---
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: 3.8212
- Bleu: 5.1667
- Gen Len: 53.5411

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 1.0   | 154  | 2.9955          | 1.7894 | 44.0952 |
| No log        | 2.0   | 308  | 2.8970          | 2.326  | 46.8317 |
| No log        | 3.0   | 462  | 2.9511          | 3.0767 | 55.8505 |
| 2.5276        | 4.0   | 616  | 3.0830          | 3.3555 | 48.737  |
| 2.5276        | 5.0   | 770  | 3.2703          | 3.5714 | 47.0602 |
| 2.5276        | 6.0   | 924  | 3.4241          | 4.3465 | 52.7744 |
| 1.0364        | 7.0   | 1078 | 3.5665          | 4.4909 | 52.705  |
| 1.0364        | 8.0   | 1232 | 3.6942          | 4.6399 | 50.4717 |
| 1.0364        | 9.0   | 1386 | 3.7852          | 5.2082 | 54.6205 |
| 0.3319        | 10.0  | 1540 | 3.8212          | 5.1667 | 53.5411 |


### Framework versions

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