t5-small-finetuned-samsum-en

This model is a fine-tuned version of t5-small on the samsum dataset. It achieves the following results on the evaluation set:

  • Loss: 1.9335
  • Rouge1: 44.3313
  • Rouge2: 20.71
  • Rougel: 37.221
  • Rougelsum: 40.9603

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: 5.6e-05
  • train_batch_size: 10
  • eval_batch_size: 10
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
1.4912 1.0 300 1.9043 44.1517 20.0186 36.6053 40.5164
1.5055 2.0 600 1.8912 44.1473 20.4456 37.069 40.6714
1.4852 3.0 900 1.8986 44.7536 20.8646 37.525 41.2189
1.4539 4.0 1200 1.9136 44.2144 20.3446 37.1088 40.7581
1.4262 5.0 1500 1.9215 44.2656 20.6044 37.3267 40.9469
1.4118 6.0 1800 1.9247 43.8793 20.4663 37.0614 40.6065
1.3987 7.0 2100 1.9256 43.9981 20.2703 36.7856 40.6354
1.3822 8.0 2400 1.9316 43.9732 20.4559 36.8039 40.5784
1.3773 9.0 2700 1.9314 44.3075 20.5435 37.0457 40.832
1.3795 10.0 3000 1.9335 44.3313 20.71 37.221 40.9603

Framework versions

  • Transformers 4.19.2
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.2
  • Tokenizers 0.12.1
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Dataset used to train santiviquez/t5-small-finetuned-samsum-en

Evaluation results