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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: 42.6976

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: 42.6976
  • Rouge2: 18.3401
  • Rougel: 35.2388
  • Rougelsum: 38.9044
  • 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 42.4907 18.3171 35.0684 38.8292 16.6532
1.8578 0.7 200 1.6878 42.0288 18.2503 34.9411 38.4881 16.7216
1.835 1.06 300 1.6823 42.742 18.6174 35.3759 38.992 16.9048
1.8144 1.41 400 1.6786 42.6286 18.3873 35.3084 38.8797 16.6618
1.8094 1.76 500 1.6754 42.6976 18.3401 35.2388 38.9044 16.8474

Framework versions

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