---
license: apache-2.0
base_model: google/efficientnet-b1
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: efficientnet_b1-food101
  results: []
datasets:
- food101
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# efficientnet_b1-food101

This model is a fine-tuned version of [google/efficientnet-b1](https://huggingface.co/google/efficientnet-b1) on [food101](https://huggingface.co/datasets/food101) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0490
- Accuracy: 0.9947

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 47   | 4.3674          | 0.1548   |
| No log        | 2.0   | 94   | 3.1870          | 0.8915   |
| No log        | 3.0   | 141  | 0.8758          | 0.9751   |
| No log        | 4.0   | 188  | 0.1010          | 0.9858   |
| No log        | 5.0   | 235  | 0.0503          | 0.9893   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2