ind-to-bbc-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: ind-to-bbc-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: 31.0264

ind-to-bbc-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: 1.2145
  • Sacrebleu: 31.0264
  • Gen Len: 45.24

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
4.3836 1.0 413 1.7444 26.819 45.5685
1.516 2.0 826 1.3331 30.1628 45.802
1.2184 3.0 1239 1.2480 30.7892 45.563
1.1033 4.0 1652 1.2187 31.136 45.289
1.0421 5.0 2065 1.2145 31.0264 45.24

Framework versions

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