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custom_food_model
ashokkourla/custom_food_model
custom_food_model is a image classification model from ashokkourla. 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
- Aug 6, 2025
- Updated
- Aug 18, 2025
- SHA
- c6510e3f
Base models
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. -->
custom_food_model
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6513
- Accuracy: 0.847
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.7143 | 1.0 | 63 | 2.5641 | 0.811 |
| 1.8708 | 2.0 | 126 | 1.8179 | 0.842 |
| 1.6223 | 3.0 | 189 | 1.6513 | 0.847 |
Framework versions
- Transformers 4.55.0
- Pytorch 2.7.1+cpu
- Datasets 3.6.0
- Tokenizers 0.21.4
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Aug 6, 2025
- Updated
- Aug 18, 2025