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distilbart-xsum-12-3-whole_summary_chatGPT_and_tweetsum

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-3 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.7952
  • Rouge1: 45.7353
  • Rouge2: 29.1566
  • Rougel: 45.8429
  • Rougelsum: 45.7353
  • Gen Len: 16.6

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: 2e-05
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 397 2.8069 42.233 23.7538 39.2701 39.2701 17.0
2.8673 2.0 794 2.7736 48.2389 29.6927 43.5004 43.5004 17.4
1.8043 3.0 1191 2.7952 45.7353 29.1566 45.8429 45.7353 16.6

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.12.1
  • Datasets 2.6.1
  • Tokenizers 0.12.1
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