ArabicTranslator / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - opus_infopankki
metrics:
  - bleu
model-index:
  - name: opus-mt-ar-en-finetuned-ar-to-en
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: opus_infopankki
          type: opus_infopankki
          args: ar-en
        metrics:
          - name: Bleu
            type: bleu
            value: 51.6508

opus-mt-ar-en-finetuned-ar-to-en

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

  • Loss: 0.7269
  • Bleu: 51.6508
  • Gen Len: 15.0812

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-06
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
1.4974 1.0 1587 1.3365 36.9061 15.3385
1.3768 2.0 3174 1.2139 39.5476 15.2079
1.2887 3.0 4761 1.1265 41.2771 15.2034
1.2076 4.0 6348 1.0556 42.6907 15.2687
1.1512 5.0 7935 0.9975 43.9498 15.2072
1.0797 6.0 9522 0.9491 45.224 15.2034
1.0499 7.0 11109 0.9101 46.1387 15.1651
1.0095 8.0 12696 0.8778 47.0586 15.1788
0.9833 9.0 14283 0.8501 47.8083 15.162
0.9601 10.0 15870 0.8267 48.5236 15.1784
0.9457 11.0 17457 0.8059 49.1717 15.095
0.9233 12.0 19044 0.7883 49.7742 15.1126
0.8964 13.0 20631 0.7736 50.2168 15.0917
0.8849 14.0 22218 0.7606 50.5583 15.0913
0.8751 15.0 23805 0.7504 50.8481 15.1108
0.858 16.0 25392 0.7417 51.1841 15.0989
0.8673 17.0 26979 0.7353 51.4271 15.0939
0.8548 18.0 28566 0.7306 51.535 15.0911
0.8483 19.0 30153 0.7279 51.6102 15.078
0.8614 20.0 31740 0.7269 51.6508 15.0812

Framework versions

  • Transformers 4.19.2
  • Pytorch 1.7.1+cu110
  • Datasets 2.2.2
  • Tokenizers 0.12.1