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vit-base-patch16-224-food101-v1
ManishW/vit-base-patch16-224-food101-v1
vit-base-patch16-224-food101-v1 is a image classification model from ManishW. Use it when you need a label for an image. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- May 13, 2023
- Updated
- May 13, 2023
- SHA
- 79c6739e
Datasets
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. -->
vit-base-patch16-224-food101-v1
This model is a fine-tuned version of google/vit-base-patch16-224 on the food101 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2359
- Accuracy: 0.924
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: 0.0001
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0682 | 0.99 | 31 | 0.3073 | 0.908 |
| 0.0425 | 1.98 | 62 | 0.2663 | 0.915 |
| 0.0262 | 2.98 | 93 | 0.2173 | 0.928 |
| 0.0446 | 4.0 | 125 | 0.2195 | 0.937 |
| 0.0642 | 4.96 | 155 | 0.2359 | 0.924 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- May 13, 2023
- Updated
- May 13, 2023