---
language:
- en
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
datasets:
- tmnam20/VieGLUE
metrics:
- accuracy
- f1
model-index:
- name: bert-base-multilingual-cased-qqp-100
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: tmnam20/VieGLUE/QQP
      type: tmnam20/VieGLUE
      config: qqp
      split: validation
      args: qqp
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8905515706158793
    - name: F1
      type: f1
      value: 0.8513354611120443
---

<!-- 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. -->

# bert-base-multilingual-cased-qqp-100

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the tmnam20/VieGLUE/QQP dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2983
- Accuracy: 0.8906
- F1: 0.8513
- Combined Score: 0.8709

## 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: 32
- eval_batch_size: 16
- seed: 100
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Combined Score |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:--------------:|
| 0.3417        | 0.44  | 5000  | 0.3198          | 0.8578   | 0.8057 | 0.8317         |
| 0.2998        | 0.88  | 10000 | 0.2908          | 0.8724   | 0.8252 | 0.8488         |
| 0.2629        | 1.32  | 15000 | 0.2970          | 0.8763   | 0.8300 | 0.8532         |
| 0.2269        | 1.76  | 20000 | 0.2874          | 0.8845   | 0.8405 | 0.8625         |
| 0.1933        | 2.2   | 25000 | 0.2962          | 0.8867   | 0.8470 | 0.8669         |
| 0.1752        | 2.64  | 30000 | 0.3174          | 0.8895   | 0.8497 | 0.8696         |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.2.0.dev20231203+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0