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swin-food102
VinoG/swin-food102
swin-food102 is a image classification model from VinoG. Use it when you need a label for an image. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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Model card
From the Hugging Face model README
<!-- 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-food102
This model is a fine-tuned version of juliensimon/autotrain-food101-1471154053 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2488
- Accuracy: 0.9332
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2026 | 0.9987 | 597 | 0.3030 | 0.924 |
| 0.308 | 1.9992 | 1195 | 0.2569 | 0.9319 |
| 0.2397 | 2.9962 | 1791 | 0.2488 | 0.9332 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Image Classification
- Library
- transformers
- Type
- swin
- Created
- May 16, 2024
- Updated
- May 17, 2024