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sum_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: 2.5387
  • Rouge1: 0.1448
  • Rouge2: 0.0511
  • Rougel: 0.1163
  • Rougelsum: 0.1161
  • 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
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 62 2.8238 0.1286 0.0385 0.106 0.1063 19.0
No log 2.0 124 2.6166 0.1387 0.0478 0.1128 0.1126 19.0
No log 3.0 186 2.5555 0.1453 0.0532 0.1173 0.1172 19.0
No log 4.0 248 2.5387 0.1448 0.0511 0.1163 0.1161 19.0

Framework versions

  • Transformers 4.35.0
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.14.1
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Base model

google-t5/t5-small
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Dataset used to train maniack/sum_model

Evaluation results