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flan-t5-small-samsum

This model is a fine-tuned version of google/flan-t5-small on the samsum dataset. It achieves the following results on the evaluation set:

  • Loss: 1.6754
  • Rouge1: 42.6698
  • Rouge2: 18.3442
  • Rougel: 35.2697
  • Rougelsum: 38.9457
  • Gen Len: 16.8474

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: 52
  • eval_batch_size: 52
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
1.8824 0.35 100 1.7015 42.477 18.2999 35.0949 38.8554 16.6532
1.8578 0.7 200 1.6878 42.0138 18.2348 34.9449 38.4907 16.7216
1.835 1.06 300 1.6823 42.7733 18.5982 35.3899 39.0215 16.9048
1.8144 1.41 400 1.6786 42.6285 18.384 35.3233 38.9203 16.6618
1.8094 1.76 500 1.6754 42.6698 18.3442 35.2697 38.9457 16.8474

Framework versions

  • Transformers 4.36.0
  • Pytorch 2.0.0
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Dataset used to train jerdna120/flan-t5-small-samsum

Evaluation results