---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
model-index:
- name: multilingual_model_v02
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# multilingual_model_v02

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3359
- Accuracy: 0.8707
- F1 Score: 0.7728
- Recall: 0.8527
- Precision: 0.7066

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score | Recall | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:------:|:---------:|
| No log        | 1.0   | 219  | 0.3391          | 0.8707   | 0.7728   | 0.8527 | 0.7066    |
| No log        | 2.0   | 438  | 0.3377          | 0.8707   | 0.7728   | 0.8527 | 0.7066    |
| 0.3688        | 3.0   | 657  | 0.3359          | 0.8707   | 0.7728   | 0.8527 | 0.7066    |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1