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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: 42.6907

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: 42.6907
  • Rouge2: 18.3626
  • Rougel: 35.2723
  • Rougelsum: 38.9062
  • 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 42.4935 18.3634 35.0823 38.8358 16.6532
1.8578 0.7 200 1.6878 42.0329 18.2685 34.9421 38.4636 16.7216
1.835 1.06 300 1.6823 42.7493 18.6379 35.4001 38.9845 16.9048
1.8144 1.41 400 1.6786 42.6157 18.4093 35.3149 38.8787 16.6618
1.8094 1.76 500 1.6754 42.6907 18.3626 35.2723 38.9062 16.8474

Framework versions

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