bbc-to-ind-nmt-v3 / README.md
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metadata
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-v3
    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: 37.0979

bbc-to-ind-nmt-v3

This model is a fine-tuned version of facebook/nllb-200-distilled-600M on the nusatranslation_mt dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1424
  • Sacrebleu: 37.0979
  • Gen Len: 37.248

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: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Sacrebleu Gen Len
4.2762 1.0 413 1.5344 30.2931 37.92
1.3119 2.0 826 1.1962 35.3764 37.3035
1.0696 3.0 1239 1.1529 36.5225 37.204
0.9763 4.0 1652 1.1420 36.8954 37.0565
0.9298 5.0 2065 1.1424 37.0979 37.248

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.14.6
  • Tokenizers 0.19.1