---

language: en tags:

• sagemaker
• bart
• summarization license: apache-2.0 datasets:
• samsum model-index:
• name: bart-large-cnn-samsum results:
  • task: name: Abstractive Text Summarization type: abstractive-text-summarization dataset: name: SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization type: samsum metrics:
    • name: Validation ROGUE-1 type: rogue-1 value: 42.621
    • name: Validation ROGUE-2 type: rogue-2 value: 21.9825
    • name: Validation ROGUE-L type: rogue-l value: 33.034
    • name: Test ROGUE-1 type: rogue-1 value: 41.3174
    • name: Test ROGUE-2 type: rogue-2 value: 20.8716
    • name: Test ROGUE-L type: rogue-l value: 32.1337 widget:
• text: | 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

---

bart-large-cnn-samsum

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

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
}

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                                           
'''
nlp(conversation)

Results

key	value
eval_rouge1	42.621
eval_rouge2	21.9825
eval_rougeL	33.034
eval_rougeLsum	39.6783
test_rouge1	41.3174
test_rouge2	20.8716
test_rougeL	32.1337
test_rougeLsum	38.4149