2-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: 02_ToS-BART
    results: []

02_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: 0.5697
  • Rouge1: 0.6086
  • Rouge2: 0.4577
  • Rougel: 0.5072
  • Rougelsum: 0.5071
  • Gen Len: 110.7293

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: 3e-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: 6
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 360 0.5018 0.5957 0.44 0.4873 0.4876 110.8398
0.049 2.0 720 0.5468 0.5923 0.4364 0.4812 0.4813 111.6133
0.0789 3.0 1080 0.5157 0.6035 0.4439 0.4933 0.4934 110.1768
0.0789 4.0 1440 0.5905 0.5873 0.4279 0.4781 0.4781 110.8343
0.044 5.0 1800 0.5581 0.6046 0.4544 0.5023 0.502 110.8674
0.0231 6.0 2160 0.5697 0.6086 0.4577 0.5072 0.5071 110.7293

Framework versions

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