metadata

library_name: transformers
license: cc-by-nc-4.0
base_model: kinleyrabgay/nllb-200-600M-dzo-eng
tags:
  - generated_from_trainer
metrics:
  - bleu
model-index:
  - name: nllb-200-600M-dzo-eng
    results: []

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'])