Simple_VieQA / README.md
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metadata
library_name: transformers
license: cc-by-sa-4.0
base_model: ZycckZ/Zk1-QA-VN-test
tags:
  - generated_from_trainer
model-index:
  - name: Zk1-QA-VN-test2
    results: []
datasets:
  - taidng/UIT-ViQuAD2.0
language:
  - vi
pipeline_tag: question-answering

Zk1-QA-VN-test2 (ZycckZ/Simple_VieQA)

This model is a fine-tuned version of ZycckZ/Zk1-QA-VN-test and taidng/UIT-ViQuAD2 dataset.

It achieves the following results on the evaluation set:

  • Loss: 1.8800
  • Exact Match (EM): 70.07
  • F1 Score: 82.34

Model description

This model now much better than the model before (ZycckZ/Zk1-QA-VN-test).

Intended uses & limitations

  • Create a simple chatbot QA 🤗
  • Just for Vietnamese QA system

Training and evaluation data

Training:

  • taidng/UIT-ViQuAD2.0 - "train"
  • taidng/UIT-ViQuAD2.0 - "validation"
  • taidng/UIT-ViQuAD2.0 - "test"

Evaluation:

  • taidng/UIT-ViQuAD2.0 - "validation"

Training procedure

Based on Question Answering HuggingFace 🤗

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss
1.171 1.0 2226 1.0648
0.8499 2.0 4452 1.1054
0.5862 3.0 6678 1.2583
0.4082 4.0 8904 1.5642
0.2835 5.0 11130 1.8800

Framework versions

  • Transformers 4.52.2
  • Pytorch 2.6.0+cu124
  • Datasets 2.14.4
  • Tokenizers 0.21.1