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metadata
tags:
  - generated_from_trainer
datasets:
  - wmt16
metrics:
  - bleu
model_index:
  - name: opus-mt-en-ro-finetuned-en-to-ro
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: wmt16
          type: wmt16
          args: ro-en
        metric:
          name: Bleu
          type: bleu
          value: 28.1641

opus-mt-en-ro-finetuned-en-to-ro

This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ro on the wmt16 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2886
  • Bleu: 28.1641
  • Gen Len: 34.1071

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: 1

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
0.7436 1.0 38145 1.2886 28.1641 34.1071

Framework versions

  • Transformers 4.9.1
  • Pytorch 1.9.0+cu102
  • Datasets 1.10.2
  • Tokenizers 0.10.3