readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  - rouge
  model-index:
  - name: mbart-large-50-English_German_Translation
    results: []
  ---
  
  <!-- 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. -->
  
  # mbart-large-50-English_German_Translation
  
  This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/facebook/mbart-large-50) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2342
  - Bleu: 35.5931
  - Rouge: {'rouge1': 0.5803386608353808, 'rouge2': 0.3939141514072567, 'rougeL': 0.5438629663406402, 'rougeLsum': 0.544153348468965}
  - Meteor: {'meteor': 0.5500546034636025}
  
  ## Model description
  
  Here is the link to the script I created to train this model:
  
  https://github.com/DunnBC22/NLP_Projects/blob/main/Machine%20Translation/NLP%20Translation%20Project-EN:DE.ipynb
  
  ## Intended uses & limitations
  
  More information needed
  
  ## Training and evaluation data
  
  Here is a the link to the page where I found this dataset:
  
  https://www.kaggle.com/datasets/hgultekin/paralel-translation-corpus-in-22-languages
  
  ## Training procedure
  
  ### Training hyperparameters
  
  The following hyperparameters were used during training:
  - learning_rate: 2e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - 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    | Rouge                                                                                                                      | Meteor                         |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:--------------------------------------------------------------------------------------------------------------------------:|:------------------------------:|
  | 1.7738        | 1.0   | 900  | 1.2342          | 35.7436 | {'rouge1': 0.5805815969432273, 'rouge2': 0.3941222478624937, 'rougeL': 0.544162316313326, 'rougeLsum': 0.5444260344836553} | {'meteor': 0.5511605039667078} |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1
  - Datasets 2.5.2
  - Tokenizers 0.12.1
  