| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: model |
| 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: 0.6 |
| --- |
| |
| <!-- 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. --> |
|
|
| # model |
|
|
| 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: 1.4897 |
| - Accuracy: 0.6 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 25 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | No log | 1.0 | 80 | 1.7001 | 0.325 | |
| | No log | 2.0 | 160 | 1.4642 | 0.4875 | |
| | No log | 3.0 | 240 | 1.3522 | 0.4625 | |
| | No log | 4.0 | 320 | 1.3493 | 0.4688 | |
| | No log | 5.0 | 400 | 1.2052 | 0.55 | |
| | No log | 6.0 | 480 | 1.2267 | 0.5563 | |
| | 1.2917 | 7.0 | 560 | 1.1744 | 0.6062 | |
| | 1.2917 | 8.0 | 640 | 1.2969 | 0.5437 | |
| | 1.2917 | 9.0 | 720 | 1.2519 | 0.5687 | |
| | 1.2917 | 10.0 | 800 | 1.3108 | 0.5125 | |
| | 1.2917 | 11.0 | 880 | 1.2725 | 0.5875 | |
| | 1.2917 | 12.0 | 960 | 1.3437 | 0.55 | |
| | 0.5002 | 13.0 | 1040 | 1.3790 | 0.5375 | |
| | 0.5002 | 14.0 | 1120 | 1.3432 | 0.625 | |
| | 0.5002 | 15.0 | 1200 | 1.4395 | 0.55 | |
| | 0.5002 | 16.0 | 1280 | 1.3672 | 0.5875 | |
| | 0.5002 | 17.0 | 1360 | 1.3928 | 0.575 | |
| | 0.5002 | 18.0 | 1440 | 1.3016 | 0.5875 | |
| | 0.2523 | 19.0 | 1520 | 1.4815 | 0.5625 | |
| | 0.2523 | 20.0 | 1600 | 1.3394 | 0.6062 | |
| | 0.2523 | 21.0 | 1680 | 1.3450 | 0.5938 | |
| | 0.2523 | 22.0 | 1760 | 1.3924 | 0.6312 | |
| | 0.2523 | 23.0 | 1840 | 1.4664 | 0.5813 | |
| | 0.2523 | 24.0 | 1920 | 1.2635 | 0.65 | |
| | 0.1723 | 25.0 | 2000 | 1.4154 | 0.5625 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.17.0 |
| - Tokenizers 0.15.1 |
|
|
