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End of training
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metadata
license: apache-2.0
base_model: google/flan-t5-small
tags:
  - generated_from_trainer
datasets:
  - samsum
metrics:
  - rouge
model-index:
  - name: flan-t5-small-samsum
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: samsum
          type: samsum
          config: samsum
          split: test
          args: samsum
        metrics:
          - name: Rouge1
            type: rouge
            value: 42.6766

flan-t5-small-samsum

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

  • Loss: 1.6754
  • Rouge1: 42.6766
  • Rouge2: 18.3823
  • Rougel: 35.2377
  • Rougelsum: 38.9432
  • Gen Len: 16.8474

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: 52
  • eval_batch_size: 52
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
1.8824 0.35 100 1.7015 42.4882 18.3559 35.0843 38.8515 16.6532
1.8578 0.7 200 1.6878 42.0007 18.2614 34.9474 38.4992 16.7216
1.835 1.06 300 1.6823 42.7535 18.6418 35.3807 39.0098 16.9048
1.8144 1.41 400 1.6786 42.6326 18.4197 35.2995 38.9165 16.6618
1.8094 1.76 500 1.6754 42.6766 18.3823 35.2377 38.9432 16.8474

Framework versions

  • Transformers 4.36.0
  • Pytorch 2.0.0
  • Datasets 2.15.0
  • Tokenizers 0.15.0