swin-finetuned-food101
This model is a fine-tuned version of microsoft/swin-large-patch4-window7-224-in22k on the zindi dataset. It achieves the following results on the evaluation set:
- Loss: 0.5697
- Accuracy: 0.7666
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 |
|---|---|---|---|---|
| 0.7373 | 1.0 | 173 | 0.6503 | 0.7366 |
| 0.6106 | 2.0 | 347 | 0.5950 | 0.7503 |
| 0.5135 | 2.99 | 519 | 0.5697 | 0.7666 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
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