sinhala-gpt2
This particular model has undergone fine-tuning based on the gpt2 architecture, utilizing a dataset of Sinhala NEWS from various sources.
Training procedure
The model was trained for 12+ hours on Kaggle GPUs.
Usage Details
from transformers import AutoTokenizer, AutoModelForCausalLM,pipeline
tokenizer = AutoTokenizer.from_pretrained("Ransaka/sinhala-gpt2")
model = AutoModelForCausalLM.from_pretrained("Ransaka/sinhala-gpt2")
generator("දුර")
or using git
git lfs install
git clone https://huggingface.co/Ransaka/sinhala-gpt2
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
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.0233 | 1.0 | 15323 | 2.3348 |
| 1.6938 | 2.0 | 30646 | 1.8377 |
| 1.4938 | 3.0 | 45969 | 1.6498 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.0
- Datasets 2.1.0
- Tokenizers 0.13.2
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