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---
language: en
license: apache-2.0
datasets:
- custom
tags:
- summarization
- flan-t5
- youtube
- fine-tuned
base_model: google/flan-t5-base
model-index:
- name: Flan T5 YouTube Summarizer
results: []
metrics:
- rouge
pipeline_tag: summarization
---
# 📺 T5 YouTube Summarizer
This is a fine-tuned [flan-t5-base](https://huggingface.co/google/flan-t5-base) model for abstractive summarization of YouTube video transcripts. The model is trained on a custom dataset of video transcriptions and their manually written summaries.
---
## ✨ Model Details
- **Base Model**: [flan-t5-base](https://huggingface.co/google/flan-t5-base)
- **Task**: Abstractive Summarization
- **Training Data**: YouTube video transcripts and human-written summaries
- **Max Input Length**: 512 tokens
- **Max Output Length**: 256 tokens
- **Fine-tuning Epochs**: 5
- **Tokenizer**: T5Tokenizer (pretrained)
---
## 🧠 Intended Use
This model is designed to generate short, informative summaries from long transcripts of educational or conceptual YouTube videos. It can be used for:
- Quick understanding of long videos
- Automated content summaries for blogs, platforms, or note-taking tools
- Enhancing accessibility for long-form spoken content
---
## 🚀 How to Use
```python
from transformers import T5ForConditionalGeneration, T5Tokenizer
# Load the model
model = T5ForConditionalGeneration.from_pretrained("bilal521/flan-t5-youtube-summarizer")
tokenizer = T5Tokenizer.from_pretrained("bilal521/flan-t5-youtube-summarizer")
# Define input text
text = "The video talks about coordinate covalent bonds, giving examples from..."
# Preprocess and summarize
inputs = tokenizer.encode("summarize: " + text, return_tensors="pt", max_length=512, truncation=True)
summary_ids = model.generate(
inputs,
max_length=256,
min_length=80,
num_beams=5,
length_penalty=2.0,
no_repeat_ngram_size=3,
early_stopping=True
)
summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
print(summary)
```
## 📊 Evaluation
| Metric | Value |
| ------- | ------------ |
| ROUGE-1 | \~0.61 |
| ROUGE-2 | \~0.27 |
| ROUGE-L | \~0.48 |
| Gen Len | \~187 tokens |
## 📌 Citation
If you use this model in your work, consider citing:
```
@misc{t5ytsummarizer2025,
title={Flan T5 YouTube Transcript Summarizer},
author={Muhammad Bilal Yousaf},
year={2025},
howpublished={\url{https://huggingface.co/bilal521/flan-t5-youtube-summarizer}},
}
``` |