BART-ToSSimplify / README.md
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metadata
license: mit
base_model: facebook/bart-large-cnn
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: 01_ToS-BART
    results: []

01_ToS-BART

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

  • Loss: 0.3895
  • Rouge1: 0.6186
  • Rouge2: 0.4739
  • Rougel: 0.5159
  • Rougelsum: 0.5152
  • Gen Len: 108.6354

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: 5e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 360 0.3310 0.5585 0.4013 0.4522 0.4522 116.1105
0.2783 2.0 720 0.3606 0.5719 0.4078 0.4572 0.4568 114.6796
0.2843 3.0 1080 0.3829 0.6019 0.4456 0.4872 0.4875 110.8066
0.2843 4.0 1440 0.3599 0.6092 0.4604 0.5049 0.5049 110.884
0.1491 5.0 1800 0.3895 0.6186 0.4739 0.5159 0.5152 108.6354

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.15.0
  • Tokenizers 0.15.0