Garbage-Classification-SWIN-Transformer
This model is a fine-tuned version of microsoft/swin-tiny-patch4-window7-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0440
- Accuracy: 0.9900
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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- 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 |
|---|---|---|---|---|
| 0.1969 | 0.9973 | 280 | 0.1740 | 0.9409 |
| 0.1014 | 1.9982 | 561 | 0.0752 | 0.9755 |
| 0.0333 | 2.9991 | 842 | 0.0551 | 0.9824 |
| 0.0332 | 4.0 | 1123 | 0.0526 | 0.9845 |
| 0.0218 | 4.9973 | 1403 | 0.0511 | 0.9866 |
| 0.0086 | 5.9982 | 1684 | 0.0515 | 0.9873 |
| 0.0057 | 6.9991 | 1965 | 0.0462 | 0.9875 |
| 0.0043 | 8.0 | 2246 | 0.0453 | 0.9891 |
| 0.0012 | 8.9973 | 2526 | 0.0460 | 0.9888 |
| 0.0017 | 9.9733 | 2800 | 0.0440 | 0.9900 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
microsoft/swin-tiny-patch4-window7-224