swin-tiny-patch4-window7-224-hotel_images_classifier_v2
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: 0.1259
- Accuracy: 0.9518
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.2929 | 1.0 | 694 | 0.1688 | 0.9386 |
| 0.2499 | 2.0 | 1389 | 0.1516 | 0.9425 |
| 0.1633 | 3.0 | 2084 | 0.1373 | 0.9488 |
| 0.1943 | 4.0 | 2779 | 0.1319 | 0.9510 |
| 0.2138 | 4.99 | 3470 | 0.1259 | 0.9518 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2