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text_shortening_model_v79

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_v79
    results: []

text_shortening_model_v79

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

  • Loss: 1.0551
  • Bert precision: 0.8947
  • Bert recall: 0.8962
  • Bert f1-score: 0.895
  • Average word count: 6.7804
  • Max word count: 16
  • Min word count: 1
  • Average token count: 10.8466
  • % shortened texts with length > 12: 1.5951

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: 7e-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
2.0194 1.0 30 1.4487 0.8778 0.8746 0.8755 6.7755 16 1 10.7288 2.3313
1.58 2.0 60 1.3193 0.8835 0.8837 0.883 6.9301 16 2 10.7791 2.3313
1.4385 3.0 90 1.2492 0.8833 0.8855 0.8839 7.0368 16 2 10.9816 2.6994
1.3616 4.0 120 1.2111 0.8877 0.8873 0.887 6.8466 16 2 10.7509 1.8405
1.2976 5.0 150 1.1685 0.8869 0.8878 0.8868 6.8564 17 2 10.8172 1.8405
1.2495 6.0 180 1.1559 0.8885 0.8895 0.8885 6.8577 16 2 10.8564 2.0859
1.201 7.0 210 1.1353 0.8889 0.891 0.8894 6.9521 16 2 11.0012 2.3313
1.1717 8.0 240 1.1164 0.8892 0.89 0.8891 6.8601 16 1 10.8933 2.0859
1.1352 9.0 270 1.1110 0.8902 0.8891 0.8891 6.708 16 1 10.7436 1.1043
1.0984 10.0 300 1.1037 0.8901 0.8909 0.8901 6.8233 17 1 10.8503 1.9632
1.0745 11.0 330 1.0937 0.8894 0.892 0.8902 6.9362 17 2 10.9742 2.3313
1.0509 12.0 360 1.0907 0.8911 0.8916 0.8908 6.8233 17 1 10.8564 1.9632
1.0269 13.0 390 1.0805 0.8906 0.8934 0.8915 6.9448 17 1 11.0135 2.2086
1.0126 14.0 420 1.0784 0.8912 0.8935 0.8919 6.9264 17 2 10.973 2.3313
0.9959 15.0 450 1.0725 0.8929 0.8944 0.8932 6.8294 17 1 10.8957 2.2086
0.9717 16.0 480 1.0715 0.8916 0.8941 0.8924 6.919 17 1 10.9963 2.0859
0.9552 17.0 510 1.0727 0.8935 0.8949 0.8937 6.8282 17 1 10.9055 1.9632
0.9461 18.0 540 1.0665 0.8947 0.8955 0.8947 6.8061 17 1 10.8613 1.5951
0.926 19.0 570 1.0664 0.8948 0.896 0.895 6.7853 16 1 10.8515 1.3497
0.9192 20.0 600 1.0636 0.8948 0.8953 0.8946 6.7718 16 1 10.8209 1.4724
0.9101 21.0 630 1.0581 0.8954 0.897 0.8957 6.8221 16 1 10.8724 1.5951
0.899 22.0 660 1.0599 0.8954 0.8974 0.8959 6.8405 16 1 10.8982 1.5951
0.8843 23.0 690 1.0586 0.8943 0.8962 0.8948 6.8393 17 2 10.9055 1.9632
0.8779 24.0 720 1.0572 0.8932 0.8961 0.8942 6.8736 17 2 10.9656 2.0859
0.8725 25.0 750 1.0573 0.8939 0.8963 0.8947 6.8098 16 2 10.9104 1.7178
0.8567 26.0 780 1.0591 0.8951 0.8968 0.8955 6.7926 17 1 10.8945 1.5951
0.8549 27.0 810 1.0577 0.8945 0.8962 0.8948 6.8135 17 1 10.9018 1.8405
0.8467 28.0 840 1.0570 0.8948 0.8961 0.895 6.7669 16 1 10.8405 1.4724
0.833 29.0 870 1.0577 0.895 0.896 0.895 6.7546 16 1 10.8294 1.3497
0.8284 30.0 900 1.0548 0.8942 0.8957 0.8945 6.7816 16 1 10.8589 1.4724
0.8296 31.0 930 1.0565 0.8947 0.8967 0.8952 6.8037 16 1 10.8982 1.4724
0.8156 32.0 960 1.0550 0.8945 0.8961 0.8948 6.7914 16 2 10.8601 1.5951
0.8095 33.0 990 1.0567 0.8944 0.8962 0.8948 6.8049 16 2 10.881 1.7178
0.8066 34.0 1020 1.0564 0.8948 0.8961 0.895 6.7853 16 1 10.8405 1.8405
0.817 35.0 1050 1.0567 0.8951 0.8961 0.8952 6.7509 16 1 10.8172 1.5951
0.8155 36.0 1080 1.0563 0.8949 0.8964 0.8952 6.7669 16 1 10.838 1.5951
0.808 37.0 1110 1.0560 0.8946 0.8965 0.8951 6.7926 16 1 10.8675 1.7178
0.8049 38.0 1140 1.0554 0.895 0.8965 0.8953 6.7742 16 1 10.8393 1.4724
0.8002 39.0 1170 1.0550 0.8946 0.8962 0.8949 6.7877 16 1 10.8491 1.5951
0.7912 40.0 1200 1.0551 0.8947 0.8962 0.895 6.7804 16 1 10.8466 1.5951

Framework versions

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