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Kankanaghosh/summarisation_model

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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summarisation_model

This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.3693
  • Rouge1: 0.3115
  • Rouge2: 0.1433
  • Rougel: 0.2744
  • Rougelsum: 0.2741
  • Gen Len: 19.957

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
  • trainbatchsize: 16
  • evalbatchsize: 16
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMWTORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizerargs=No additional optimizer arguments
  • lrschedulertype: linear
  • num_epochs: 4
  • mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation LossRouge1Rouge2RougelRougelsumGen Len
No log1.01052.46040.28650.1250.24960.249319.9403
No log2.02102.39960.30230.13760.26540.265519.9379
No log3.03152.37550.30860.14220.27130.271619.9332
No log4.04202.36930.31150.14330.27440.274119.957

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0