---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
datasets:
- vietnamese_students_feedback
metrics:
- accuracy
model-index:
- name: bert-base-multilingual-uncased-vietnamese_sentiment_analysis
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: vietnamese_students_feedback
      type: vietnamese_students_feedback
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9279848389134555
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-multilingual-uncased-vietnamese_sentiment_analysis

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on the vietnamese_students_feedback dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2852
- Accuracy: 0.9280

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4054        | 1.0   | 715  | 0.2864          | 0.9154   |
| 0.2643        | 2.0   | 1430 | 0.2852          | 0.9280   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.1
- Tokenizers 0.13.3