clee9 / opt125m-lora-pruned-wanda-2-4

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Total runs: 0
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Model's Last Updated: December 10 2024

Introduction of opt125m-lora-pruned-wanda-2-4

Model Details of opt125m-lora-pruned-wanda-2-4

opt125m-lora-pruned-wanda-2-4

This model is a fine-tuned version of saresri/pruned_opt on an unknown dataset.

Model description

More information needed

Intended uses & limitations

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Training and evaluation data

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Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0002
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1
  • num_epochs: 3
  • mixed_precision_training: Native AMP
Training results

Evaluation Results (Validation): {'rouge1': 0.2943, 'rouge2': 0.0737, 'rougeL': 0.1923, 'rougeLsum': 0.2062}

Evaluation Results (Test): {'rouge1': 0.1739, 'rouge2': 0.088, 'rougeL': 0.144, 'rougeLsum': 0.1451}

Framework versions
  • PEFT 0.14.0
  • Transformers 4.47.0
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.21.0

Runs of clee9 opt125m-lora-pruned-wanda-2-4 on huggingface.co

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