readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - wmt16
  metrics:
  - bleu
  model-index:
  - name: opus-mt-de-en-finetuned-de-to-en-second
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: wmt16
        type: wmt16
        args: de-en
      metrics:
      - name: Bleu
        type: bleu
        value: 37.9762
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # opus-mt-de-en-finetuned-de-to-en-second
  
  This model is a fine-tuned version of [Helsinki-NLP/opus-mt-de-en](https://huggingface.co/Helsinki-NLP/opus-mt-de-en) on the wmt16 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2282
  - Bleu: 37.9762
  - Gen Len: 25.3696
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
  | No log        | 1.0   | 157  | 1.1837          | 38.8278 | 25.22   |
  | No log        | 2.0   | 314  | 1.2057          | 38.3047 | 25.2908 |
  | No log        | 3.0   | 471  | 1.2167          | 38.231  | 25.316  |
  | 1.4808        | 4.0   | 628  | 1.2256          | 37.9871 | 25.3556 |
  | 1.4808        | 5.0   | 785  | 1.2282          | 37.9762 | 25.3696 |
  
  
  ### Framework versions
  
  - Transformers 4.12.5
  - Pytorch 1.10.0+cu111
  - Datasets 1.16.1
  - Tokenizers 0.10.3
  