william7642/my_awesome_food_model
By william7642 · ↓ 7 · ♥ 0 · Updated 2023-10-01
What's in this repo
This page lists the files in william7642/my_awesome_food_model, including model.onnx, model_quantized.onnx.
- 2 ONNX models (.onnx files)
- 15 files, including 3 .json, 2 .onnx, 2 .bin, 2 .1, 2 .0, 1 .md
- Last updated 2023-10-01
ONNX files
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
my_awesome_food_model
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the food101 dataset. It achieves the following results on the evaluation set:
- Loss: 1.0616
- Accuracy: 0.7962
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: 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 |
|---|---|---|---|---|
| 1.9969 | 1.0 | 947 | 1.9538 | 0.7321 |
| 1.1907 | 2.0 | 1894 | 1.2216 | 0.7806 |
| 0.9433 | 3.0 | 2841 | 1.0616 | 0.7962 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
Model info
Created: 2022-12-20
Updated: 2023-10-01
View on Hugging FaceFiles (15)
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