---
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-v8
  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: 37.8271
---

<!-- 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-v8

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: 1.1397
- Sacrebleu: 37.8271
- Gen Len: 37.329

## 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: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 5.9033        | 1.0   | 207  | 3.5144          | 25.8748   | 39.2155 |
| 2.4501        | 2.0   | 414  | 1.4664          | 31.5752   | 38.098  |
| 1.2896        | 3.0   | 621  | 1.1951          | 35.3334   | 37.154  |
| 1.0669        | 4.0   | 828  | 1.1503          | 36.5808   | 36.977  |
| 0.969         | 5.0   | 1035 | 1.1384          | 37.1725   | 37.2425 |
| 0.9036        | 6.0   | 1242 | 1.1310          | 37.6427   | 37.141  |
| 0.8572        | 7.0   | 1449 | 1.1333          | 37.6234   | 37.264  |
| 0.821         | 8.0   | 1656 | 1.1333          | 37.7638   | 37.222  |
| 0.7971        | 9.0   | 1863 | 1.1385          | 37.8469   | 37.378  |
| 0.7811        | 10.0  | 2070 | 1.1397          | 37.8271   | 37.329  |


### Framework versions

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