EN_mt5-base_15_spider

This model is a fine-tuned version of google/mt5-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3557
  • Rouge2 Precision: 0.6104
  • Rouge2 Recall: 0.4164
  • Rouge2 Fmeasure: 0.4669

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: 5e-05
  • train_batch_size: 12
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Rouge2 Precision Rouge2 Recall Rouge2 Fmeasure
9.1945 1.0 722 1.9988 0.2524 0.1722 0.1809
2.7281 2.0 1444 0.3721 0.4727 0.3003 0.3376
0.2067 3.0 2166 0.3160 0.5435 0.3541 0.4033
0.1692 4.0 2888 0.3153 0.5628 0.3863 0.4314
0.1252 5.0 3610 0.3225 0.5764 0.3907 0.4381
0.1117 6.0 4332 0.3165 0.5707 0.3891 0.435
0.0973 7.0 5054 0.3269 0.5693 0.3868 0.4335
0.0897 8.0 5776 0.3365 0.585 0.4009 0.4478
0.082 9.0 6498 0.3407 0.6035 0.4129 0.4619
0.0721 10.0 7220 0.3453 0.5963 0.4089 0.4568
0.0703 11.0 7942 0.3434 0.6032 0.4137 0.4629
0.0638 12.0 8664 0.3505 0.6077 0.4178 0.4667
0.0615 13.0 9386 0.3509 0.611 0.4169 0.467
0.0599 14.0 10108 0.3554 0.608 0.4153 0.4651
0.058 15.0 10830 0.3557 0.6104 0.4164 0.4669

Framework versions

  • Transformers 4.26.1
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.7.dev0
  • Tokenizers 0.13.3
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