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Add evaluation results on wmt16
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - wmt16
metrics:
  - bleu
model-index:
  - name: translation
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: wmt16
          type: wmt16
          args: ro-en
        metrics:
          - name: Bleu
            type: bleu
            value: 28.5866
      - task:
          name: Translation
          type: translation
        dataset:
          type: wmt16
          name: wmt16
          config: ro-en
          split: test
        metrics:
          - name: BLEU
            type: bleu
            value: 3.3124
            verified: true

translation

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: 1.3170
  • Bleu: 28.5866
  • Gen Len: 33.9575

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
  • training_steps: 1000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
0.8302 0.03 1000 1.3170 28.5866 33.9575

Framework versions

  • Transformers 4.19.2
  • Pytorch 1.11.0+cu113
  • Datasets 2.2.2
  • Tokenizers 0.12.1