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

# bert_product_classifier_name

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: 0.3406
- Accuracy: 0.9517
- F1: 0.9513
- Precision: 0.9514
- Recall: 0.9517

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.8574        | 1.0   | 960  | 0.3075          | 0.9079   | 0.9069 | 0.9077    | 0.9079 |
| 0.267         | 2.0   | 1920 | 0.2432          | 0.9292   | 0.9294 | 0.9307    | 0.9292 |
| 0.1596        | 3.0   | 2880 | 0.2228          | 0.9411   | 0.9408 | 0.9409    | 0.9411 |
| 0.1094        | 4.0   | 3840 | 0.2540          | 0.9452   | 0.9447 | 0.9447    | 0.9452 |
| 0.0755        | 5.0   | 4800 | 0.2652          | 0.9470   | 0.9471 | 0.9472    | 0.9470 |
| 0.0506        | 6.0   | 5760 | 0.2924          | 0.9492   | 0.9491 | 0.9491    | 0.9492 |
| 0.0364        | 7.0   | 6720 | 0.3251          | 0.9475   | 0.9470 | 0.9476    | 0.9475 |
| 0.022         | 8.0   | 7680 | 0.3271          | 0.9518   | 0.9515 | 0.9514    | 0.9518 |
| 0.0122        | 9.0   | 8640 | 0.3368          | 0.9522   | 0.9520 | 0.9519    | 0.9522 |
| 0.0103        | 10.0  | 9600 | 0.3406          | 0.9517   | 0.9513 | 0.9514    | 0.9517 |


### Framework versions

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