shahidul034/BanglaGPT

textgenerationbangla_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}}