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

# result-colab

This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3660
- Accuracy: 0.8991
- Precision: 0.8990
- Recall: 0.8942
- F1: 0.8959

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.3839        | 1.0   | 24   | 0.4077          | 0.8716   | 0.8635    | 0.8717 | 0.8639 |
| 0.3268        | 2.0   | 48   | 0.4052          | 0.8578   | 0.8510    | 0.8489 | 0.8467 |
| 0.2524        | 3.0   | 72   | 0.4014          | 0.8899   | 0.8938    | 0.8795 | 0.8843 |
| 0.2171        | 4.0   | 96   | 0.3582          | 0.8899   | 0.8860    | 0.8849 | 0.8846 |
| 0.1712        | 5.0   | 120  | 0.3983          | 0.8899   | 0.8885    | 0.8804 | 0.8826 |
| 0.1627        | 6.0   | 144  | 0.3789          | 0.8991   | 0.8984    | 0.8998 | 0.8983 |
| 0.1462        | 7.0   | 168  | 0.3884          | 0.8991   | 0.9004    | 0.8922 | 0.8955 |
| 0.1499        | 8.0   | 192  | 0.3727          | 0.9083   | 0.9069    | 0.9080 | 0.9070 |
| 0.1557        | 9.0   | 216  | 0.3669          | 0.8991   | 0.8990    | 0.8942 | 0.8959 |
| 0.1462        | 10.0  | 240  | 0.3660          | 0.8991   | 0.8990    | 0.8942 | 0.8959 |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1