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

# comida_no_comida_text_classifier

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: 0.0823
- Accuracy: 0.9903

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5879        | 1.0   | 26   | 0.1729          | 0.9420   |
| 0.1047        | 2.0   | 52   | 0.1249          | 0.9758   |
| 0.042         | 3.0   | 78   | 0.0938          | 0.9807   |
| 0.0022        | 4.0   | 104  | 0.0756          | 0.9903   |
| 0.0086        | 5.0   | 130  | 0.0767          | 0.9903   |
| 0.0005        | 6.0   | 156  | 0.0789          | 0.9903   |
| 0.0004        | 7.0   | 182  | 0.0804          | 0.9903   |
| 0.0003        | 8.0   | 208  | 0.0815          | 0.9903   |
| 0.0003        | 9.0   | 234  | 0.0821          | 0.9903   |
| 0.0003        | 10.0  | 260  | 0.0823          | 0.9903   |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.1
- Tokenizers 0.21.0