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vit-base-patch16-224-in21k-lora
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on food101 dataset. It achieves the following results on the evaluation set:
- trainable params: 667,493 || all params: 86,543,818 || trainable%: 0.7713
- Loss: 0.3400
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.005
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.8448 | 1.0 | 74 | 0.4689 |
| 0.7281 | 2.0 | 148 | 0.4009 |
| 0.6533 | 3.0 | 222 | 0.3697 |
| 0.5799 | 4.0 | 296 | 0.3520 |
| 0.5547 | 5.0 | 370 | 0.3400 |
Framework versions
- PEFT 0.11.1
- Transformers 4.43.4
- Pytorch 2.2.1+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
google/vit-base-patch16-224-in21k