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ind-to-bbc-nmt-v2

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ind-to-bbc-nmt-v2
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---
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: ind-to-bbc-nmt-v2
  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: 31.5851
---

<!-- 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. -->

# ind-to-bbc-nmt-v2

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: 1.1713
- Sacrebleu: 31.5851
- Gen Len: 45.311

## 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Sacrebleu | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 3.6041        | 1.0   | 825  | 1.4552          | 28.698    | 45.0965 |
| 1.3318        | 2.0   | 1650 | 1.2516          | 30.4316   | 45.683  |
| 1.103         | 3.0   | 2475 | 1.1934          | 30.9199   | 45.474  |
| 0.9875        | 4.0   | 3300 | 1.1762          | 31.635    | 45.254  |
| 0.9204        | 5.0   | 4125 | 1.1713          | 31.5851   | 45.311  |


### Framework versions

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