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thesis-led-finetuned-on-wcep

This model is a fine-tuned version of allenai/led-base-16384 on the wcep-10 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6816
  • Rouge1: 43.4358
  • Rouge2: 21.8159
  • Rougel: 35.0411
  • Rougelsum: 36.1007
  • Gen Len: 27.2843

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: 4
  • eval_batch_size: 4
  • 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
1.6843 1.0 2040 1.6753 42.8519 21.8933 35.0226 35.9911 25.6647
1.4083 2.0 4080 1.6672 43.5166 22.0845 35.283 36.4006 26.4098
1.1981 3.0 6120 1.6816 43.4358 21.8159 35.0411 36.1007 27.2843

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.1.2
  • Datasets 2.18.0
  • Tokenizers 0.15.2
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