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metadata
license: cc-by-nc-sa-4.0
tags:
  - simplification
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: mt5-simplification-spanish-clara-med
    results: []

mt5-simplification-spanish-clara-med

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

  • Loss: 1.9829
  • Rouge1: 33.5827
  • Rouge2: 19.3568
  • Rougel: 30.9427
  • Rougelsum: 30.922

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: 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: 30

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
No log 1.0 190 2.6879 31.8425 17.5967 29.0762 29.1474
No log 2.0 380 2.4770 32.6054 18.6606 30.0148 30.0565
3.3044 3.0 570 2.3618 32.873 18.9033 30.2114 30.2842
3.3044 4.0 760 2.2842 33.0173 18.9165 30.2803 30.3708
2.7475 5.0 950 2.2176 32.769 18.6209 30.1211 30.1858
2.7475 6.0 1140 2.1974 32.8461 18.7023 30.1932 30.2432
2.7475 7.0 1330 2.1625 32.8013 18.7017 30.1099 30.1752
2.5234 8.0 1520 2.1315 33.0317 18.8095 30.3504 30.394
2.5234 9.0 1710 2.1086 33.2546 18.9599 30.5465 30.5782
2.3775 10.0 1900 2.0830 33.2349 18.8346 30.4815 30.524
2.3775 11.0 2090 2.0655 33.1573 18.9358 30.4626 30.4931
2.3775 12.0 2280 2.0599 33.2281 19.0066 30.5592 30.5896
2.2837 13.0 2470 2.0464 33.2839 19.1136 30.7237 30.7471
2.2837 14.0 2660 2.0343 33.4208 19.0347 30.6897 30.7073
2.2132 15.0 2850 2.0351 33.4278 19.0579 30.7056 30.7218
2.2132 16.0 3040 2.0276 33.541 19.1772 30.8324 30.8551
2.2132 17.0 3230 2.0122 33.455 19.1121 30.79 30.8033
2.1561 18.0 3420 2.0124 33.3712 19.1315 30.7892 30.8023
2.1561 19.0 3610 2.0098 33.5589 19.2569 30.86 30.8629
2.1136 20.0 3800 2.0018 33.4333 19.124 30.7894 30.8035
2.1136 21.0 3990 1.9954 33.5845 19.2881 30.9155 30.9167
2.1136 22.0 4180 1.9947 33.6133 19.3605 30.9736 30.9831
2.0851 23.0 4370 1.9924 33.6015 19.3226 30.9673 30.9695
2.0851 24.0 4560 1.9861 33.7693 19.3866 31.0921 31.0837
2.0569 25.0 4750 1.9851 33.7423 19.431 31.0085 31.0119
2.0569 26.0 4940 1.9865 33.6365 19.3494 30.9259 30.9263
2.0569 27.0 5130 1.9864 33.6976 19.3426 30.9851 30.9756
2.0421 28.0 5320 1.9843 33.6246 19.3228 30.9379 30.9345
2.0421 29.0 5510 1.9835 33.5947 19.3477 30.912 30.9164
2.0319 30.0 5700 1.9829 33.5827 19.3568 30.9427 30.922

Framework versions

  • Transformers 4.25.1
  • Pytorch 1.13.0
  • Datasets 2.8.0
  • Tokenizers 0.12.1