File size: 1,842 Bytes
9f2151c b2299a8 73592ef b2299a8 73592ef fead1bc 83dbab8 9f2151c b2299a8 9f2151c 5740fc2 9f2151c 5740fc2 dda687a 9f2151c 5740fc2 9f2151c |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 |
---
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
should probably proofread and complete it, then remove this comment. -->
# 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
|