---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hf_tutorial_food_not_food_text_classifier-distilbert-base-uncased
  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. -->

# hf_tutorial_food_not_food_text_classifier-distilbert-base-uncased

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0687
- Accuracy: 0.98

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4267        | 1.0   | 7    | 0.1057          | 0.98     |
| 0.0479        | 2.0   | 14   | 0.0092          | 1.0      |
| 0.0053        | 3.0   | 21   | 0.0480          | 0.98     |
| 0.0019        | 4.0   | 28   | 0.0694          | 0.98     |
| 0.0011        | 5.0   | 35   | 0.0747          | 0.98     |
| 0.0008        | 6.0   | 42   | 0.0737          | 0.98     |
| 0.0007        | 7.0   | 49   | 0.0721          | 0.98     |
| 0.0006        | 8.0   | 56   | 0.0702          | 0.98     |
| 0.0006        | 9.0   | 63   | 0.0691          | 0.98     |
| 0.0006        | 10.0  | 70   | 0.0687          | 0.98     |


### Framework versions

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