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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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