transformers tensorboard safetensors m2m_100 text2text-generation generated_from_trainer dataset:nusatranslation_mt base_model:facebook/nllb-200-distilled-600M base_model:finetune:facebook/nllb-200-distilled-600M license:cc-by-nc-4.0 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: facebook/nllb-200-distilled-600M
datasets:
- nusatranslation_mt
license: cc-by-nc-4.0
metrics:
- sacrebleu
tags:
- generated_from_trainer
model-index:
- name: ind-to-bbc-nmt-v8
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: nusatranslation_mt
      type: nusatranslation_mt
      config: nusatranslation_mt_btk_ind_source
      split: test
      args: nusatranslation_mt_btk_ind_source
    metrics:
    - type: sacrebleu
      value: 31.404
      name: Sacrebleu
---

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# ind-to-bbc-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: 1.1714
- Sacrebleu: 31.404
- Gen Len: 45.259

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 5.9718        | 1.0   | 207  | 3.5105          | 24.1454   | 44.5145 |
| 2.5392        | 2.0   | 414  | 1.6246          | 28.1486   | 45.45   |
| 1.46          | 3.0   | 621  | 1.3187          | 30.5425   | 45.375  |
| 1.2013        | 4.0   | 828  | 1.2437          | 31.2443   | 45.2075 |
| 1.0869        | 5.0   | 1035 | 1.2084          | 31.0749   | 45.3445 |
| 1.0083        | 6.0   | 1242 | 1.1851          | 31.167    | 45.35   |
| 0.9563        | 7.0   | 1449 | 1.1811          | 31.2377   | 45.344  |
| 0.9149        | 8.0   | 1656 | 1.1719          | 31.2539   | 45.343  |
| 0.8881        | 9.0   | 1863 | 1.1738          | 31.5399   | 45.145  |
| 0.872         | 10.0  | 2070 | 1.1714          | 31.404    | 45.259  |


### Framework versions

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