---
license: mit
tags:
- generated_from_trainer
metrics:
- bleu
- rouge
model-index:
- name: mbart-large-50-English_French_Translation_v2
  results: []
language:
- en
- fr
---

# mbart-large-50-English_French_Translation_v2

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: 0.3902
- Bleu: 35.1914
- Rouge: {'rouge1': 0.641952430267112, 'rouge2': 0.4572909036472911, 'rougeL': 0.607001331434416, 'rougeLsum': 0.6068905123656807}
- Meteor: {'meteor': 0.5916610499445853}

## Model description

This model translates French input text samples to English.

For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Machine%20Translation/NLP%20Translation%20Project-EN:FR.ipynb

## Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology.

## Training and evaluation data

Dataset Source: 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                         |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:----------------------------------------------------------------------------------------------------------------------------:|:------------------------------:|
| 1.1677        | 1.0   | 750  | 0.3902          | 35.1914 | {'rouge1': 0.6419485887304972, 'rouge2': 0.45727961744986984, 'rougeL': 0.6069956611472951, 'rougeLsum': 0.6068859187671477} | {'meteor': 0.5916768663368279} |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.12.1
- Datasets 2.9.0
- Tokenizers 0.12.1