swin-tiny-patch4-window7-224-finetuned-eurosat-finetuned-cifar100
This model was trained from scratch on the cifar10 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3047
- Accuracy: 0.9066
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 |
|---|---|---|---|---|
| 0.7695 | 1.0 | 351 | 0.4700 | 0.8668 |
| 0.6836 | 2.0 | 703 | 0.3270 | 0.9 |
| 0.6207 | 2.99 | 1053 | 0.3047 | 0.9066 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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