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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-v7
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: 31.4148
---
<!-- 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-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: 1.1534
- Sacrebleu: 31.4148
- Gen Len: 45.246
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 5.1799 | 1.0 | 413 | 2.3351 | 25.3863 | 45.489 |
| 1.6805 | 2.0 | 826 | 1.3384 | 30.3818 | 45.661 |
| 1.2114 | 3.0 | 1239 | 1.2202 | 30.9982 | 45.562 |
| 1.0517 | 4.0 | 1652 | 1.1827 | 31.2905 | 45.3925 |
| 0.9461 | 5.0 | 2065 | 1.1678 | 31.6094 | 45.2625 |
| 0.8728 | 6.0 | 2478 | 1.1471 | 31.2517 | 45.4265 |
| 0.8153 | 7.0 | 2891 | 1.1497 | 31.332 | 45.1645 |
| 0.7719 | 8.0 | 3304 | 1.1467 | 31.372 | 45.3915 |
| 0.743 | 9.0 | 3717 | 1.1491 | 31.4979 | 45.0825 |
| 0.7204 | 10.0 | 4130 | 1.1534 | 31.4148 | 45.246 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1
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