---
library_name: transformers
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0995
- Accuracy: 0.9724
- Precision: 0.9731
- Recall: 0.9724
- F1: 0.9724

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.1995        | 1.0   | 172  | 0.1873          | 0.9507   | 0.9508    | 0.9507 | 0.9505 |
| 0.1341        | 2.0   | 344  | 0.1119          | 0.9666   | 0.9670    | 0.9666 | 0.9666 |
| 0.0784        | 3.0   | 516  | 0.0995          | 0.9724   | 0.9731    | 0.9724 | 0.9724 |
| 0.0609        | 4.0   | 688  | 0.1330          | 0.9623   | 0.9623    | 0.9623 | 0.9623 |
| 0.0434        | 5.0   | 860  | 0.1333          | 0.9637   | 0.9638    | 0.9637 | 0.9637 |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0