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llama3.1-mini-QLoRA

This model is a fine-tuned version of meta-llama/Llama-3.2-1B on an unknown dataset.

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: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • 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_ratio: 0.1
  • num_epochs: 10

Training results

Framework versions

  • PEFT 0.13.2
  • Transformers 4.46.1
  • Pytorch 2.5.0+cu121
  • Datasets 3.0.2
  • Tokenizers 0.20.1
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