tensorboard safetensors generated_from_trainer dataset:food101 region:us
---
tags:
- generated_from_trainer
datasets:
- food101
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-in21k-finetuned-lora-food101
  results: []
---

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# vit-base-patch16-224-in21k-finetuned-lora-food101

This model was trained from scratch on the food101 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1086
- Accuracy: 0.966

## 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: 0.005
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 512
- 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 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 9    | 0.6070          | 0.878    |
| 2.2106        | 2.0   | 18   | 0.1910          | 0.948    |
| 0.354         | 3.0   | 27   | 0.1266          | 0.966    |
| 0.2142        | 4.0   | 36   | 0.1141          | 0.968    |
| 0.1788        | 5.0   | 45   | 0.1086          | 0.966    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
