metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuned-fake-food
results: []
finetuned-fake-food
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: 0.3455
- Accuracy: 0.8541
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5416 | 0.1264 | 100 | 0.5593 | 0.7081 |
| 0.5299 | 0.2528 | 200 | 0.5342 | 0.7422 |
| 0.5503 | 0.3793 | 300 | 0.4875 | 0.7717 |
| 0.5561 | 0.5057 | 400 | 0.4622 | 0.7941 |
| 0.5581 | 0.6321 | 500 | 0.5501 | 0.7457 |
| 0.5845 | 0.7585 | 600 | 0.5088 | 0.7475 |
| 0.5695 | 0.8850 | 700 | 0.4740 | 0.7860 |
| 0.5406 | 1.0114 | 800 | 0.4856 | 0.7816 |
| 0.5353 | 1.1378 | 900 | 0.4252 | 0.8156 |
| 0.5345 | 1.2642 | 1000 | 0.5014 | 0.7762 |
| 0.5105 | 1.3906 | 1100 | 0.4800 | 0.7860 |
| 0.5266 | 1.5171 | 1200 | 0.4618 | 0.7959 |
| 0.4709 | 1.6435 | 1300 | 0.3906 | 0.8281 |
| 0.4624 | 1.7699 | 1400 | 0.4208 | 0.8129 |
| 0.4677 | 1.8963 | 1500 | 0.4207 | 0.8174 |
| 0.4478 | 2.0228 | 1600 | 0.3557 | 0.8478 |
| 0.4451 | 2.1492 | 1700 | 0.3546 | 0.8442 |
| 0.3796 | 2.2756 | 1800 | 0.3199 | 0.8720 |
| 0.4358 | 2.4020 | 1900 | 0.3308 | 0.8603 |
| 0.3373 | 2.5284 | 2000 | 0.3455 | 0.8541 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1