This model is a fine-tuned version of GPT-2 (small) trained on the TinyStories dataset — a large collection of short, simple stories for children.
The goal of this project is to create a lightweight, fun, and creative story generator that can produce short, imaginative stories from user prompts.

✨ Intended Use

Use this model for:

Generating short, creative stories
Educational or entertainment purposes
Quick writing inspiration or kids’ content

Example use:

python

from transformers import pipeline
generator = pipeline("text-generation", model="Fathi7ma/tiny-stories-gpt2")
prompt = "A tiny robot who wanted to fly"
print(generator(prompt, max_length=80, num_return_sequences=1)[0]["generated_text"])


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.9127        | 1.0   | 2375 | 1.7789          |
| 1.7876        | 2.0   | 4750 | 1.7186          |
| 1.6976        | 3.0   | 7125 | 1.6995          |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1