Downloads · 30 days
4
6% of all-time downloads
my_awesome_food_model
nimishac28/my_awesome_food_model
my_awesome_food_model is a image classification model from nimishac28. 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.
<a href="https://huggingface.co/spaces/nimishac28/huggingface-static-2f2526" target="blank"<img src="https://raw.githubusercontent.com/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in Tra…
All-time downloads
63
Public
Parameters
85.9M
1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors344 MB · 100%
At a glance
- Task
- Image Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- vit
- Access
- Public
- Created
- Jul 3, 2026
- Updated
- Jul 3, 2026
- SHA
- eb2989c0
Base models
Model card
From the Hugging Face model README
<a href="https://huggingface.co/spaces/nimishac28/huggingface-static-2f2526" target="_blank"><img src="https://raw.githubusercontent.com/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in Trackio" title="Visualize in Trackio" style="height: 40px;"/></a>
<!-- 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. -->my_awesome_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: 2.2741
- Accuracy: 0.464
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_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.9399 | 1.0 | 63 | 2.8394 | 0.362 |
| 2.5064 | 2.0 | 126 | 2.4431 | 0.428 |
| 2.3115 | 3.0 | 189 | 2.2741 | 0.464 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Image Classification
- Library
- transformers
- Type
- vit
- License
- apache-2.0
- Created
- Jul 3, 2026
- Updated
- Jul 3, 2026