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nllb-200-1.3B-ICFOSS-malayalam_Hindi_Translator

This model is a fine-tuned version of facebook/nllb-200-1.3B on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3788
  • Bleu: 62.5154
  • Rouge: {'rouge1': 0.42504662037099206, 'rouge2': 0.2891987093258279, 'rougeL': 0.4211514655126128, 'rougeLsum': 0.42156526904087943}
  • Chrf: {'score': 79.24933104383702, 'char_order': 6, 'word_order': 0, 'beta': 2}

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: 0.0002
  • 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: cosine
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Bleu Rouge Chrf
0.5095 1.0 4698 0.4099 59.5376 {'rouge1': 0.4220305313233426, 'rouge2': 0.2866519629954242, 'rougeL': 0.41646494668344247, 'rougeLsum': 0.4167340351207185} {'score': 77.52631821685847, 'char_order': 6, 'word_order': 0, 'beta': 2}
0.4213 2.0 9396 0.3842 61.7541 {'rouge1': 0.4247871478803683, 'rouge2': 0.28898946927686797, 'rougeL': 0.42099815319030365, 'rougeLsum': 0.4209781732451786} {'score': 78.54007352748269, 'char_order': 6, 'word_order': 0, 'beta': 2}
0.3888 3.0 14094 0.3785 62.2691 {'rouge1': 0.42665978089706913, 'rouge2': 0.28916951694997156, 'rougeL': 0.42136280849134333, 'rougeLsum': 0.4219221144613403} {'score': 79.11003191466068, 'char_order': 6, 'word_order': 0, 'beta': 2}
0.3764 4.0 18792 0.3785 62.4514 {'rouge1': 0.42373682879235186, 'rouge2': 0.2891987093258279, 'rougeL': 0.41970156954196886, 'rougeLsum': 0.4201735443294585} {'score': 79.20088697777769, 'char_order': 6, 'word_order': 0, 'beta': 2}
0.3741 5.0 23490 0.3788 62.5154 {'rouge1': 0.42504662037099206, 'rouge2': 0.2891987093258279, 'rougeL': 0.4211514655126128, 'rougeLsum': 0.42156526904087943} {'score': 79.24933104383702, 'char_order': 6, 'word_order': 0, 'beta': 2}

Framework versions

  • PEFT 0.10.0
  • Transformers 4.40.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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