---
library_name: transformers
base_model: AkremGomri/my_awesome_food_model
tags:
- trackio
- trackio:https://huggingface.co/spaces/AkremGomri/trackio
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hf_image_classification
  results: []
---

<!-- 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. -->

<a href="https://huggingface.co/spaces/AkremGomri/trackio" target="_blank"><img src="https://raw.githubusercontent.com/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in Trackio" title="Visualize in Trackio" style="height: 40px;"/></a>
# hf_image_classification

This model is a fine-tuned version of [AkremGomri/my_awesome_food_model](https://huggingface.co/AkremGomri/my_awesome_food_model) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8116
- Accuracy: 0.913

## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1734        | 1.0   | 63   | 1.1388          | 0.907    |
| 0.7969        | 2.0   | 126  | 0.8880          | 0.917    |
| 0.7487        | 3.0   | 189  | 0.8116          | 0.913    |


### Framework versions

- Transformers 5.1.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2