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update model card README.md
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metadata
license: apache-2.0
tags:
  - summarisation
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: >-
      bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-news-Sumy
    results: []

bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-news-Sumy

This model is a fine-tuned version of mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5583
  • Rouge1: 55.2899
  • Rouge2: 43.2426
  • Rougel: 38.5056
  • Rougelsum: 53.8807

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: 5.6e-05
  • 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: 8

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
1.7407 1.0 223 1.5900 51.3058 38.3952 35.7343 49.7129
1.4813 2.0 446 1.5500 53.8089 41.2455 37.3864 52.3387
1.3517 3.0 669 1.5429 53.4914 40.907 37.1428 52.0338
1.2432 4.0 892 1.5472 54.1139 41.3589 37.6392 52.711
1.1748 5.0 1115 1.5426 55.3482 43.312 38.0625 54.0424
1.1108 6.0 1338 1.5529 55.4752 43.3561 38.5813 54.1141
1.0745 7.0 1561 1.5539 55.705 43.6772 38.7629 54.3892
1.0428 8.0 1784 1.5583 55.2899 43.2426 38.5056 53.8807

Framework versions

  • Transformers 4.21.0
  • Pytorch 1.12.0+cu113
  • Datasets 2.4.0
  • Tokenizers 0.12.1