transformers safetensors mbart text2text-generation translation mBART base_model:facebook/mbart-large-50-many-to-many-mmt base_model:finetune:facebook/mbart-large-50-many-to-many-mmt autotrain_compatible endpoints_compatible region:us
---
base_model: facebook/mbart-large-50-many-to-many-mmt
library_name: transformers
metrics:
- bleu
tags:
- translation
- mBART
model-index:
- name: mbart-en-np-seqtoseq-sentence-translation
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/darvilab/Training%20Sentence%20Translation/runs/nul533k2)
# mbart-en-np-seqtoseq-sentence-translation

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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1896
- Bleu: 40.4595
- Gen Len: 10.288

## 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: 2e-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
| 1.0147        | 1.0   | 1250 | 0.9876          | 40.1501 | 9.885   |
| 0.6038        | 2.0   | 2500 | 1.0122          | 40.728  | 10.113  |
| 0.3557        | 3.0   | 3750 | 1.0809          | 35.9297 | 10.844  |
| 0.2071        | 4.0   | 5000 | 1.1502          | 40.4318 | 10.28   |
| 0.1241        | 5.0   | 6250 | 1.1896          | 40.4595 | 10.288  |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1