transformers pytorch mbart text2text-generation translation generated_from_trainer base_model:facebook/mbart-large-50 base_model:finetune:facebook/mbart-large-50 license:mit autotrain_compatible endpoints_compatible region:us
---
base_model: facebook/mbart-large-50
license: mit
metrics:
- bleu
- rouge
tags:
- translation
- generated_from_trainer
model-index:
- name: mbart-large-50-en-es-translation-lr-1e-05-weight-decay-0.001
  results: []
---

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# mbart-large-50-en-es-translation-lr-1e-05-weight-decay-0.001

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: 0.9549
- Bleu: 45.0307
- Rouge: {'rouge1': 0.7049318825090395, 'rouge2': 0.5238048751750992, 'rougeL': 0.684187379601513, 'rougeLsum': 0.6843574853855577}

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu    | Rouge                                                                                                                        |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:----------------------------------------------------------------------------------------------------------------------------:|
| 1.4627        | 1.0   | 4500  | 1.0255          | 42.1880 | {'rouge1': 0.6725633216905762, 'rouge2': 0.48605402524493657, 'rougeL': 0.6498853764470456, 'rougeLsum': 0.6501981166312041} |
| 0.8878        | 2.0   | 9000  | 0.9572          | 44.1734 | {'rouge1': 0.6912686406245903, 'rouge2': 0.5093695171345348, 'rougeL': 0.6701896043455414, 'rougeLsum': 0.6703473419504804}  |
| 0.7125        | 3.0   | 13500 | 0.9414          | 44.8709 | {'rouge1': 0.7051197958532004, 'rouge2': 0.5210482863677958, 'rougeL': 0.6843075431636916, 'rougeLsum': 0.6846265298079588}  |
| 0.6092        | 4.0   | 18000 | 0.9549          | 45.0821 | {'rouge1': 0.7047932899349161, 'rouge2': 0.523739339466653, 'rougeL': 0.6840127607742443, 'rougeLsum': 0.684202100852132}    |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4.dev0
- Tokenizers 0.13.3
