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metadata
license: mit
base_model: MT-Informal-Languages/Helsinki-NLP-opus-mt-ug
tags:
  - generated_from_trainer
metrics:
  - bleu
model-index:
  - name: Helsinki_lg_inf_en
    results: []

Visualize in Weights & Biases

Helsinki_lg_inf_en

This model is a fine-tuned version of MT-Informal-Languages/Helsinki-NLP-opus-mt-ug on the Luganda Formal Data dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0505
  • Bleu: 57.3885
  • Gen Len: 17.3595

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: 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
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
No log 1.0 153 0.4708 0.9369 19.2244
No log 2.0 306 0.4227 1.1005 20.8706
No log 3.0 459 0.3854 1.4207 19.8702
1.1563 4.0 612 0.3519 1.7877 19.5442
1.1563 5.0 765 0.3216 2.4366 18.7977
1.1563 6.0 918 0.2929 3.0827 18.6413
0.375 7.0 1071 0.2677 3.9367 19.2035
0.375 8.0 1224 0.2427 5.605 18.5111
0.375 9.0 1377 0.2192 7.0359 18.6204
0.2959 10.0 1530 0.1980 9.5819 17.8284
0.2959 11.0 1683 0.1794 11.9364 17.7428
0.2959 12.0 1836 0.1621 13.9353 18.0643
0.2959 13.0 1989 0.1464 16.9189 17.8714
0.2334 14.0 2142 0.1315 19.2848 18.0201
0.2334 15.0 2295 0.1189 22.6041 17.973
0.2334 16.0 2448 0.1085 25.554 18.0324
0.1848 17.0 2601 0.0992 28.6049 17.4644
0.1848 18.0 2754 0.0905 31.9759 17.8104
0.1848 19.0 2907 0.0828 35.5846 17.8108
0.1507 20.0 3060 0.0764 39.748 17.656
0.1507 21.0 3213 0.0712 42.3511 17.5602
0.1507 22.0 3366 0.0665 45.7843 17.5238
0.1285 23.0 3519 0.0628 48.4047 17.5233
0.1285 24.0 3672 0.0592 50.5559 17.3403
0.1285 25.0 3825 0.0564 52.0378 17.4443
0.1285 26.0 3978 0.0545 54.0726 17.579
0.1132 27.0 4131 0.0526 55.201 17.4017
0.1132 28.0 4284 0.0515 56.6048 17.4447
0.1132 29.0 4437 0.0508 57.2182 17.448
0.1047 30.0 4590 0.0505 57.3885 17.3595

Framework versions

  • Transformers 4.42.3
  • Pytorch 2.1.2
  • Datasets 2.20.0
  • Tokenizers 0.19.1