| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| model-index: |
| - name: beans_ViT |
| 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. --> |
|
|
| # beans_ViT |
| |
| 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: 1.2997 |
| - Accuracy: 0.7969 |
| - F1: 0.7991 |
| |
| ## 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: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 30 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | No log | 1.0 | 17 | 0.8693 | 0.6090 | 0.5953 | |
| | No log | 2.0 | 34 | 0.9652 | 0.6015 | 0.5977 | |
| | No log | 3.0 | 51 | 0.7178 | 0.6992 | 0.6927 | |
| | No log | 4.0 | 68 | 0.7488 | 0.6992 | 0.6955 | |
| | No log | 5.0 | 85 | 0.6517 | 0.7068 | 0.7070 | |
| | No log | 6.0 | 102 | 0.7816 | 0.6842 | 0.6541 | |
| | No log | 7.0 | 119 | 0.5014 | 0.7744 | 0.7733 | |
| | No log | 8.0 | 136 | 0.5321 | 0.7669 | 0.7680 | |
| | No log | 9.0 | 153 | 0.5985 | 0.7444 | 0.7457 | |
| | No log | 10.0 | 170 | 0.4675 | 0.8271 | 0.8274 | |
| | No log | 11.0 | 187 | 0.5750 | 0.7744 | 0.7576 | |
| | No log | 12.0 | 204 | 0.6617 | 0.7293 | 0.7066 | |
| | No log | 13.0 | 221 | 0.6396 | 0.7594 | 0.7577 | |
| | No log | 14.0 | 238 | 0.4302 | 0.8346 | 0.8352 | |
| | No log | 15.0 | 255 | 0.4018 | 0.8421 | 0.8427 | |
| | No log | 16.0 | 272 | 0.5673 | 0.7895 | 0.7883 | |
| | No log | 17.0 | 289 | 0.5037 | 0.8120 | 0.8097 | |
| | No log | 18.0 | 306 | 0.5939 | 0.8496 | 0.8487 | |
| | No log | 19.0 | 323 | 0.6590 | 0.8120 | 0.8111 | |
| | No log | 20.0 | 340 | 0.6060 | 0.8571 | 0.8559 | |
| | No log | 21.0 | 357 | 0.5806 | 0.8421 | 0.8418 | |
| | No log | 22.0 | 374 | 0.6180 | 0.8421 | 0.8414 | |
| | No log | 23.0 | 391 | 0.7707 | 0.7669 | 0.7633 | |
| | No log | 24.0 | 408 | 0.5440 | 0.8421 | 0.8418 | |
| | No log | 25.0 | 425 | 0.6596 | 0.8496 | 0.8497 | |
| | No log | 26.0 | 442 | 0.5393 | 0.8346 | 0.8342 | |
| | No log | 27.0 | 459 | 0.6320 | 0.8797 | 0.8795 | |
| | No log | 28.0 | 476 | 0.5903 | 0.8496 | 0.8507 | |
| | No log | 29.0 | 493 | 0.6826 | 0.8647 | 0.8644 | |
| | 0.3346 | 30.0 | 510 | 0.6493 | 0.8571 | 0.8567 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.47.0 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.3.1 |
| - Tokenizers 0.21.0 |
| |
