 | 0.3125 | |
| | No log | 18.0 | 180 | 1.9313 | 0.325 | |
| | No log | 19.0 | 190 | 1.9075 | 0.35 | |
| | No log | 20.0 | 200 | 1.8817 | 0.3563 | |
| | No log | 21.0 | 210 | 1.8535 | 0.3812 | |
| | No log | 22.0 | 220 | 1.8244 | 0.4062 | |
| | No log | 23.0 | 230 | 1.7954 | 0.4188 | |
| | No log | 24.0 | 240 | 1.7664 | 0.4375 | |
| | No log | 25.0 | 250 | 1.7380 | 0.45 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - Pytorch 2.4.0+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
|
|
