# Summarization Fine-tuning Dataset

A dataset of 2000 examples for fine-tuning small language models on summarization tasks.

## Statistics

- **Total examples**: 2000
- **Train examples**: 1600 (80.0%)
- **Validation examples**: 200 (10.0%)
- **Test examples**: 200 (10.0%)

## Dataset Distribution

| Dataset | Count | Percentage |
|---------|-------|------------|
| xsum | 2000 | 100.0% |

## Format

The dataset is provided in alpaca format.

## Configuration

- **Maximum tokens**: 2000
- **Tokenizer**: gpt2
- **Random seed**: 42

## Usage

```python
from datasets import load_dataset

# Load the dataset
dataset = load_dataset("YOUR_USERNAME/summarization-finetune-10k")

# Access the splits
train_data = dataset["train"]
val_data = dataset["validation"]
test_data = dataset["test"]
```