Test_sagemaker

This model is a fine-tuned version of NousResearch/Llama-2-7b-hf on the None 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: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 64
  • optimizer: Use OptimizerNames.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: 500
  • num_epochs: 1
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
No log 0.9874 54 0.7080 0.5133 0.5101 0.4731 0.4909

Framework versions

  • PEFT 0.14.0
  • Transformers 4.47.0
  • Pytorch 2.3.1.post300
  • Datasets 3.2.0
  • Tokenizers 0.21.0
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