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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: bbc-to-ind-nmt-v6
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: 38.2052
---
<!-- 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-v6
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: 1.1940
- Sacrebleu: 38.2052
- Gen Len: 37.467
## 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: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Sacrebleu | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 4.1507 | 1.0 | 825 | 1.3826 | 31.3365 | 37.6035 |
| 1.2319 | 2.0 | 1650 | 1.1646 | 36.0321 | 37.553 |
| 0.9893 | 3.0 | 2475 | 1.1238 | 37.2804 | 37.284 |
| 0.8593 | 4.0 | 3300 | 1.1213 | 38.1118 | 37.409 |
| 0.7624 | 5.0 | 4125 | 1.1353 | 38.2863 | 37.234 |
| 0.6872 | 6.0 | 4950 | 1.1404 | 38.3932 | 37.1405 |
| 0.6253 | 7.0 | 5775 | 1.1566 | 38.1803 | 37.191 |
| 0.5781 | 8.0 | 6600 | 1.1723 | 38.3633 | 37.351 |
| 0.5441 | 9.0 | 7425 | 1.1836 | 38.25 | 37.485 |
| 0.5214 | 10.0 | 8250 | 1.1940 | 38.2052 | 37.467 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1
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