README.md

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