readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - wmt16
  metrics:
  - bleu
  model-index:
  - name: opus-mt-tr-en-finetuned-en-to-tr
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: wmt16
        type: wmt16
        config: tr-en
        split: train
        args: tr-en
      metrics:
      - name: Bleu
        type: bleu
        value: 6.471
  ---
  
  <!-- 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-tr-en-finetuned-en-to-tr
  
  This model is a fine-tuned version of [Helsinki-NLP/opus-mt-tr-en](https://huggingface.co/Helsinki-NLP/opus-mt-tr-en) on the wmt16 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.9429
  - Bleu: 6.471
  - Gen Len: 56.1688
  
  ## 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: 3
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Bleu   | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
  | 1.5266        | 1.0   | 12860 | 2.2526          | 4.5834 | 55.6563 |
  | 1.2588        | 2.0   | 25720 | 2.0113          | 5.9203 | 56.3506 |
  | 1.1878        | 3.0   | 38580 | 1.9429          | 6.471  | 56.1688 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  