sinhala-gpt-lyrics

This particular model has undergone fine-tuning based on the gpt2 architecture, utilizing a dataset of around 500k Sinhala lyrics from various sources.

Training procedure

The model was trained for approximately 7 hours on Kaggle GPUs.

Usage Details

from transformers import AutoTokenizer, AutoModelForCausalLM,pipeline

tokenizer = AutoTokenizer.from_pretrained("Ransaka/sinhala-gpt-lyrics")
model = AutoModelForCausalLM.from_pretrained("Ransaka/sinhala-gpt-lyrics")
generator = pipeline('text-generation',model=model, tokenizer=tokenizer)
generator("දුර") #දුර ඈත පාසැල් වියේ.

or using git

git lfs install
git clone https://huggingface.co/Ransaka/sinhala-gpt-lyrics

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 3

Training results

Framework versions

• Transformers 4.26.1
• Pytorch 1.13.0
• Datasets 2.1.0
• Tokenizers 0.13.2