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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: microsoft/swin-tiny-patch4-window7-224 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: swin-tiny-patch4-window7-224-finetuned-eurosat |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5614035087719298 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# swin-tiny-patch4-window7-224-finetuned-eurosat |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6599 |
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- Accuracy: 0.5614 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 4 | 0.6771 | 0.5789 | |
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| No log | 2.0 | 8 | 0.6415 | 0.6140 | |
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| 0.6754 | 3.0 | 12 | 0.6351 | 0.6667 | |
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| 0.6754 | 4.0 | 16 | 0.6629 | 0.5614 | |
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| 0.6122 | 5.0 | 20 | 0.6631 | 0.5789 | |
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| 0.6122 | 6.0 | 24 | 0.6529 | 0.5789 | |
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| 0.6122 | 7.0 | 28 | 0.6541 | 0.5614 | |
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| 0.5894 | 8.0 | 32 | 0.6599 | 0.5614 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.0 |
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- Tokenizers 0.21.0 |
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