---
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: 0.3751
- Accuracy: 0.8853
- Precision: 0.8785
- Recall: 0.8773
- F1: 0.8773

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.3635        | 1.0   | 48   | 1.1593          | 0.5963   | 0.4671    | 0.5259 | 0.4501 |
| 0.9895        | 2.0   | 96   | 0.7987          | 0.6881   | 0.6824    | 0.6271 | 0.6017 |
| 0.6845        | 3.0   | 144  | 0.6432          | 0.7523   | 0.7789    | 0.7076 | 0.7071 |
| 0.5856        | 4.0   | 192  | 0.5896          | 0.7844   | 0.8315    | 0.7457 | 0.7463 |
| 0.4328        | 5.0   | 240  | 0.4232          | 0.8716   | 0.8750    | 0.8585 | 0.8645 |
| 0.4298        | 6.0   | 288  | 0.4118          | 0.8853   | 0.8783    | 0.8810 | 0.8789 |
| 0.322         | 7.0   | 336  | 0.3988          | 0.8807   | 0.8824    | 0.8655 | 0.8712 |
| 0.3561        | 8.0   | 384  | 0.4169          | 0.8716   | 0.8630    | 0.8679 | 0.8637 |
| 0.27          | 9.0   | 432  | 0.3779          | 0.8991   | 0.8972    | 0.8913 | 0.8938 |
| 0.2472        | 10.0  | 480  | 0.3850          | 0.8991   | 0.8928    | 0.8942 | 0.8924 |
| 0.2349        | 11.0  | 528  | 0.3749          | 0.8945   | 0.8855    | 0.8919 | 0.8875 |
| 0.2491        | 12.0  | 576  | 0.3798          | 0.9037   | 0.8969    | 0.8992 | 0.8975 |
| 0.2239        | 13.0  | 624  | 0.3778          | 0.8853   | 0.8783    | 0.8810 | 0.8793 |
| 0.2276        | 14.0  | 672  | 0.3755          | 0.8899   | 0.8827    | 0.8823 | 0.8822 |
| 0.206         | 15.0  | 720  | 0.3751          | 0.8853   | 0.8785    | 0.8773 | 0.8773 |


### Framework versions

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