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text_shortening_model_v74

Text2Text Generation
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PyTorch
t5
Generated from Trainer
text-generation-inference
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metadata
license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
model-index:
  - name: text_shortening_model_v74
    results: []

text_shortening_model_v74

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

  • Loss: 1.2644
  • Bert precision: 0.8826
  • Bert recall: 0.8851
  • Bert f1-score: 0.8832
  • Average word count: 6.7137
  • Max word count: 16
  • Min word count: 2
  • Average token count: 10.6547
  • % shortened texts with length > 12: 2.6026

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 40

Training results

Training Loss Epoch Step Validation Loss Bert precision Bert recall Bert f1-score Average word count Max word count Min word count Average token count % shortened texts with length > 12
2.5095 1.0 37 1.9952 0.8247 0.8396 0.8308 8.5926 19 0 12.961 12.8128
2.1271 2.0 74 1.7552 0.8393 0.8454 0.841 7.7247 17 0 11.7738 9.3093
1.9629 3.0 111 1.6420 0.8552 0.8582 0.8556 7.2022 17 1 11.3193 6.5065
1.8511 4.0 148 1.5687 0.8646 0.8639 0.8634 6.8078 17 1 10.8539 4.1041
1.7806 5.0 185 1.5196 0.8684 0.8693 0.8681 6.8278 16 1 10.8438 3.8038
1.7193 6.0 222 1.4840 0.8713 0.8736 0.8717 6.8388 18 2 10.8318 3.4034
1.6763 7.0 259 1.4540 0.8756 0.8765 0.8754 6.7528 18 2 10.6847 3.003
1.6389 8.0 296 1.4316 0.8766 0.8785 0.8769 6.7628 16 2 10.6917 2.6026
1.6146 9.0 333 1.4149 0.8771 0.8798 0.8778 6.8018 15 2 10.7177 2.7027
1.597 10.0 370 1.3986 0.8782 0.8811 0.879 6.7998 15 2 10.7067 2.5025
1.5761 11.0 407 1.3860 0.8792 0.8815 0.8797 6.7588 15 2 10.6496 2.3023
1.5456 12.0 444 1.3747 0.8792 0.8813 0.8797 6.7387 16 2 10.6376 2.2022
1.533 13.0 481 1.3647 0.88 0.8823 0.8805 6.7347 16 2 10.6276 2.1021
1.5142 14.0 518 1.3536 0.8805 0.8822 0.8808 6.7047 16 2 10.5746 1.9019
1.514 15.0 555 1.3429 0.8803 0.882 0.8805 6.6847 16 2 10.5606 1.7017
1.4973 16.0 592 1.3353 0.8805 0.8828 0.881 6.7467 16 2 10.6627 2.1021
1.4792 17.0 629 1.3277 0.8811 0.8829 0.8814 6.7077 16 2 10.6166 2.002
1.4669 18.0 666 1.3206 0.8815 0.8831 0.8817 6.6927 16 2 10.6016 2.1021
1.4667 19.0 703 1.3141 0.881 0.8831 0.8815 6.7167 16 2 10.6306 2.1021
1.4497 20.0 740 1.3097 0.8808 0.883 0.8813 6.7227 16 2 10.6416 2.1021
1.4533 21.0 777 1.3053 0.8814 0.8831 0.8817 6.6997 16 2 10.6086 2.1021
1.4408 22.0 814 1.2998 0.8808 0.8825 0.881 6.7037 16 2 10.6076 2.2022
1.4343 23.0 851 1.2958 0.8807 0.8829 0.8812 6.7297 16 2 10.6306 2.3023
1.4295 24.0 888 1.2926 0.881 0.8833 0.8816 6.7427 16 2 10.6486 2.4024
1.4219 25.0 925 1.2887 0.8812 0.8835 0.8818 6.7327 16 2 10.6426 2.4024
1.4045 26.0 962 1.2855 0.8814 0.8836 0.8819 6.7187 16 2 10.6256 2.4024
1.409 27.0 999 1.2826 0.8817 0.884 0.8823 6.7217 16 2 10.6456 2.6026
1.3994 28.0 1036 1.2803 0.8826 0.8848 0.8831 6.7047 16 2 10.6226 2.7027
1.3905 29.0 1073 1.2778 0.8823 0.8847 0.8829 6.7267 16 2 10.6507 2.8028
1.4014 30.0 1110 1.2751 0.8821 0.8845 0.8827 6.7237 16 2 10.6466 2.8028
1.3946 31.0 1147 1.2732 0.8826 0.8849 0.8831 6.7167 16 2 10.6426 2.8028
1.3915 32.0 1184 1.2712 0.8823 0.8845 0.8828 6.7057 16 2 10.6336 2.7027
1.3904 33.0 1221 1.2695 0.8824 0.8847 0.883 6.7047 16 2 10.6376 2.7027
1.3843 34.0 1258 1.2684 0.8828 0.885 0.8833 6.7097 16 2 10.6406 2.6026
1.3875 35.0 1295 1.2672 0.8827 0.8852 0.8834 6.7217 16 2 10.6607 2.6026
1.3794 36.0 1332 1.2661 0.8828 0.8851 0.8834 6.7087 16 2 10.6426 2.6026
1.3906 37.0 1369 1.2654 0.8828 0.8853 0.8835 6.7177 16 2 10.6567 2.6026
1.3841 38.0 1406 1.2648 0.8826 0.8851 0.8833 6.7107 16 2 10.6476 2.6026
1.3761 39.0 1443 1.2645 0.8825 0.885 0.8832 6.7137 16 2 10.6537 2.6026
1.3797 40.0 1480 1.2644 0.8826 0.8851 0.8832 6.7137 16 2 10.6547 2.6026

Framework versions

  • Transformers 4.33.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3