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fine-tuned-flan-t5-20-epochs

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

  • Loss: 0.7842
  • Rouge1: 0.2614
  • Rouge2: 0.0824
  • Rougel: 0.226
  • Rougelsum: 0.2273
  • Gen Len: 14.54

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 301 1.8551 0.1314 0.0425 0.1139 0.1139 11.4
2.7128 2.0 602 0.9826 0.1868 0.065 0.1564 0.1571 15.06
2.7128 3.0 903 0.8569 0.2079 0.0718 0.1716 0.1722 15.05
1.1113 4.0 1204 0.8300 0.2141 0.0705 0.181 0.181 14.59
0.9116 5.0 1505 0.8204 0.2254 0.0837 0.1943 0.1945 14.92
0.9116 6.0 1806 0.8116 0.243 0.0807 0.2074 0.2072 15.03
0.8732 7.0 2107 0.8082 0.2376 0.0752 0.2015 0.2016 14.83
0.8732 8.0 2408 0.8007 0.2345 0.0735 0.2015 0.2021 14.41
0.8336 9.0 2709 0.7968 0.2456 0.0757 0.2081 0.2081 14.4
0.8151 10.0 3010 0.7942 0.2544 0.0752 0.2134 0.2146 14.58
0.8151 11.0 3311 0.7924 0.2497 0.0783 0.2118 0.2124 14.5
0.8187 12.0 3612 0.7907 0.2552 0.0769 0.2189 0.2191 14.43
0.8187 13.0 3913 0.7891 0.258 0.077 0.2197 0.2199 14.37
0.8028 14.0 4214 0.7867 0.2511 0.0801 0.2146 0.2147 14.71
0.7793 15.0 4515 0.7852 0.2551 0.0777 0.2175 0.2177 14.67
0.7793 16.0 4816 0.7858 0.2594 0.0774 0.2219 0.2219 14.47
0.7872 17.0 5117 0.7850 0.2609 0.0803 0.2233 0.2244 14.56
0.7872 18.0 5418 0.7843 0.2599 0.0811 0.2242 0.2256 14.55
0.7756 19.0 5719 0.7844 0.261 0.0824 0.2256 0.2271 14.55
0.7752 20.0 6020 0.7842 0.2614 0.0824 0.226 0.2273 14.54

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.0
  • Tokenizers 0.15.0
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