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mycustom_summarization_model

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

  • Loss: 2.5992
  • Rouge1: 0.1386
  • Rouge2: 0.0475
  • Rougel: 0.1129
  • Rougelsum: 0.1129
  • Gen Len: 19.0

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 4

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 62 2.8842 0.1287 0.0356 0.1075 0.1078 19.0
No log 2.0 124 2.6762 0.1303 0.0427 0.1086 0.1086 19.0
No log 3.0 186 2.6165 0.1352 0.046 0.1112 0.111 19.0
No log 4.0 248 2.5992 0.1386 0.0475 0.1129 0.1129 19.0

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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Finetuned from

Dataset used to train Asilkan/mycustom_summarization_model

Evaluation results