swin-tiny-patch4-window7-224-finetuned-eurosat
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0393
- Accuracy: 0.9844
- F1: 0.9845
- Precision: 0.9847
- Recall: 0.9844
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
0.3039 | 1.0 | 95 | 0.1300 | 0.9607 | 0.9609 | 0.9619 | 0.9607 |
0.2357 | 2.0 | 190 | 0.0815 | 0.9678 | 0.9678 | 0.9685 | 0.9678 |
0.163 | 3.0 | 285 | 0.0559 | 0.9807 | 0.9807 | 0.9809 | 0.9807 |
0.1267 | 4.0 | 380 | 0.0492 | 0.9837 | 0.9837 | 0.9839 | 0.9837 |
0.1059 | 5.0 | 475 | 0.0393 | 0.9844 | 0.9845 | 0.9847 | 0.9844 |
Framework versions
- Transformers 4.22.1
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1
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Evaluation results
- Accuracy on imagefolderself-reported0.984
- F1 on imagefolderself-reported0.984
- Precision on imagefolderself-reported0.985
- Recall on imagefolderself-reported0.984