musralina/helsinki-opus-de-en-fine-tuned-wmt16-finetuned-src-to-trg

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helsinki-opus-de-en-fine-tuned-wmt16-finetuned-src-to-trg

This model is a fine-tuned version of mariav/helsinki-opus-de-en-fine-tuned-wmt16 on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 0.8597
• —Rouge1: 64.539
• —Rouge2: 32.7634
• —Rougel: 61.3523
• —Rougelsum: 61.3758
• —Gen Len: 23.9561
• —Bleu-1: 64.1391
• —Bleu-2: 45.1093
• —Bleu-3: 32.4697
• —Bleu-4: 24.2684
• —Meteor: 0.5436

Model description

This model is a fine-tuned version of mariav/helsinki-opus-de-en-fine-tuned-wmt16 on Phoenix Weather dataset (PHOENIX-2014-T).

Intended uses & limitations

The purpose is Neural Machine Translation from German text into German Sign Glosses, which could be used for avatar generation within the Sign Language Production task.

Training and evaluation data

Phoenix Weather dataset (PHOENIX-2014-T)

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• —learning_rate: 5e-05
• —trainbatchsize: 5
• —evalbatchsize: 5
• —seed: 7575
• —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• —lrschedulertype: linear
• —num_epochs: 5

Training results

Framework versions

• —Transformers 4.30.1
• —Pytorch 2.0.1+cu118
• —Datasets 2.12.0
• —Tokenizers 0.13.3