---
language:
- ro
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-en-ro
tags:
- generated_from_trainer
datasets:
- IoanRazvan/ro-romani
metrics:
- bleu
model-index:
- name: MarianMT Romani-Romanian NMT
  results:
  - task:
      name: Translation
      type: translation
    dataset:
      name: IoanRazvan/ro-romani
      type: IoanRazvan/ro-romani
      args: 'config: ro, split: train'
    metrics:
    - name: Bleu
      type: bleu
      value: 0.6077195716202178
---

<!-- 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. -->

# MarianMT Romani-Romanian NMT

This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ro](https://huggingface.co/Helsinki-NLP/opus-mt-en-ro) on the IoanRazvan/ro-romani dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3277
- Bleu: 0.6077

## 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: 1e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.5152        | 5.19  | 1000 | 0.4979          | 0.4753 |
| 0.4051        | 10.39 | 2000 | 0.3960          | 0.5528 |
| 0.351         | 15.58 | 3000 | 0.3577          | 0.5847 |
| 0.3222        | 20.78 | 4000 | 0.3394          | 0.5983 |
| 0.3108        | 25.97 | 5000 | 0.3305          | 0.6056 |
| 0.3005        | 31.17 | 6000 | 0.3277          | 0.6077 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2