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metadata
license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
datasets:
  - samsum
metrics:
  - rouge
model-index:
  - name: t5-small-t5-dialogue-summarizer
    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: 41.8545

t5-small-t5-dialogue-summarizer

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

  • Loss: 1.7739
  • Rouge1: 41.8545
  • Rouge2: 19.0397
  • Rougel: 35.2065
  • Rougelsum: 38.8278
  • Gen Len: 16.6222

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
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • 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 1.0 460 1.7926 41.5391 18.4858 34.6806 38.3183 16.6663
1.9666 2.0 921 1.7810 41.5694 18.5639 34.9915 38.4652 16.5599
1.9457 3.0 1381 1.7785 42.0475 19.0086 35.2119 38.8236 16.6858
1.9241 4.0 1840 1.7739 41.8545 19.0397 35.2065 38.8278 16.6222

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0