nllb-200-600M-dzo-eng
This model is a fine-tuned version of facebook/nllb-200-distilled-600M on kinleyrabgay/dz_to_en dataset. It achieves the following results on the evaluation set:
- Loss: 0.0774
- Bleu: 59.5127
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Bleu |
---|---|---|---|---|
0.0765 | 1.0 | 1250 | 0.0746 | 58.0373 |
0.0576 | 2.0 | 2500 | 0.0728 | 58.5746 |
0.0465 | 3.0 | 3750 | 0.0735 | 59.3099 |
0.0381 | 4.0 | 5000 | 0.0758 | 59.2493 |
0.033 | 5.0 | 6250 | 0.0774 | 59.5127 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
Usage
from transformers import pipeline
translator = pipeline(
"translation",
model="kinleyrabgay/nllb-200-600M-dzo-eng",
src_lang="dzo_Tibt",
tgt_lang="eng_Latn"
)
dz_text = "ག་ནི་བ་ ཡིད་ཕྲོག"
translation = translator(dz_text)
print(translation[0]['translation_text'])
- Downloads last month
- 72
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
🙋
1
Ask for provider support
Model tree for kinleyrabgay/nllb-200-600M-dzo-eng
Unable to build the model tree, the base model loops to the model itself. Learn more.