swinv2-tiny-patch4-window8-256-finetuned-og_dataset_5e
This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0958
- Accuracy: 0.9635
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 |
|---|---|---|---|---|
| 0.5003 | 1.0 | 546 | 0.3882 | 0.8384 |
| 0.3697 | 2.0 | 1092 | 0.2029 | 0.9236 |
| 0.3195 | 3.0 | 1638 | 0.1565 | 0.9381 |
| 0.2392 | 4.0 | 2184 | 0.1251 | 0.9517 |
| 0.2343 | 5.0 | 2730 | 0.0958 | 0.9635 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2