---
base_model: FPTAI/vibert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vi-fin-news
  results: []
license: apache-2.0
language:
- vi
library_name: transformers
pipeline_tag: text-classification
---

<!-- 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. -->

# vi-fin-news

This model is a fine-tuned version of [FPTAI/vibert-base-cased](https://huggingface.co/FPTAI/vibert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4509
- Accuracy: 0.9136

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1176        | 1.0   | 1150 | 0.3566          | 0.9181   |
| 0.0582        | 2.0   | 2300 | 0.4509          | 0.9136   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.2
- Datasets 2.12.0
- Tokenizers 0.13.3