--- 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: bbc-to-ind-nmt-v7 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: 38.1839 --- # bbc-to-ind-nmt-v7 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: 1.1540 - Sacrebleu: 38.1839 - Gen Len: 37.279 ## 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: 16 - 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 | |:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:| | 5.0915 | 1.0 | 413 | 2.2849 | 27.9598 | 38.462 | | 1.483 | 2.0 | 826 | 1.2052 | 35.2398 | 37.6305 | | 1.0733 | 3.0 | 1239 | 1.1450 | 36.4283 | 37.133 | | 0.9415 | 4.0 | 1652 | 1.1232 | 37.7264 | 37.198 | | 0.8558 | 5.0 | 2065 | 1.1231 | 37.9682 | 37.399 | | 0.7867 | 6.0 | 2478 | 1.1286 | 38.272 | 37.4305 | | 0.736 | 7.0 | 2891 | 1.1343 | 38.0986 | 37.31 | | 0.696 | 8.0 | 3304 | 1.1416 | 38.2159 | 37.219 | | 0.6674 | 9.0 | 3717 | 1.1494 | 38.2257 | 37.307 | | 0.6488 | 10.0 | 4130 | 1.1540 | 38.1839 | 37.279 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.14.6 - Tokenizers 0.19.1