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bart_summarisation

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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="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