metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: food-recognition
results: []
food-recognition
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: 0.2610
- Accuracy: 0.9324
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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5974 | 0.21 | 100 | 0.6096 | 0.8292 |
| 0.5911 | 0.43 | 200 | 0.5204 | 0.8476 |
| 0.7085 | 0.64 | 300 | 0.4329 | 0.8708 |
| 0.5302 | 0.85 | 400 | 0.4843 | 0.8428 |
| 0.2436 | 1.07 | 500 | 0.3767 | 0.886 |
| 0.2355 | 1.28 | 600 | 0.3344 | 0.8956 |
| 0.1497 | 1.49 | 700 | 0.3447 | 0.8932 |
| 0.2213 | 1.71 | 800 | 0.3082 | 0.9072 |
| 0.2197 | 1.92 | 900 | 0.3169 | 0.902 |
| 0.0719 | 2.13 | 1000 | 0.2977 | 0.9136 |
| 0.0526 | 2.35 | 1100 | 0.3455 | 0.9084 |
| 0.0926 | 2.56 | 1200 | 0.3140 | 0.9208 |
| 0.0427 | 2.77 | 1300 | 0.3307 | 0.9128 |
| 0.0716 | 2.99 | 1400 | 0.3007 | 0.9204 |
| 0.0151 | 3.2 | 1500 | 0.2791 | 0.9292 |
| 0.032 | 3.41 | 1600 | 0.2737 | 0.9296 |
| 0.0611 | 3.62 | 1700 | 0.2620 | 0.9336 |
| 0.0175 | 3.84 | 1800 | 0.2610 | 0.9324 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.1.1+cpu
- Datasets 2.15.0
- Tokenizers 0.15.0