slauw87/bart_summarisation

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