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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: 1.6729
  • Rouge1: 42.6
  • Rouge2: 18.7153
  • Rougel: 35.4138
  • Rougelsum: 38.8543
  • Gen Len: 16.9170

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: 32
  • eval_batch_size: 32
  • 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
1.8863 0.22 100 1.7049 42.0859 18.0002 34.7349 38.3446 16.5788
1.8463 0.43 200 1.6947 42.4056 18.3005 34.9821 38.8013 17.3614
1.8548 0.65 300 1.6792 42.585 18.5643 35.2235 38.8298 17.1514
1.8358 0.87 400 1.6772 42.1544 18.2303 34.8971 38.3609 16.5873
1.8129 1.08 500 1.6729 42.6 18.7153 35.4138 38.8543 16.9170
1.8068 1.3 600 1.6709 42.5217 18.3285 35.1455 38.5954 16.9451
1.7973 1.52 700 1.6687 42.8667 18.624 35.3429 38.9322 16.7546
1.7979 1.74 800 1.6668 42.919 18.7388 35.4528 39.0561 16.8791
1.7899 1.95 900 1.6670 43.0931 18.741 35.5047 39.2321 16.9109

Framework versions

  • Transformers 4.36.0
  • Pytorch 2.0.0
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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Model size
77M params
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F32
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Finetuned from

Dataset used to train sk-2302/flan-t5-small-samsum

Evaluation results