metadata

license: apache-2.0
tags:
  - summarization
  - generated_from_trainer
datasets:
  - cnn_dailymail
metrics:
  - rouge
model-index:
  - name: bart-base-finetuned-cnn-news
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: cnn_dailymail
          type: cnn_dailymail
          config: 3.0.0
          split: validation
          args: 3.0.0
        metrics:
          - name: Rouge1
            type: rouge
            value: 21.8948

bart-base-finetuned-cnn-news

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

Loss: 2.8560
Rouge1: 21.8948
Rouge2: 9.7157
Rougel: 17.9348
Rougelsum: 20.5347

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.00056
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
3.7005	1.0	718	2.9872	21.7279	9.0406	17.392	20.0627
2.937	2.0	1436	2.8590	21.3056	8.5254	17.2338	20.0403
2.2642	3.0	2154	2.6744	21.277	9.6162	17.7775	20.1688
1.5774	4.0	2872	2.7020	21.7458	9.846	18.1649	20.7067
1.0174	5.0	3590	2.8560	21.8948	9.7157	17.9348	20.5347

Framework versions

Transformers 4.27.2
Pytorch 1.13.1+cu117
Datasets 2.11.0
Tokenizers 0.13.3