ndhieu1101/medical-bidirectional-machine-translation-checkpoints-170348

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medical-bidirectional-machine-translation-checkpoints-170348

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 2.4300
• —Bleu: 46.9673
• —Meteor: 0.7008
• —Ter: 44.9558

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
• —trainbatchsize: 8
• —evalbatchsize: 8
• —seed: 42
• —gradientaccumulationsteps: 4
• —totaltrainbatch_size: 32
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_ratio: 0.05
• —num_epochs: 3
• —mixedprecisiontraining: Native AMP
• —labelsmoothingfactor: 0.1

Training results

Framework versions

• —Transformers 4.57.6
• —Pytorch 2.10.0+cu128
• —Datasets 5.0.0
• —Tokenizers 0.22.2