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---
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
- translation
- mBART
metrics:
- bleu
model-index:
- name: mbart-en-np-seqtoseq-sentence-translation
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. -->
[<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
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