akashmaggon / mt5-small-finetuned-amazon-en-es

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Model's Last Updated: August 24 2023
summarization

Introduction of mt5-small-finetuned-amazon-en-es

Model Details of mt5-small-finetuned-amazon-en-es

mt5-small-finetuned-amazon-en-es

This model is a fine-tuned version of google/mt5-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 3.0235
  • Rouge1: 16.8125
  • Rouge2: 9.0054
  • Rougel: 16.4607
  • Rougelsum: 16.3782
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: 5.6e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 8
Training results
Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
3.6964 1.0 1209 3.2660 16.5796 8.1879 16.038 15.9964
3.6612 2.0 2418 3.1208 18.3195 9.3145 17.6299 17.567
3.4414 3.0 3627 3.0604 16.2481 8.07 15.7698 15.7559
3.3168 4.0 4836 3.0624 15.8551 7.5199 15.6639 15.4861
3.2377 5.0 6045 3.0420 16.0485 7.7961 15.817 15.6537
3.1651 6.0 7254 3.0293 16.7136 8.6636 16.5564 16.4142
3.1424 7.0 8463 3.0249 17.0907 8.6811 16.7997 16.6651
3.1144 8.0 9672 3.0235 16.8125 9.0054 16.4607 16.3782
Framework versions
  • Transformers 4.32.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3

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