| --- |
| 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-finetuned-eurosat |
| 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: 0.9966577540106952 |
| --- |
| |
| <!-- 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-finetuned-eurosat |
|
|
| 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: 0.0271 |
| - Accuracy: 0.9967 |
|
|
| ## 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 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 15 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.0898 | 1.0 | 327 | 0.0707 | 0.9757 | |
| | 0.0221 | 2.0 | 654 | 0.0278 | 0.9920 | |
| | 0.06 | 3.0 | 981 | 0.0345 | 0.9913 | |
| | 0.0094 | 4.0 | 1309 | 0.0300 | 0.9947 | |
| | 0.0004 | 5.0 | 1636 | 0.0398 | 0.9942 | |
| | 0.0035 | 6.0 | 1963 | 0.0136 | 0.9975 | |
| | 0.0246 | 7.0 | 2290 | 0.0339 | 0.9940 | |
| | 0.0012 | 8.0 | 2618 | 0.0316 | 0.9958 | |
| | 0.0 | 9.0 | 2945 | 0.0302 | 0.9964 | |
| | 0.0 | 10.0 | 3272 | 0.0201 | 0.9973 | |
| | 0.0003 | 11.0 | 3599 | 0.0222 | 0.9955 | |
| | 0.0 | 12.0 | 3927 | 0.0218 | 0.9962 | |
| | 0.0001 | 13.0 | 4254 | 0.0293 | 0.9962 | |
| | 0.0002 | 14.0 | 4581 | 0.0272 | 0.9962 | |
| | 0.0 | 14.99 | 4905 | 0.0271 | 0.9967 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.15.0 |
| - Tokenizers 0.15.0 |
|
|
