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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - billsum
metrics:
  - rouge
  - bleu
model-index:
  - name: T5-small_finetuned_billsum_subset_model_bs16_lr5e-05
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: billsum
          type: billsum
          config: default
          split: ca_test
          args: default
        metrics:
          - name: Rouge1
            type: rouge
            value: 0.1918
          - name: Bleu
            type: bleu
            value: 0.0008

T5-small_finetuned_billsum_subset_model_bs16_lr5e-05

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

  • Loss: 2.0113
  • Rouge1: 0.1918
  • Rouge2: 0.0975
  • Rougel: 0.1668
  • Rougelsum: 0.1665
  • Gen Len: 19.0
  • Bleu: 0.0008

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: 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 Bleu
No log 1.0 62 2.0260 0.1936 0.0982 0.1681 0.1678 19.0 0.0008
No log 2.0 124 2.0155 0.1908 0.0949 0.1659 0.1656 19.0 0.0007
No log 3.0 186 2.0131 0.1902 0.0948 0.1651 0.1646 19.0 0.0008
No log 4.0 248 2.0113 0.1918 0.0975 0.1668 0.1665 19.0 0.0008

Framework versions

  • Transformers 4.27.4
  • Pytorch 2.0.0+cu118
  • Datasets 2.11.0
  • Tokenizers 0.13.3