--- license: mit tags: - generated_from_trainer metrics: - bleu - rouge model-index: - name: mbart-large-50-English_German_Translation results: [] language: - en - de --- # 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 This model is intended to demonstrate my ability to solve a complex problem using technology. ## 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