bart-large-finetuned-aeslc-test

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

  • Loss: 2.4993
  • Rouge1: 34.1259
  • Rouge2: 18.262
  • Rougel: 33.121
  • Rougelsum: 33.1402
  • Gen Len: 10.1516

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

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
3.1135 1.0 980 2.4993 34.1259 18.262 33.121 33.1402 10.1516

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.3
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Dataset used to train sohamchougule/bart-large-finetuned-aeslc-test

Evaluation results