---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: product_classifier_split_url_nodigit
  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_split_url_nodigit

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0964
- Accuracy: 0.9805
- F1: 0.9804
- Precision: 0.9804
- Recall: 0.9805

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.3863        | 1.0   | 960  | 0.1176          | 0.9677   | 0.9678 | 0.9680    | 0.9677 |
| 0.0978        | 2.0   | 1920 | 0.0969          | 0.9758   | 0.9758 | 0.9760    | 0.9758 |
| 0.0554        | 3.0   | 2880 | 0.0884          | 0.9810   | 0.9810 | 0.9810    | 0.9810 |
| 0.0336        | 4.0   | 3840 | 0.0964          | 0.9805   | 0.9804 | 0.9804    | 0.9805 |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3