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English-to-Meru-language-translation-LoRA
KnoxDevelopers/English-to-Meru-language-translation-LoRA
English-to-Meru-language-translation-LoRA is a machine learning model from KnoxDevelopers. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as cc-by-nc-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- cc-by-nc-4.0
- Access
- Public
- Created
- Aug 4, 2026
- Updated
- Aug 4, 2026
- SHA
- c29b430a
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
English-to-Meru-language-translation-LoRA
This model is a fine-tuned version of facebook/nllb-200-distilled-600M on the English-Meru dataset. It achieves the following results on the evaluation set:
- Loss: 1.7783
Model description
A LoRA adapter for translating text from English to Kimeru.
Intended uses & limitations
More information needed
Training and evaluation data
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 7
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 5.2921 | 1.0 | 1742 | 2.3882 |
| 4.6466 | 2.0 | 3484 | 2.1125 |
| 4.3495 | 3.0 | 5226 | 1.9624 |
| 4.1860 | 4.0 | 6968 | 1.8715 |
| 4.0373 | 5.0 | 8710 | 1.8175 |
| 3.8794 | 6.0 | 10452 | 1.7889 |
| 3.9127 | 7.0 | 12194 | 1.7783 |
Evaluation metrics
| Metric | Results | Explained |
|---|---|---|
| sacrebleu | 7.824 | Evaluation matches exact word sequence referencing our ground truth and adapter output. |
| 0-20= translation is literal or broken, 20-50=good, >60=very good or identical training and test data. | ||
| chrF++ | 37.682 | Eval matches character sequence instead of whole words. |
| Model adapter is getting the root words and grammar concepts right but using different word variations or spellings than our ground truth, this is concluded due to the low sacrebleu results. |
Framework versions
- PEFT 0.19.1
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2
- Library
- peft
- License
- cc-by-nc-4.0
- Languages
- en, mer
- Created
- Aug 4, 2026
- Updated
- Aug 4, 2026