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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}}
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