---
license: cc-by-nc-4.0
base_model: facebook/nllb-200-distilled-600M
tags:
- generated_from_trainer
datasets:
- nusatranslation_mt
metrics:
- sacrebleu
model-index:
- name: bbc-to-ind-nmt-v6
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: nusatranslation_mt
      type: nusatranslation_mt
      config: nusatranslation_mt_btk_ind_source
      split: test
      args: nusatranslation_mt_btk_ind_source
    metrics:
    - name: Sacrebleu
      type: sacrebleu
      value: 38.2052
---

<!-- 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. -->

# bbc-to-ind-nmt-v6

This model is a fine-tuned version of [facebook/nllb-200-distilled-600M](https://huggingface.co/facebook/nllb-200-distilled-600M) on the nusatranslation_mt dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1940
- Sacrebleu: 38.2052
- Gen Len: 37.467

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Sacrebleu | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 4.1507        | 1.0   | 825  | 1.3826          | 31.3365   | 37.6035 |
| 1.2319        | 2.0   | 1650 | 1.1646          | 36.0321   | 37.553  |
| 0.9893        | 3.0   | 2475 | 1.1238          | 37.2804   | 37.284  |
| 0.8593        | 4.0   | 3300 | 1.1213          | 38.1118   | 37.409  |
| 0.7624        | 5.0   | 4125 | 1.1353          | 38.2863   | 37.234  |
| 0.6872        | 6.0   | 4950 | 1.1404          | 38.3932   | 37.1405 |
| 0.6253        | 7.0   | 5775 | 1.1566          | 38.1803   | 37.191  |
| 0.5781        | 8.0   | 6600 | 1.1723          | 38.3633   | 37.351  |
| 0.5441        | 9.0   | 7425 | 1.1836          | 38.25     | 37.485  |
| 0.5214        | 10.0  | 8250 | 1.1940          | 38.2052   | 37.467  |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1