t5-base-samsum / README.md
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metadata
license: apache-2.0
tags:
  - summarization
  - generated_from_trainer
datasets:
  - samsum
metrics:
  - rouge
model-index:
  - name: t5-base-samsum
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: samsum
          type: samsum
          config: samsum
          split: validation
          args: samsum
        metrics:
          - name: Rouge1
            type: rouge
            value: 48.9131

t5-base-samsum

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

  • Loss: 0.6172
  • Rouge1: 48.9131
  • Rouge2: 25.4942
  • Rougel: 41.2363
  • Rougelsum: 45.3434

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
0.7606 1.0 3683 0.6254 46.9778 23.8245 39.8294 43.4639
0.6273 2.0 7366 0.6119 48.2515 24.7534 40.4415 44.5567
0.5769 3.0 11049 0.6116 48.228 24.7865 40.7537 44.4026
0.5412 4.0 14732 0.6145 48.8563 25.356 41.1913 45.186
0.5199 5.0 18415 0.6172 48.9131 25.4942 41.2363 45.3434

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.12.0
  • Tokenizers 0.13.3