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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-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: 38.1839
---
<!-- 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-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
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