mT5-fine-tune / README.md
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metadata
license: apache-2.0
base_model: google/mt5-small
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: mT5-fine-tune
    results: []

mT5-fine-tune

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: 2.5256
  • Rouge1: 0.0822
  • Rouge2: 0.0244
  • Rougel: 0.0813
  • Rougelsum: 0.0814
  • Gen Len: 18.9803
  • Chrf Score: 20.301
  • Chrf Char Order: 6
  • Chrf Word Order: 0
  • Chrf Beta: 2

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: 0.0001
  • 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: 7

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len Chrf Score Chrf Char Order Chrf Word Order Chrf Beta
3.5479 1.0 1951 2.7435 0.0672 0.021 0.0666 0.0667 18.9323 19.2495 6 0 2
3.1717 2.0 3902 2.6452 0.0746 0.0207 0.0738 0.0737 18.9814 20.1079 6 0 2
3.0151 3.0 5853 2.6014 0.0834 0.0243 0.0826 0.0823 18.9891 20.2875 6 0 2
2.95 4.0 7804 2.5647 0.0765 0.0218 0.0757 0.0757 18.981 20.2327 6 0 2
2.8592 5.0 9755 2.5480 0.0822 0.0242 0.0814 0.0813 18.9819 20.3982 6 0 2
2.8214 6.0 11706 2.5317 0.0841 0.0255 0.0831 0.083 18.9764 20.3935 6 0 2
2.789 7.0 13657 2.5256 0.0822 0.0244 0.0813 0.0814 18.9803 20.301 6 0 2

Framework versions

  • Transformers 4.33.0
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.13.3