| --- |
| license: apache-2.0 |
| base_model: microsoft/swin-base-patch4-window7-224-in22k |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: swin-base-patch4-window7-224-in22k-MM_Classification_base_V10 |
| 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: 0.8639652677279306 |
| --- |
| |
| <!-- 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-base-patch4-window7-224-in22k-MM_Classification_base_V10 |
| |
| This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3253 |
| - Accuracy: 0.8640 |
| |
| ## 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: 7 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | 0.9254 | 0.9552 | 16 | 0.4842 | 0.8133 | |
| | 0.4552 | 1.9701 | 33 | 0.3855 | 0.8495 | |
| | 0.4034 | 2.9851 | 50 | 0.3452 | 0.8611 | |
| | 0.3583 | 4.0 | 67 | 0.3357 | 0.8582 | |
| | 0.353 | 4.9552 | 83 | 0.3281 | 0.8625 | |
| | 0.3387 | 5.9701 | 100 | 0.3240 | 0.8640 | |
| | 0.3157 | 6.6866 | 112 | 0.3253 | 0.8640 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.44.0 |
| - Pytorch 1.13.1+cu117 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
