---
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-v5
  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: 38.4814
---

<!-- 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-v5

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: 1.2310
- Sacrebleu: 38.4814
- Gen Len: 37.8455

## 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: 4
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:-------:|
| 3.4154        | 1.0   | 1650  | 1.2829          | 33.2857   | 37.9245 |
| 1.1633        | 2.0   | 3300  | 1.1418          | 36.6342   | 37.407  |
| 0.9377        | 3.0   | 4950  | 1.1148          | 38.0023   | 37.17   |
| 0.795         | 4.0   | 6600  | 1.1197          | 38.2402   | 37.3695 |
| 0.6827        | 5.0   | 8250  | 1.1465          | 38.3719   | 37.315  |
| 0.5937        | 6.0   | 9900  | 1.1642          | 38.3424   | 37.547  |
| 0.5216        | 7.0   | 11550 | 1.1917          | 38.56     | 37.8515 |
| 0.466         | 8.0   | 13200 | 1.2079          | 38.6061   | 37.6135 |
| 0.425         | 9.0   | 14850 | 1.2228          | 38.4918   | 37.928  |
| 0.3995        | 10.0  | 16500 | 1.2310          | 38.4814   | 37.8455 |


### Framework versions

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