opus-mt-en-ar-evaluated-en-to-ar-4000instances-un_multi-leaningRate2e-05-batchSize8-11-action-1

This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ar on the un_multi dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1850
  • Bleu: 51.7715
  • Meteor: 0.5164
  • Gen Len: 25.5612

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: 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: 11

Training results

Training Loss Epoch Step Validation Loss Bleu Meteor Gen Len
0.6999 0.25 100 0.1959 50.1492 0.508 25.2788
0.1994 0.5 200 0.1931 51.003 0.513 25.4038
0.1863 0.75 300 0.1864 51.3268 0.5145 25.1675
0.1826 1.0 400 0.1841 51.2507 0.513 25.2388
0.1494 1.25 500 0.1840 51.4291 0.5159 25.4225
0.1483 1.5 600 0.1839 51.2645 0.5126 25.395
0.1547 1.75 700 0.1837 51.7589 0.5157 25.48
0.1487 2.0 800 0.1845 51.896 0.5177 25.3988
0.1235 2.25 900 0.1852 52.0583 0.5177 25.5212
0.1164 2.5 1000 0.1850 51.7715 0.5164 25.5612

Framework versions

  • Transformers 4.18.0
  • Pytorch 1.11.0
  • Datasets 2.1.0
  • Tokenizers 0.12.1
Downloads last month
12
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train meghazisofiane/opus-mt-en-ar-evaluated-en-to-ar-4000instances-un_multi-leaningRate2e-05-batchSize8-11-action-1

Evaluation results