nllb-200-1.3B-ICFOSS-Malayalam_English_Translation1.3b

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: 1.0536
• Bleu: 36.7256
• Rouge: {'rouge1': 0.6977825292445439, 'rouge2': 0.47317224666360513, 'rougeL': 0.6369586014923634, 'rougeLsum': 0.6367120144580565}
• Chrf: {'score': 63.88643397225133, '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: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Bleu	Rouge	Chrf
1.1683	1.0	5750	1.0774	35.9761	{'rouge1': 0.6937855960659589, 'rouge2': 0.466938063654629, 'rougeL': 0.6325990208208303, 'rougeLsum': 0.6323899971616622}	{'score': 63.363704282940446, 'char_order': 6, 'word_order': 0, 'beta': 2}
1.1177	2.0	11500	1.0617	36.3486	{'rouge1': 0.6957984629345982, 'rouge2': 0.47067647725021045, 'rougeL': 0.6351678391451753, 'rougeLsum': 0.6350175761315434}	{'score': 63.657728669261445, 'char_order': 6, 'word_order': 0, 'beta': 2}
1.102	3.0	17250	1.0559	36.7216	{'rouge1': 0.6970801919668868, 'rouge2': 0.47279660574601357, 'rougeL': 0.6364385448189633, 'rougeLsum': 0.6362592345657716}	{'score': 63.89202343434442, 'char_order': 6, 'word_order': 0, 'beta': 2}
1.0967	4.0	23000	1.0545	36.7450	{'rouge1': 0.6977900451765099, 'rouge2': 0.4734910607221403, 'rougeL': 0.6373405033951935, 'rougeLsum': 0.6371420919202282}	{'score': 63.918132836888965, 'char_order': 6, 'word_order': 0, 'beta': 2}
1.0935	5.0	28750	1.0538	36.7038	{'rouge1': 0.6978511315129863, 'rouge2': 0.4733012047244315, 'rougeL': 0.6371351829239855, 'rougeLsum': 0.6369801889854168}	{'score': 63.87115369473548, 'char_order': 6, 'word_order': 0, 'beta': 2}
1.0928	6.0	34500	1.0536	36.7485	{'rouge1': 0.6977169592049554, 'rouge2': 0.4734304167965041, 'rougeL': 0.636966108177003, 'rougeLsum': 0.6367749449397957}	{'score': 63.894445637643784, 'char_order': 6, 'word_order': 0, 'beta': 2}
1.0918	7.0	40250	1.0536	36.7256	{'rouge1': 0.6977825292445439, 'rouge2': 0.47317224666360513, 'rougeL': 0.6369586014923634, 'rougeLsum': 0.6367120144580565}	{'score': 63.88643397225133, '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