--- 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-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: 31.4148 --- # ind-to-bbc-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: 1.1534 - Sacrebleu: 31.4148 - Gen Len: 45.246 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:| | 5.1799 | 1.0 | 413 | 2.3351 | 25.3863 | 45.489 | | 1.6805 | 2.0 | 826 | 1.3384 | 30.3818 | 45.661 | | 1.2114 | 3.0 | 1239 | 1.2202 | 30.9982 | 45.562 | | 1.0517 | 4.0 | 1652 | 1.1827 | 31.2905 | 45.3925 | | 0.9461 | 5.0 | 2065 | 1.1678 | 31.6094 | 45.2625 | | 0.8728 | 6.0 | 2478 | 1.1471 | 31.2517 | 45.4265 | | 0.8153 | 7.0 | 2891 | 1.1497 | 31.332 | 45.1645 | | 0.7719 | 8.0 | 3304 | 1.1467 | 31.372 | 45.3915 | | 0.743 | 9.0 | 3717 | 1.1491 | 31.4979 | 45.0825 | | 0.7204 | 10.0 | 4130 | 1.1534 | 31.4148 | 45.246 | ### Framework versions - Transformers 4.41.2 - Pytorch 2.3.0+cu121 - Datasets 2.14.6 - Tokenizers 0.19.1