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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-v5
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: 38.4814
---
<!-- 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-v5
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: 1.2310
- Sacrebleu: 38.4814
- Gen Len: 37.8455
## 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: 4
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:-------:|
| 3.4154 | 1.0 | 1650 | 1.2829 | 33.2857 | 37.9245 |
| 1.1633 | 2.0 | 3300 | 1.1418 | 36.6342 | 37.407 |
| 0.9377 | 3.0 | 4950 | 1.1148 | 38.0023 | 37.17 |
| 0.795 | 4.0 | 6600 | 1.1197 | 38.2402 | 37.3695 |
| 0.6827 | 5.0 | 8250 | 1.1465 | 38.3719 | 37.315 |
| 0.5937 | 6.0 | 9900 | 1.1642 | 38.3424 | 37.547 |
| 0.5216 | 7.0 | 11550 | 1.1917 | 38.56 | 37.8515 |
| 0.466 | 8.0 | 13200 | 1.2079 | 38.6061 | 37.6135 |
| 0.425 | 9.0 | 14850 | 1.2228 | 38.4918 | 37.928 |
| 0.3995 | 10.0 | 16500 | 1.2310 | 38.4814 | 37.8455 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1
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