---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: product_classifier_url_name2
  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_url_name2

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: 0.2686
- Accuracy: 0.9383
- F1: 0.9380
- Precision: 0.9380
- Recall: 0.9383

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.8154        | 1.0   | 960  | 0.3342          | 0.8979   | 0.8979 | 0.8989    | 0.8979 |
| 0.2711        | 2.0   | 1920 | 0.2602          | 0.9279   | 0.9277 | 0.9278    | 0.9279 |
| 0.1624        | 3.0   | 2880 | 0.2528          | 0.9354   | 0.9351 | 0.9356    | 0.9354 |
| 0.109         | 4.0   | 3840 | 0.2686          | 0.9383   | 0.9380 | 0.9380    | 0.9383 |


### Framework versions

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