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: bbc-to-ind-nmt-v7
  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: 38.1839
      name: Sacrebleu
---

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# bbc-to-ind-nmt-v7

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: 1.1540
- Sacrebleu: 38.1839
- Gen Len: 37.279

## 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: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 5.0915        | 1.0   | 413  | 2.2849          | 27.9598   | 38.462  |
| 1.483         | 2.0   | 826  | 1.2052          | 35.2398   | 37.6305 |
| 1.0733        | 3.0   | 1239 | 1.1450          | 36.4283   | 37.133  |
| 0.9415        | 4.0   | 1652 | 1.1232          | 37.7264   | 37.198  |
| 0.8558        | 5.0   | 2065 | 1.1231          | 37.9682   | 37.399  |
| 0.7867        | 6.0   | 2478 | 1.1286          | 38.272    | 37.4305 |
| 0.736         | 7.0   | 2891 | 1.1343          | 38.0986   | 37.31   |
| 0.696         | 8.0   | 3304 | 1.1416          | 38.2159   | 37.219  |
| 0.6674        | 9.0   | 3717 | 1.1494          | 38.2257   | 37.307  |
| 0.6488        | 10.0  | 4130 | 1.1540          | 38.1839   | 37.279  |


### Framework versions

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