| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: facebook/deit-small-patch16-224 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| - recall |
| model-index: |
| - name: deit_fold_4 |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: None |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9515570934256056 |
| - name: Recall |
| type: recall |
| value: 0.9524889695792607 |
| --- |
| |
| <!-- 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. --> |
|
|
| # deit_fold_4 |
|
|
| This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.1613 |
| - Accuracy: 0.9516 |
| - F1 Score: 0.9557 |
| - Recall: 0.9525 |
|
|
| ## 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: 1e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 150 |
| - num_epochs: 100 |
| - label_smoothing_factor: 0.15 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:| |
| | 3.0112 | 1.0 | 19 | 2.9175 | 0.1349 | 0.1173 | 0.1476 | |
| | 2.8882 | 2.0 | 38 | 2.7478 | 0.2837 | 0.2479 | 0.2602 | |
| | 2.6765 | 3.0 | 57 | 2.5537 | 0.4360 | 0.3402 | 0.3670 | |
| | 2.3897 | 4.0 | 76 | 2.2672 | 0.5882 | 0.5441 | 0.5359 | |
| | 1.9781 | 5.0 | 95 | 1.8705 | 0.7924 | 0.7997 | 0.7861 | |
| | 1.6123 | 6.0 | 114 | 1.5627 | 0.8512 | 0.8659 | 0.8675 | |
| | 1.4216 | 7.0 | 133 | 1.3723 | 0.8962 | 0.9067 | 0.9017 | |
| | 1.2460 | 8.0 | 152 | 1.2605 | 0.9308 | 0.9380 | 0.9351 | |
| | 1.1724 | 9.0 | 171 | 1.2218 | 0.9308 | 0.9370 | 0.9337 | |
| | 1.1521 | 10.0 | 190 | 1.1915 | 0.9446 | 0.9492 | 0.9488 | |
| | 1.1116 | 11.0 | 209 | 1.1921 | 0.9377 | 0.9440 | 0.9451 | |
| | 1.0878 | 12.0 | 228 | 1.1973 | 0.9343 | 0.9406 | 0.9428 | |
| | 1.0601 | 13.0 | 247 | 1.1842 | 0.9377 | 0.9435 | 0.9451 | |
| | 1.0711 | 14.0 | 266 | 1.1563 | 0.9446 | 0.9497 | 0.9475 | |
| | 1.0461 | 15.0 | 285 | 1.1533 | 0.9446 | 0.9497 | 0.9475 | |
| | 1.0390 | 16.0 | 304 | 1.1613 | 0.9516 | 0.9557 | 0.9525 | |
| | 1.0080 | 17.0 | 323 | 1.1645 | 0.9412 | 0.9463 | 0.9465 | |
| | 1.0109 | 18.0 | 342 | 1.1656 | 0.9377 | 0.9434 | 0.9438 | |
| | 1.0092 | 19.0 | 361 | 1.1701 | 0.9446 | 0.9494 | 0.9501 | |
| | 0.9972 | 20.0 | 380 | 1.1859 | 0.9377 | 0.9432 | 0.9429 | |
| | 1.0005 | 21.0 | 399 | 1.1708 | 0.9446 | 0.9501 | 0.9522 | |
| | 0.9900 | 22.0 | 418 | 1.1849 | 0.9412 | 0.9470 | 0.9476 | |
| | 0.9758 | 23.0 | 437 | 1.1893 | 0.9446 | 0.9496 | 0.9511 | |
| | 0.9886 | 24.0 | 456 | 1.1739 | 0.9446 | 0.9496 | 0.9511 | |
| | 0.9757 | 25.0 | 475 | 1.1648 | 0.9412 | 0.9460 | 0.9440 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 5.0.0 |
| - Tokenizers 0.22.2 |
|
|
