---
language: en
tags:
- summarization
- t5
- cnn-dailymail
datasets:
- abisee/cnn_dailymail
metrics:
- rouge
pipeline_tag: summarization
---

# T5-small Fine-Tuned on CNN/DailyMail

This model generates abstractive summaries of English news articles.

## Model Details
- **Base model:** t5-small
- **Dataset:** CNN/DailyMail v3.0.0
- **Task:** Abstractive text summarization
- **Framework:** PyTorch + HuggingFace Transformers

## Performance (ROUGE, on held-out test sample)
| Metric | Score |
|---|---|
| ROUGE-1 | 36.1 |
| ROUGE-2 | 15.36 |
| ROUGE-L | 26.07 |

## How to Use

⚠️ This model requires the `"summarize: "` prefix on every input, since it's a T5 model.

```python
from transformers import pipeline

summarizer = pipeline("summarization", model="samandar1105/text-summarizer")
text = "summarize: " + "YOUR LONG ARTICLE TEXT HERE"
result = summarizer(text, max_length=80, min_length=20, do_sample=False)
print(result[0]["summary_text"])
```

## Training Details
- Learning rate: 3e-5
- Epochs: 4
- Batch size: 8
- Max input length: 512 tokens
- Max target length: 128 tokens