---
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-with_tokenizer
  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-with_tokenizer

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: 0.3390
- Accuracy: 0.8945
- Precision: 0.8847
- Recall: 0.8927
- F1: 0.8869

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.2288        | 1.0   | 48   | 0.9276          | 0.6789   | 0.5929    | 0.6138 | 0.5825 |
| 0.7686        | 2.0   | 96   | 0.5879          | 0.7661   | 0.7354    | 0.7159 | 0.7019 |
| 0.5665        | 3.0   | 144  | 0.4706          | 0.8440   | 0.8498    | 0.8238 | 0.8281 |
| 0.4813        | 4.0   | 192  | 0.4045          | 0.8578   | 0.8514    | 0.8329 | 0.8354 |
| 0.3716        | 5.0   | 240  | 0.3770          | 0.8624   | 0.8566    | 0.8398 | 0.8426 |
| 0.3535        | 6.0   | 288  | 0.3538          | 0.8853   | 0.8760    | 0.8664 | 0.8690 |
| 0.2511        | 7.0   | 336  | 0.3626          | 0.8716   | 0.8631    | 0.8573 | 0.8591 |
| 0.2826        | 8.0   | 384  | 0.3490          | 0.8899   | 0.8809    | 0.8886 | 0.8823 |
| 0.2295        | 9.0   | 432  | 0.3372          | 0.8807   | 0.8697    | 0.8720 | 0.8705 |
| 0.181         | 10.0  | 480  | 0.3410          | 0.8853   | 0.8743    | 0.8789 | 0.8757 |
| 0.178         | 11.0  | 528  | 0.3416          | 0.8945   | 0.8847    | 0.8927 | 0.8869 |
| 0.208         | 12.0  | 576  | 0.3390          | 0.8945   | 0.8847    | 0.8927 | 0.8869 |


### Framework versions

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