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vi-fin-news

Text Classification
Transformers
PyTorch
Vietnamese
bert
Generated from Trainer
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metadata
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

vi-fin-news

This model is a fine-tuned version of 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