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---
license: apache-2.0
tags:
- translation
- generated_from_trainer
datasets:
- news_commentary
metrics:
- bleu
model-index:
- name: pt-opus-news
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: news_commentary
type: news_commentary
config: en-pt
split: train
args: en-pt
metrics:
- name: Bleu
type: bleu
value: 37.5501808262607
---
<!-- 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. -->
# pt-opus-news
This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-mul](https://huggingface.co/Helsinki-NLP/opus-mt-en-mul) on the news_commentary dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0975
- Bleu: 37.5502
## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- Transformers 4.22.0
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
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