readme: 
  ---
  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: 43.2111
         - name: Validation ROGUE-2
           type: rogue-2
           value: 22.3519
         - name: Validation ROGUE-L
           type: rogue-l
           value: 33.315
         - name: Test ROGUE-1
           type: rogue-1
           value: 41.8283
         - name: Test ROGUE-2
           type: rogue-2
           value: 20.9857
         - name: Test ROGUE-L
           type: rogue-l
           value: 32.3602
  widget:
  - text: | 
      Sugi: I am tired of everything in my life. 
      Tommy: What? How happy you life is! I do envy you.
      Sugi: You don't know that I have been over-protected by my mother these years. I am really about to leave the family and spread my wings.
      Tommy: Maybe you are right. 
  ---
  ## `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](https://huggingface.co/transformers/sagemaker.html)
  - [Example Notebooks](https://github.com/huggingface/notebooks/tree/master/sagemaker)
  - [Amazon SageMaker documentation for Hugging Face](https://docs.aws.amazon.com/sagemaker/latest/dg/hugging-face.html)
  - [Python SDK SageMaker documentation for Hugging Face](https://sagemaker.readthedocs.io/en/stable/frameworks/huggingface/index.html)
  - [Deep Learning Container](https://github.com/aws/deep-learning-containers/blob/master/available_images.md#huggingface-training-containers)
  ## 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="slauw87/bart-large-cnn-samsum")
      conversation = '''Sugi: I am tired of everything in my life. 
      Tommy: What? How happy you life is! I do envy you.
      Sugi: You don't know that I have been over-protected by my mother these years. I am really about to leave the family and spread my wings.
      Tommy: Maybe you are right.                                           
      '''
      nlp(conversation)
  ## Results
  | key | value |
  | --- | ----- |
  | eval_rouge1 | 43.2111 |
  | eval_rouge2 | 22.3519 |
  | eval_rougeL | 33.3153 |
  | eval_rougeLsum | 40.0527 |
  | predict_rouge1 | 41.8283 |
  | predict_rouge2 | 20.9857 |
  | predict_rougeL | 32.3602 |
  | predict_rougeLsum | 38.7316 |
  