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# efficientnet-b3-finetuned-food101

This model is a fine-tuned version of [google/efficientnet-b3](https://huggingface.co/google/efficientnet-b3) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5278
- Accuracy: 0.9
- F1: 0.9042

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|
| 4.1358        | 1.0    | 157  | 3.9867          | 0.328    | 0.3446 |
| 2.5658        | 2.0    | 314  | 2.4812          | 0.71     | 0.7205 |
| 1.5019        | 3.0    | 471  | 1.4903          | 0.806    | 0.8127 |
| 1.1238        | 4.0    | 628  | 0.9173          | 0.834    | 0.8377 |
| 1.0664        | 5.0    | 785  | 0.6943          | 0.8793   | 0.8803 |
| 0.8955        | 6.0    | 942  | 0.6340          | 0.8847   | 0.8874 |
| 0.8461        | 7.0    | 1099 | 0.5398          | 0.8907   | 0.8934 |
| 0.841         | 8.0    | 1256 | 0.5054          | 0.88     | 0.8863 |
| 0.8           | 9.0    | 1413 | 0.5278          | 0.9      | 0.9042 |
| 0.7614        | 9.9408 | 1560 | 0.5160          | 0.896    | 0.9002 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1

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