t5-base-asqa-cb / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
model-index:
  - name: t5-base-asqa-cb
    results: []

t5-base-asqa-cb

This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.7489
  • Rougelsum: 26.6134

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss Rougelsum
No log 1.0 273 2.9648 23.8374
3.5538 2.0 546 2.9054 24.2701
3.5538 3.0 819 2.8744 24.4172
3.1468 4.0 1092 2.8557 24.5949
3.1468 5.0 1365 2.8400 24.7069
3.0711 6.0 1638 2.8280 24.8685
3.0711 7.0 1911 2.8191 24.9829
3.0348 8.0 2184 2.8109 25.0908
3.0348 9.0 2457 2.8038 25.2485
2.9962 10.0 2730 2.7978 25.3279
2.9635 11.0 3003 2.7920 25.4465
2.9635 12.0 3276 2.7878 25.5927
2.9328 13.0 3549 2.7833 25.6925
2.9328 14.0 3822 2.7809 25.7563
2.9126 15.0 4095 2.7773 25.8123
2.9126 16.0 4368 2.7747 25.9039
2.8878 17.0 4641 2.7719 25.9636
2.8878 18.0 4914 2.7693 26.0025
2.8744 19.0 5187 2.7673 26.0578
2.8744 20.0 5460 2.7656 26.1161
2.8579 21.0 5733 2.7629 26.1490
2.8418 22.0 6006 2.7614 26.1830
2.8418 23.0 6279 2.7604 26.2146
2.8256 24.0 6552 2.7586 26.2899
2.8256 25.0 6825 2.7586 26.2724
2.8093 26.0 7098 2.7566 26.3183
2.8093 27.0 7371 2.7551 26.3365
2.8083 28.0 7644 2.7546 26.3950
2.8083 29.0 7917 2.7537 26.4357
2.7917 30.0 8190 2.7529 26.4681
2.7917 31.0 8463 2.7526 26.5021
2.785 32.0 8736 2.7512 26.5241
2.7779 33.0 9009 2.7510 26.5361
2.7779 34.0 9282 2.7502 26.5620
2.771 35.0 9555 2.7495 26.6038
2.771 36.0 9828 2.7488 26.6161
2.7647 37.0 10101 2.7489 26.6134

Framework versions

  • Transformers 4.23.0.dev0
  • Pytorch 1.12.1+cu102
  • Datasets 2.4.0
  • Tokenizers 0.12.1