🚀 bart-large-cnn-samsum

This model was trained using Amazon SageMaker and the new Hugging Face Deep Learning container, aiming to provide high - quality summarization services.

🚀 Quick Start

This model was trained using Amazon SageMaker and the new Hugging Face Deep Learning container.

For more information look at:

• 🤗 Transformers Documentation: Amazon SageMaker
• Example Notebooks
• Amazon SageMaker documentation for Hugging Face
• Python SDK SageMaker documentation for Hugging Face
• Deep Learning Container

✨ Features

⚠️ Important Note

If you want to use the model you should try a newer fine - tuned FLAN - T5 version [philschmid/flan - t5 - base - samsum](https://huggingface.co/philschmid/flan - t5 - base - samsum) out scoring the BART version with +6 on ROGUE1 achieving 47.24.

TRY [philschmid/flan - t5 - base - samsum](https://huggingface.co/philschmid/flan - t5 - base - samsum)

📦 Installation

No specific installation steps are provided in the original document.

💻 Usage Examples

Basic Usage

from transformers import pipeline
summarizer = pipeline("summarization", model="philschmid/bart-large-cnn-samsum")

conversation = '''Jeff: Can I train a 🤗 Transformers model on Amazon SageMaker? 
Philipp: Sure you can use the new Hugging Face Deep Learning Container. 
Jeff: ok.
Jeff: and how can I get started? 
Jeff: where can I find documentation? 
Philipp: ok, ok you can find everything here. https://huggingface.co/blog/the-partnership-amazon-sagemaker-and-hugging-face                                           
'''
summarizer(conversation)

📚 Documentation

Hyperparameters

{
    "dataset_name": "samsum",
    "do_eval": true,
    "do_predict": true,
    "do_train": true,
    "fp16": true,
    "learning_rate": 5e-05,
    "model_name_or_path": "facebook/bart-large-cnn",
    "num_train_epochs": 3,
    "output_dir": "/opt/ml/model",
    "per_device_eval_batch_size": 4,
    "per_device_train_batch_size": 4,
    "predict_with_generate": true,
    "seed": 7
}

Results

📄 License

This project is licensed under the MIT license.