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This model is a fine-tuned version of google/pegasus-cnn_dailymail on the samsum dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4919

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: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
1.6776 0.54 500 1.4919

Framework versions

  • Transformers 4.22.2
  • Pytorch 1.12.1+cpu
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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Dataset used to train Lwhieldon/pegasus-samsum

Space using Lwhieldon/pegasus-samsum 1