模型:
slauw87/bart_summarisation
该模型是使用Amazon SageMaker和新的Hugging Face Deep Learning容器进行训练的。欲了解更多信息,请查看:
{ "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
}
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)
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 |