transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:food101 autotrain_compatible endpoints_compatible region:us
---
tags:
- generated_from_trainer
datasets:
- food101
model-index:
- name: food-image-classification
  results: []
---

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# food-image-classification

This model was trained from scratch on the food101 dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.4645
- eval_accuracy: 0.8831
- eval_runtime: 156.6057
- eval_samples_per_second: 96.74
- eval_steps_per_second: 6.047
- epoch: 54.91
- step: 52000

## 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: 500

### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.1
