--- 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-v8 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: 31.404 --- # ind-to-bbc-nmt-v8 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: 1.1714 - Sacrebleu: 31.404 - Gen Len: 45.259 ## 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: 32 - 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 | |:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:| | 5.9718 | 1.0 | 207 | 3.5105 | 24.1454 | 44.5145 | | 2.5392 | 2.0 | 414 | 1.6246 | 28.1486 | 45.45 | | 1.46 | 3.0 | 621 | 1.3187 | 30.5425 | 45.375 | | 1.2013 | 4.0 | 828 | 1.2437 | 31.2443 | 45.2075 | | 1.0869 | 5.0 | 1035 | 1.2084 | 31.0749 | 45.3445 | | 1.0083 | 6.0 | 1242 | 1.1851 | 31.167 | 45.35 | | 0.9563 | 7.0 | 1449 | 1.1811 | 31.2377 | 45.344 | | 0.9149 | 8.0 | 1656 | 1.1719 | 31.2539 | 45.343 | | 0.8881 | 9.0 | 1863 | 1.1738 | 31.5399 | 45.145 | | 0.872 | 10.0 | 2070 | 1.1714 | 31.404 | 45.259 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.14.6 - Tokenizers 0.19.1