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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - summarize_from_feedback
metrics:
  - rouge
model-index:
  - name: flan-t5-large-finetuned-openai-summarize_from_feedback
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: summarize_from_feedback
          type: summarize_from_feedback
          config: comparisons
          split: train
          args: comparisons
        metrics:
          - name: Rouge1
            type: rouge
            value: 30.2401
          - name: Rouge2
            type: rouge
            value: 11.4916
          - name: RougeL
            type: rouge
            value: 24.6485
          - name: RougeLSum
            type: rouge
            value: 26.1801
pipeline_tag: summarization

flan-t5-large-finetuned-openai-summarize_from_feedback

This model is a fine-tuned version of google/flan-t5-large on the summarize_from_feedback dataset. It achieves the following results on the evaluation set:

  • Loss: 2.3118
  • Rouge1: 30.2401
  • Rouge2: 11.4916
  • Rougel: 24.6485
  • Rougelsum: 26.1801
  • Gen Len: 18.8428

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: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 6

Training results

See Tensorboard

Citation

@misc {manuel_romero_2023,
    author       = { {Manuel Romero} },
    title        = { flan-t5-large-finetuned-openai-summarize_from_feedback (Revision 51666f9) },
    year         = 2023,
    url          = { https://huggingface.co/mrm8488/flan-t5-large-finetuned-openai-summarize_from_feedback },
    doi          = { 10.57967/hf/0266 },
    publisher    = { Hugging Face }
}

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0+cu116
  • Datasets 2.8.0
  • Tokenizers 0.13.2