---
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: mbart-large-50-many-to-many-mmt-finetuned-pt-to-en
  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-many-to-many-mmt-finetuned-pt-to-en

This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0116
- Bleu: 3.9795
- Gen Len: 46.1292

## 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: 0.0002
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| 2.981         | 1.0   | 989  | 2.6925          | 2.0264 | 53.1604 |
| 2.1381        | 2.0   | 1978 | 2.6576          | 2.6268 | 47.2153 |
| 1.6501        | 3.0   | 2967 | 2.7743          | 2.9549 | 45.5091 |
| 1.2518        | 4.0   | 3956 | 2.9517          | 3.1862 | 49.9585 |
| 0.9188        | 5.0   | 4945 | 3.1741          | 3.3758 | 46.0227 |
| 0.6615        | 6.0   | 5934 | 3.3934          | 3.4223 | 42.5911 |
| 0.4714        | 7.0   | 6923 | 3.6090          | 3.8522 | 48.1263 |
| 0.3283        | 8.0   | 7912 | 3.8027          | 3.7817 | 46.4619 |
| 0.2291        | 9.0   | 8901 | 3.9314          | 3.9939 | 47.2651 |
| 0.163         | 10.0  | 9890 | 4.0116          | 3.9795 | 46.1292 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1