---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: product_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. -->

# product_classifier

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6760
- Accuracy: {'accuracy': 0.80125}
- Precision: {'precision': 0.785989926719994}
- Recall: {'recall': 0.7755906520102293}
- F1 Score: {'f1': 0.7704315421053631}

## 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: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy                | Precision                         | Recall                         | F1 Score                  |
|:-------------:|:-----:|:----:|:---------------:|:-----------------------:|:---------------------------------:|:------------------------------:|:-------------------------:|
| 0.9575        | 1.0   | 3200 | 0.6832          | {'accuracy': 0.7978125} | {'precision': 0.7851098622896849} | {'recall': 0.7737991362724596} | {'f1': 0.771520016712035} |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3