---
license: mit
tags:
- pytorch
- sinhala
- gpt2
model-index:
- name: sinhala-gpt2
  results: []
widget:
- text: මහ
- text: සංවිධ
- text: දුර්ලභ
- text: තනිවීලා
- text: ඔබ
inference:
  parameters:
    do_sample: false
    temperature: 0.2
language:
- si
---

# sinhala-gpt2

This particular model has undergone fine-tuning based on the [gpt2](https://huggingface.co/gpt2) architecture, utilizing a dataset of Sinhala NEWS from various sources.
Even though this version of GPT-2 has been finely tuned and is quite simple, it is still capable of generating news articles that are identical. Take, for example, the following samples(Some of them are hilarious though :D):
- "ඔබ විසින් මෙම විරෝධතාව සංවිධානය කර තිබුණේ නැහැ කියලා හිටපු ජනාධිපති මහ"
- "දුර්ලභ ගණයේ විශ්වවිද්යාල ප්රතිපාදන කොමිෂන් සභාවේ සභාපති මහාචාර්ය ජී එල්"

⚠️ Since the dataset used for this model is mostly composed of news articles, it is heavily biased towards generating news content. This bias may become apparent during the generation process.

## Training procedure
The model was trained for approximately 12+ hours on Kaggle GPUs.

## Usage Details

```python
from transformers import AutoTokenizer, AutoModelForCausalLM,pipeline

tokenizer = AutoTokenizer.from_pretrained("Ransaka/sinhala-gpt2")
model = AutoModelForCausalLM.from_pretrained("Ransaka/sinhala-gpt2")
generator("දුර") #දුර ඈත පාසැල් වියේ පසුවූයේ මෙම සිද්ධිය සම්බන්ධයෙන් විමර්ශන සිදුකරන බවයි
```
or using git
```bash
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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.3015        | 1.0   | 15323 | 2.3498             |
| 1.8582        | 2.0   | 30646 | 1.9921             |
| 1.5491        | 3.0   | 45969 | 1.9376             |


### Framework versions

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