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SAS-finetuned-cochrane-medeasi

This model is a fine-tuned version of haining/scientific_abstract_simplification on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: nan
  • Bleu: {'bleu': 3.5213074954706223e-06, 'precisions': [0.49951576455396535, 0.15234465234465233, 0.06880219369313224, 0.036816459122902004], 'brevity_penalty': 2.9884691172035265e-05, 'length_ratio': 0.08757975289560735, 'translation_length': 9293, 'reference_length': 106109}
  • Sari: {'sari': 2.5441859559296094}

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: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Bleu Sari
No log 1.0 159 nan {'bleu': 3.5213074954706223e-06, 'precisions': [0.49951576455396535, 0.15234465234465233, 0.06880219369313224, 0.036816459122902004], 'brevity_penalty': 2.9884691172035265e-05, 'length_ratio': 0.08757975289560735, 'translation_length': 9293, 'reference_length': 106109} {'sari': 2.5441859559296094}
No log 2.0 318 nan {'bleu': 3.5213074954706223e-06, 'precisions': [0.49951576455396535, 0.15234465234465233, 0.06880219369313224, 0.036816459122902004], 'brevity_penalty': 2.9884691172035265e-05, 'length_ratio': 0.08757975289560735, 'translation_length': 9293, 'reference_length': 106109} {'sari': 2.5441859559296094}
No log 3.0 477 nan {'bleu': 3.5213074954706223e-06, 'precisions': [0.49951576455396535, 0.15234465234465233, 0.06880219369313224, 0.036816459122902004], 'brevity_penalty': 2.9884691172035265e-05, 'length_ratio': 0.08757975289560735, 'translation_length': 9293, 'reference_length': 106109} {'sari': 2.5441859559296094}

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1
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