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fairnightzz/t5-small-finetuned-notes2anki-v1

This model is a fine-tuned version of fairnightzz/t5-small-finetuned-notes2anki-v1 on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 2.0038
  • Validation Loss: 1.8288
  • Train Rouge1: 13.1471
  • Train Rouge2: 8.0633
  • Train Rougel: 11.5696
  • Train Rougelsum: 12.9462
  • Train Gen Len: 19.0
  • Epoch: 19

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:

  • optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Rouge1 Train Rouge2 Train Rougel Train Rougelsum Train Gen Len Epoch
3.4022 2.7364 11.2311 4.8587 8.7075 10.4700 19.0 0
3.1245 2.5569 10.5563 4.2629 8.3375 9.8786 19.0 1
2.9024 2.4407 11.8667 6.4823 9.7059 11.2729 19.0 2
2.7711 2.3598 11.8220 7.0101 10.1169 11.6068 19.0 3
2.6620 2.2961 10.8857 5.9477 9.2469 10.6552 19.0 4
2.5896 2.2397 11.2067 6.5960 9.7992 10.9471 19.0 5
2.5014 2.1927 9.9929 5.4838 8.5468 9.7819 19.0 6
2.4545 2.1455 10.8128 5.8837 8.7679 10.3815 19.0 7
2.3996 2.1049 11.3686 5.9480 8.9953 10.6468 19.0 8
2.3564 2.0707 10.7723 5.1838 8.6172 10.1052 19.0 9
2.3213 2.0349 11.2138 5.9159 9.1719 10.5998 19.0 10
2.2527 2.0028 10.9398 6.1004 9.2349 10.1944 19.0 11
2.2318 1.9755 10.9252 6.2422 9.1758 10.1406 19.0 12
2.1920 1.9456 11.1478 6.5824 9.6520 10.6710 19.0 13
2.1522 1.9267 11.3610 6.4087 9.9797 10.9126 19.0 14
2.1173 1.9031 11.3989 6.5776 10.1344 10.9575 19.0 15
2.0782 1.8845 13.2115 8.1938 11.6289 12.9284 19.0 16
2.0779 1.8688 13.1524 8.1482 11.5699 12.8713 19.0 17
2.0447 1.8506 13.2316 8.2242 11.6640 12.9850 19.0 18
2.0038 1.8288 13.1471 8.0633 11.5696 12.9462 19.0 19

Framework versions

  • Transformers 4.35.2
  • TensorFlow 2.15.0
  • Datasets 2.16.1
  • Tokenizers 0.15.0
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