swin-tiny-patch4-window7-224-finetuned-image_quality
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.5242
- Accuracy: 0.9091
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 1 | 0.6762 | 0.6364 |
| No log | 2.0 | 2 | 0.6309 | 0.7273 |
| No log | 3.0 | 3 | 0.6095 | 0.6364 |
| No log | 4.0 | 4 | 0.5775 | 0.6364 |
| No log | 5.0 | 5 | 0.5443 | 0.8182 |
| No log | 6.0 | 6 | 0.5242 | 0.9091 |
| No log | 7.0 | 7 | 0.5149 | 0.8182 |
| No log | 8.0 | 8 | 0.5094 | 0.8182 |
| No log | 9.0 | 9 | 0.5038 | 0.8182 |
| 0.4095 | 10.0 | 10 | 0.4992 | 0.8182 |
Framework versions
- Transformers 4.19.4
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1