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f01480ec-6ce7-4b3c-9303-91367246caed

This model is a fine-tuned version of oopsung/llama2-7b-koNqa-test-v1 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1468

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: 0.000212
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 50
  • training_steps: 500

Training results

Training Loss Epoch Step Validation Loss
No log 0.0009 1 2.8770
0.4067 0.0443 50 0.5001
0.2624 0.0887 100 0.3697
0.24 0.1330 150 0.3292
0.1908 0.1774 200 0.3351
0.166 0.2217 250 0.2703
0.1555 0.2661 300 0.2393
0.1737 0.3104 350 0.1916
0.1532 0.3548 400 0.1630
0.1183 0.3991 450 0.1467
0.1017 0.4435 500 0.1468

Framework versions

  • PEFT 0.13.2
  • Transformers 4.46.0
  • Pytorch 2.5.0+cu124
  • Datasets 3.0.1
  • Tokenizers 0.20.1
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