ind-to-bbc-nmt-v6 / 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-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: 31.0331
---
<!-- 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-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: 1.1587
- Sacrebleu: 31.0331
- Gen Len: 45.1815
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 4.3415 | 1.0 | 825 | 1.6110 | 27.0363 | 45.267 |
| 1.415 | 2.0 | 1650 | 1.2550 | 30.5956 | 45.5 |
| 1.1044 | 3.0 | 2475 | 1.1769 | 31.2342 | 45.4315 |
| 0.951 | 4.0 | 3300 | 1.1532 | 31.8633 | 45.149 |
| 0.8409 | 5.0 | 4125 | 1.1340 | 31.5171 | 45.355 |
| 0.7582 | 6.0 | 4950 | 1.1273 | 31.0686 | 45.222 |
| 0.6937 | 7.0 | 5775 | 1.1387 | 31.3129 | 45.1355 |
| 0.6433 | 8.0 | 6600 | 1.1479 | 31.444 | 45.233 |
| 0.6056 | 9.0 | 7425 | 1.1521 | 31.3122 | 45.0945 |
| 0.5819 | 10.0 | 8250 | 1.1587 | 31.0331 | 45.1815 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.14.6
- Tokenizers 0.19.1