Helsinki_lg_inf_en / README.md
MubarakB's picture
Model save
12841c6 verified
metadata
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-lg-en
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 Helsinki-NLP/opus-mt-lg-en on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1764
  • Bleu: 22.8149
  • Gen Len: 17.7776

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

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
No log 1.0 153 0.5662 0.6031 20.9541
No log 2.0 306 0.5118 0.8533 20.1433
No log 3.0 459 0.4754 1.1179 19.9124
0.6777 4.0 612 0.4452 1.4213 20.2326
0.6777 5.0 765 0.4181 1.7245 19.2424
0.6777 6.0 918 0.3940 2.0655 19.5872
0.463 7.0 1071 0.3722 2.6043 19.2969
0.463 8.0 1224 0.3512 3.4014 18.864
0.463 9.0 1377 0.3323 4.0558 19.0541
0.3973 10.0 1530 0.3150 4.9264 18.878
0.3973 11.0 1683 0.2989 6.1751 18.1102
0.3973 12.0 1836 0.2845 6.909 18.405
0.3973 13.0 1989 0.2708 8.2081 18.1388
0.3476 14.0 2142 0.2589 9.0267 18.1527
0.3476 15.0 2295 0.2477 9.8007 18.1826
0.3476 16.0 2448 0.2374 11.2825 17.9705
0.309 17.0 2601 0.2282 12.38 17.9427
0.309 18.0 2754 0.2200 13.1971 18.2629
0.309 19.0 2907 0.2127 14.6993 18.0356
0.278 20.0 3060 0.2058 15.8696 17.7944
0.278 21.0 3213 0.2001 17.2214 17.656
0.278 22.0 3366 0.1951 18.3989 17.6769
0.2597 23.0 3519 0.1906 19.6026 17.7543
0.2597 24.0 3672 0.1869 20.6405 17.817
0.2597 25.0 3825 0.1835 20.7913 17.7273
0.2597 26.0 3978 0.1809 21.5904 17.7518
0.2452 27.0 4131 0.1789 21.9249 17.69
0.2452 28.0 4284 0.1775 22.3964 17.6953
0.2452 29.0 4437 0.1767 22.6803 17.7547
0.2379 30.0 4590 0.1764 22.8149 17.7776

Framework versions

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