| --- |
| license: apache-2.0 |
| base_model: microsoft/swin-tiny-patch4-window7-224 |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: swin-tiny-patch4-window7-224-MM_Classification |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: validation |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.8693982074263764 |
| --- |
| |
| <!-- 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. --> |
|
|
| # swin-tiny-patch4-window7-224-MM_Classification |
| |
| This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3468 |
| - Accuracy: 0.8694 |
| |
| ## 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: 128 |
| - eval_batch_size: 128 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 512 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 20 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 1.0476 | 1.0 | 19 | 0.7707 | 0.6530 | |
| | 0.6226 | 2.0 | 38 | 0.4743 | 0.8105 | |
| | 0.4477 | 3.0 | 57 | 0.4133 | 0.8323 | |
| | 0.3963 | 4.0 | 76 | 0.3813 | 0.8476 | |
| | 0.3694 | 5.0 | 95 | 0.3753 | 0.8540 | |
| | 0.3451 | 6.0 | 114 | 0.3587 | 0.8489 | |
| | 0.3382 | 7.0 | 133 | 0.3531 | 0.8451 | |
| | 0.3253 | 8.0 | 152 | 0.3498 | 0.8579 | |
| | 0.3121 | 9.0 | 171 | 0.3437 | 0.8579 | |
| | 0.2855 | 10.0 | 190 | 0.3447 | 0.8656 | |
| | 0.2961 | 11.0 | 209 | 0.3350 | 0.8617 | |
| | 0.273 | 12.0 | 228 | 0.3484 | 0.8566 | |
| | 0.2745 | 13.0 | 247 | 0.3433 | 0.8604 | |
| | 0.2613 | 14.0 | 266 | 0.3498 | 0.8643 | |
| | 0.2527 | 15.0 | 285 | 0.3365 | 0.8579 | |
| | 0.2619 | 16.0 | 304 | 0.3450 | 0.8617 | |
| | 0.2436 | 17.0 | 323 | 0.3454 | 0.8681 | |
| | 0.2518 | 18.0 | 342 | 0.3437 | 0.8681 | |
| | 0.243 | 19.0 | 361 | 0.3468 | 0.8694 | |
| | 0.2415 | 20.0 | 380 | 0.3455 | 0.8694 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.43.3 |
| - Pytorch 1.13.1+cu117 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
