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

sourceHugging Faceapache-2.0updated 4y agoView on Hugging Face
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Model Card

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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
  • —trainbatchsize: 8
  • —evalbatchsize: 8
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: linear
  • —num_epochs: 11

Training results

Training LossEpochStepValidation LossBleuMeteorGen Len
0.69990.251000.195950.14920.50825.2788
0.19940.52000.193151.0030.51325.4038
0.18630.753000.186451.32680.514525.1675
0.18261.04000.184151.25070.51325.2388
0.14941.255000.184051.42910.515925.4225
0.14831.56000.183951.26450.512625.395
0.15471.757000.183751.75890.515725.48
0.14872.08000.184551.8960.517725.3988
0.12352.259000.185252.05830.517725.5212
0.11642.510000.185051.77150.516425.5612

Framework versions

  • —Transformers 4.18.0
  • —Pytorch 1.11.0
  • —Datasets 2.1.0
  • —Tokenizers 0.12.1