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ArunIcfoss/mbart-large-50-many-to-many-mmt-ICFOSS-Malayalam_English_Translation

sourceHugging Faceupdated 2y agoView on Hugging Face
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Model Card

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mbart-large-50-many-to-many-mmt-ICFOSS-MalayalamEnglishTranslation

This model is a fine-tuned version of facebook/mbart-large-50-many-to-many-mmt on the None dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.3733
  • —Bleu: 28.9041
  • —Rouge: {'rouge1': 0.6211709615166336, 'rouge2': 0.3817538086155071, 'rougeL': 0.5654819931253774, 'rougeLsum': 0.5656455299372645}
  • —Chrf: {'score': 56.252579884228325, 'charorder': 6, 'wordorder': 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
  • —trainbatchsize: 16
  • —evalbatchsize: 16
  • —seed: 42
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: cosine
  • —num_epochs: 8

Training results

Training LossEpochStepValidation LossBleuRougeChrf
1.53291.047001.428427.0756{'rouge1': 0.6054918604734425, 'rouge2': 0.36327221325964765, 'rougeL': 0.5490261054453232, 'rougeLsum': 0.5491186003413475}{'score': 54.690919979551, 'charorder': 6, 'wordorder': 0, 'beta': 2}
1.42952.094001.392428.2063{'rouge1': 0.614973366544844, 'rouge2': 0.373550100507563, 'rougeL': 0.5589026806041284, 'rougeLsum': 0.5589661976445393}{'score': 55.635529686949894, 'charorder': 6, 'wordorder': 0, 'beta': 2}
1.39423.0141001.379228.5831{'rouge1': 0.6187502745206666, 'rouge2': 0.37919936984407143, 'rougeL': 0.5626864397042893, 'rougeLsum': 0.5627150169042504}{'score': 56.019161628219024, 'charorder': 6, 'wordorder': 0, 'beta': 2}
1.37954.0188001.375928.7523{'rouge1': 0.620515288235373, 'rouge2': 0.38072092563685545, 'rougeL': 0.5644953116677603, 'rougeLsum': 0.5646285495158272}{'score': 56.162861197192925, 'charorder': 6, 'wordorder': 0, 'beta': 2}
1.37235.0235001.373528.8675{'rouge1': 0.6225302294049915, 'rouge2': 0.382440202243451, 'rougeL': 0.5664785907343486, 'rougeLsum': 0.5666347228887372}{'score': 56.30835530151895, 'charorder': 6, 'wordorder': 0, 'beta': 2}
1.36846.0282001.373128.8915{'rouge1': 0.6214787732761883, 'rouge2': 0.3815472818692578, 'rougeL': 0.5656767538045446, 'rougeLsum': 0.5657190870277087}{'score': 56.251600472693866, 'charorder': 6, 'wordorder': 0, 'beta': 2}
1.36857.0329001.373228.8953{'rouge1': 0.6216361131555139, 'rouge2': 0.3821354228713412, 'rougeL': 0.5655300849639422, 'rougeLsum': 0.565595149126267}{'score': 56.26874870012928, 'charorder': 6, 'wordorder': 0, 'beta': 2}
1.36788.0376001.373328.9041{'rouge1': 0.6211709615166336, 'rouge2': 0.3817538086155071, 'rougeL': 0.5654819931253774, 'rougeLsum': 0.5656455299372645}{'score': 56.252579884228325, 'charorder': 6, 'wordorder': 0, 'beta': 2}

Framework versions

  • —PEFT 0.10.0
  • —Transformers 4.39.3
  • —Pytorch 2.1.0+cu121
  • —Datasets 2.18.0
  • —Tokenizers 0.15.0