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t5-small-machine-articles-tag-generation

Summarization
Transformers
PyTorch
TensorBoard
English
t5
text2text-generation
Generated from Trainer
machine_learning
article_tag
tag_generation
ml_article_tag
blog_tag_generation
tagging
text-generation-inference
Inference Endpoints
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t5-small-machine-articles-tag-generation / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: t5-small-machine-articles-tag-generation
    results: []

t5-small-machine-articles-tag-generation

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

  • Loss: 1.9833
  • Rouge1: 35.3543
  • Rouge2: 18.1226
  • Rougel: 31.3958
  • Rougelsum: 31.414
  • Gen Len: 17.6596

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
3.7917 1.0 47 3.0002 19.9138 6.9215 17.6969 17.7888 18.9787
3.0113 2.0 94 2.5823 22.9993 9.0341 20.8118 20.7657 18.7021
2.7086 3.0 141 2.3643 26.7716 12.2207 24.1983 24.2611 18.3298
2.5192 4.0 188 2.2361 28.5866 13.6305 26.1201 26.1367 17.9894
2.4089 5.0 235 2.1661 30.1919 13.8779 27.1523 27.1256 18.0638
2.3293 6.0 282 2.1185 31.1222 15.6736 27.3953 27.4457 17.8404
2.2635 7.0 329 2.0875 32.3166 16.3032 28.7062 28.732 17.9149
2.2349 8.0 376 2.0653 31.8387 15.616 28.3254 28.4288 17.7979
2.1945 9.0 423 2.0473 32.388 16.4027 28.5642 28.6096 17.6809
2.1658 10.0 470 2.0352 33.9489 16.999 29.8446 29.8251 17.5426
2.1414 11.0 517 2.0252 34.0804 17.6999 30.1921 30.2739 17.5106
2.1103 12.0 564 2.0155 34.3488 17.8273 30.2613 30.3358 17.5957
2.1052 13.0 611 2.0053 35.1038 18.3494 30.6999 30.7655 17.6064
2.0795 14.0 658 2.0004 35.366 18.8791 31.4931 31.5691 17.7872
2.0612 15.0 705 1.9951 36.1778 18.7911 31.5974 31.6309 17.6064
2.0792 16.0 752 1.9886 35.0387 18.2363 31.5279 31.5694 17.6702
2.0695 17.0 799 1.9868 36.1432 18.4902 31.8314 31.7955 17.617
2.0593 18.0 846 1.9844 35.7847 18.3497 31.745 31.7007 17.6809
2.0395 19.0 893 1.9842 36.0629 18.9649 32.098 32.0453 17.5745
2.0623 20.0 940 1.9833 35.3543 18.1226 31.3958 31.414 17.6596

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2