---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: food_type_classification_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# food_type_classification_model

Easily classify any food product into Plant-based(**PLANT_BASED**) or Animal-based(**ANIMAL_BASED**) based on ingredients or product title.

This model was trained using a dataset from **[USDA FoodData Central](https://fdc.nal.usda.gov/download-datasets.html)** which contains 
the ANIMAL_BASED and PLANT_BASED classification labels based on the available protein type in a food product. 


This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) .
It achieves the following results on the evaluation set:
- **Loss: 0.0249**
- **Accuracy: 0.9940**

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 336  | 0.0351          | 0.9933   |
| 0.0711        | 2.0   | 672  | 0.0249          | 0.9940   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0