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---
language: id
tags:
- gpt2-indo-small-kids-stories
license: mit
widget:
- text: "Archie sedang mengendarai roket ke planet Mars."
---
## GPT-2 Indonesian Small Kids Stories
GPT-2 Indonesian Small Kids Stories is a causal language model based on the [OpenAI GPT-2](https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf) model. The model was originally the pre-trained [GPT2 Small Indonesian](https://huggingface.co/flax-community/gpt2-small-indonesian) model, which was then fine-tuned on Indonesian kids' stories from [Room To Read](https://literacycloud.org/) and [Let's Read](https://reader.letsreadasia.org/).
10% of the dataset was kept for evaluation purposes. The pre-trained model was fine-tuned and achieved an evaluation loss of 3.777 and an evaluation perplexity of 43.68.
Hugging Face's `Trainer` class from the [Transformers](https://huggingface.co/transformers) library was used to train the model. PyTorch was used as the backend framework during training, but the model remains compatible with other frameworks nonetheless.
## Model
| Model | #params | Arch. | Training/Validation data (text) |
| ------------------------------ | ------- | ---------- | --------------------------------- |
| `gpt2-indo-small-kids-stories` | 124M | GPT2 Small | Indonesian Kids' Stories (860 KB) |
## Evaluation Results
The model was fine-tuned for 10 epochs.
| Epoch | Training Loss | Validation Loss |
| ----- | ------------- | --------------- |
| 1 | 4.259600 | 4.020201 |
| 2 | 3.979100 | 3.911295 |
| 3 | 3.818300 | 3.849313 |
| 4 | 3.691600 | 3.809931 |
| 5 | 3.589300 | 3.789201 |
| 6 | 3.506200 | 3.778665 |
| 7 | 3.439200 | 3.774871 |
| 8 | 3.387600 | 3.774859 |
| 9 | 3.351300 | 3.776672 |
| 10 | 3.330100 | 3.776935 |
## How to Use (PyTorch)
### As Causal Language Model
```python
from transformers import pipeline
pretrained_name = "bookbot/gpt2-indo-small-kids-stories"
nlp = pipeline(
"text-generation",
model=pretrained_name,
tokenizer=pretrained_name
)
nlp("Archie sedang mengendarai roket ke planet Mars.")
```
### Feature Extraction in PyTorch
```python
from transformers import GPT2LMHeadModel, GPT2TokenizerFast
pretrained_name = "bookbot/gpt2-indo-small-kids-stories"
model = GPT2LMHeadModel.from_pretrained(pretrained_name)
tokenizer = GPT2TokenizerFast.from_pretrained(pretrained_name)
prompt = "Archie sedang mengendarai roket ke planet Mars."
encoded_input = tokenizer(prompt, return_tensors='pt')
output = model(**encoded_input)
```
## Disclaimer
Do consider the biases which come from both the pre-trained GPT-2 model and the Indonesian Kids' Stories dataset that may be carried over into the results of this model.
## Author
GPT-2 Indonesian Small Kids Stories was trained and evaluated by [Wilson Wongso](https://w11wo.github.io/). All computation and development are done on Google Colaboratory using their free GPU access.
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