ind-to-bbc-nmt-v2 / README.md
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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-v2
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: 31.5851
---
<!-- 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-v2
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: 1.1713
- Sacrebleu: 31.5851
- Gen Len: 45.311
## 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: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Sacrebleu | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 4.8114 | 1.0 | 825 | 1.4552 | 28.698 | 45.0965 |
| 1.3328 | 2.0 | 1650 | 1.2516 | 30.4316 | 45.683 |
| 1.163 | 3.0 | 2475 | 1.1934 | 30.9199 | 45.474 |
| 0.9982 | 4.0 | 3300 | 1.1762 | 31.635 | 45.254 |
| 0.9001 | 5.0 | 4125 | 1.1713 | 31.5851 | 45.311 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1