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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: 42.6378

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: 1.6629
  • Rouge1: 42.6378
  • Rouge2: 18.2896
  • Rougel: 35.1851
  • Rougelsum: 38.8113
  • Gen Len: 16.8596

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: 40
  • eval_batch_size: 40
  • 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
1.7932 0.27 100 1.6830 42.7032 18.4803 35.278 38.9331 17.0403
1.8102 0.54 200 1.6701 42.2811 18.2246 35.0893 38.4619 16.7265
1.8279 0.81 300 1.6658 42.6465 18.6939 35.4208 38.9399 16.8120
1.802 1.08 400 1.6633 42.5867 18.3579 35.3253 38.7049 16.6862
1.773 1.36 500 1.6629 42.6378 18.2896 35.1851 38.8113 16.8596
1.7752 1.63 600 1.6598 42.7111 18.3689 35.4218 38.8698 16.9328
1.7688 1.9 700 1.6589 42.6972 18.3536 35.3153 38.7976 17.0073

Framework versions

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