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my_awesome_billsum_model_12

This model is a fine-tuned version of google-t5/t5-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6167
  • Rouge1: 0.9635
  • Rouge2: 0.8396
  • Rougel: 0.8914
  • Rougelsum: 0.8919
  • Gen Len: 5.1042

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: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 12 2.0578 0.4077 0.2938 0.3916 0.3923 17.6458
No log 2.0 24 1.5690 0.4152 0.2977 0.4017 0.4017 17.3125
No log 3.0 36 1.1237 0.47 0.3505 0.4472 0.4469 15.4792
No log 4.0 48 0.8172 0.7763 0.6588 0.7333 0.7354 8.8542
No log 5.0 60 0.6854 0.9174 0.7868 0.8455 0.8454 6.0833
No log 6.0 72 0.6514 0.9635 0.8396 0.8914 0.8919 5.1042
No log 7.0 84 0.6364 0.9635 0.8396 0.8914 0.8919 5.1042
No log 8.0 96 0.6261 0.9635 0.8396 0.8914 0.8919 5.1042
No log 9.0 108 0.6202 0.9635 0.8396 0.8914 0.8919 5.1042
No log 10.0 120 0.6167 0.9635 0.8396 0.8914 0.8919 5.1042

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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