BanglaGPT_512 / README.md
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text_generation_bangla_model

BanglaCLM dataset:

  • OSCAR: 12.84GB

  • Wikipedia dump: 6.24GB

  • ProthomAlo: 3.92GB

  • Kalerkantho: 3.24GB

Model description

  • context size : 128

Training and evaluation data

The BanglaCLM data set is divided into a training set (90%)and a validation set (10%).

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • Batch size: 32

  • Initial learning rate: 5e-5

  • Number of warmup steps: 10000

  • Weight decay rate: 0.01

  • Tokenization algorithm: BPE

  • Vocabulary size of tokenizer: 50256

  • Total trainable params: 124,439,808

  • Epochs: 40

  • Number of training steps: 40772228

  • training_precision: float32

Training results

perplexity score: 2.86.

Framework versions

  • Transformers 4.26.1
  • TensorFlow 2.11.0
  • Datasets 2.10.0
  • Tokenizers 0.13.2

Citation

If you find this model helpful, please cite.

@INPROCEEDINGS{10303383,
  author={Salim, Md. Shahidul and Murad, Hasan and Das, Dola and Ahmed, Faisal},
  booktitle={2023 International Conference on Information and Communication Technology for Sustainable Development (ICICT4SD)}, 
  title={BanglaGPT: A Generative Pretrained Transformer-Based Model for Bangla Language}, 
  year={2023},
  volume={},
  number={},
  pages={56-59},
  doi={10.1109/ICICT4SD59951.2023.10303383}}