medical-bidirectional-machine-translation-checkpoints-511042

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medical-bidirectional-machine-translation-checkpoints-511042

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

• Loss: 2.3042
• Bleu: 50.0202
• Meteor: 0.7238
• Ter: 42.2003

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 32
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.05
• num_epochs: 3
• mixed_precision_training: Native AMP
• label_smoothing_factor: 0.1

Training results

Framework versions

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