swin-tiny-patch4-window7-224-finetuned-eurosat
This model is a fine-tuned version of andupets/real-estate-image-classification on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0613
- Accuracy: 0.9805
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.089 | 0.99 | 140 | 0.1050 | 0.9635 |
| 0.0565 | 2.0 | 281 | 0.0760 | 0.9725 |
| 0.0421 | 2.98 | 420 | 0.0613 | 0.9805 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3