<!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. -->
swin-base-finetuned-snacks
This model is a fine-tuned version of microsoft/swin-base-patch4-window7-224 on the snacks dataset. It achieves the following results on the evaluation set:
- Loss: 0.2404
- Accuracy: 0.9455
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 |
|---|---|---|---|---|
| 0.0044 | 1.0 | 38 | 0.2981 | 0.9309 |
| 0.0023 | 2.0 | 76 | 0.2287 | 0.9445 |
| 0.0012 | 3.0 | 114 | 0.2404 | 0.9455 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
