metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - samsum
metrics:
  - rouge
model-index:
  - name: bart-large-cnn-samsum
    results:
      - task:
          type: summarization
          name: Summarization
        dataset:
          name: >-
            SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive
            Summarization
          type: samsum
        metrics:
          - type: rogue-1
            value: 43.6283
            name: Validation ROGUE-1
          - type: rogue-2
            value: 19.3096
            name: Validation ROGUE-2
          - type: rogue-l
            value: 41.214
            name: Validation ROGUE-L

bart-large-cnn-samsum

This model is a fine-tuned version of facebook/bart-large-cnn on the samsum dataset. It achieves the following results on the evaluation set:

Loss: 0.755
Rouge1: 43.6283
Rouge2: 19.3096
Rougel: 41.2140
Rougelsum: 37.2590

Model description

More information needed

Intended uses & limitations

from transformers import pipeline
summarizer = pipeline("summarization", model="AdamCodd/bart-large-cnn-samsum")

conversation = '''Sugi: I am tired of everything in my life.
Tommy: What? How happy your life is! I do envy you.
Sugi: You don't know that I have been overprotected by my mother these years. I am really about to leave the family and spread my wings.
Tommy: Maybe you are right.                                         
'''
summarizer(conversation)

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 3e-05
train_batch_size: 4
eval_batch_size: 4
seed: 1270
optimizer: AdamW with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 150
num_epochs: 1

Training results

key	value
eval_rouge1	43.6283
eval_rouge2	19.3096
eval_rougeL	41.2140
eval_rougeLsum	37.2590

Framework versions

Transformers 4.33.2
Pytorch lightning 2.0.9
Tokenizers 0.13.3