Llama-3.1-8B-MagPie-Ultra

This model is a fine-tuned version of meta-llama/Llama-3.1-8B on the argilla-warehouse/magpie-ultra-v1.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5915

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: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
0.5939 0.9998 1002 0.5915

Framework versions

  • Transformers 4.45.0
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.1
  • Tokenizers 0.20.0
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Dataset used to train argilla-warehouse/Llama-3.1-8B-MagPie-Ultra