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-0.01
  results: []
---

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# mbart-large-50-en-es-translation-lr-1e-05-weight-decay-0.01

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: 0.9547
- Bleu: 45.0896
- Rouge: {'rouge1': 0.7050843983318068, 'rouge2': 0.5221826018405332, 'rougeL': 0.6843669248955093, 'rougeLsum': 0.6845499780252107}

## 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                                                                                                                       |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:---------------------------------------------------------------------------------------------------------------------------:|
| 1.4571        | 1.0   | 4500  | 1.0262          | 41.9188 | {'rouge1': 0.6701489298042851, 'rouge2': 0.4850120961190509, 'rougeL': 0.6479081216501843, 'rougeLsum': 0.6480345623292922} |
| 0.889         | 2.0   | 9000  | 0.9559          | 44.3378 | {'rouge1': 0.6920481616267358, 'rouge2': 0.5087283264258592, 'rougeL': 0.6709294966142768, 'rougeLsum': 0.6710449317682404} |
| 0.7134        | 3.0   | 13500 | 0.9416          | 44.9705 | {'rouge1': 0.7026762914671131, 'rouge2': 0.5192700210995049, 'rougeL': 0.6817974408692513, 'rougeLsum': 0.6819680202609157} |
| 0.6098        | 4.0   | 18000 | 0.9547          | 45.1741 | {'rouge1': 0.7051668954804624, 'rouge2': 0.5222186626492409, 'rougeL': 0.6844002112351866, 'rougeLsum': 0.6845851183829141} |


### Framework versions

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