mrupar's picture
End of training
c385515
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: 42.6693

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: 42.6693
  • Rouge2: 18.3378
  • Rougel: 35.2729
  • Rougelsum: 38.9033
  • 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 42.4703 18.3068 35.1199 38.8083 16.6532
1.8578 0.7 200 1.6878 42.0064 18.2236 34.9497 38.4611 16.7216
1.835 1.06 300 1.6823 42.7407 18.5955 35.4344 38.9663 16.9048
1.8144 1.41 400 1.6786 42.6272 18.3894 35.34 38.8868 16.6618
1.8094 1.76 500 1.6754 42.6693 18.3378 35.2729 38.9033 16.8474

Framework versions

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