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phi-3-mini-QLoRA

This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5741

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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
1.1422 0.1810 100 0.6625
0.6238 0.3619 200 0.6002
0.5932 0.5429 300 0.5906
0.5926 0.7238 400 0.5860
0.5794 0.9048 500 0.5834
0.5868 1.0857 600 0.5815
0.5711 1.2667 700 0.5796
0.5729 1.4476 800 0.5785
0.5858 1.6286 900 0.5772
0.5732 1.8095 1000 0.5763
0.5736 1.9905 1100 0.5756
0.5638 2.1715 1200 0.5754
0.5769 2.3524 1300 0.5746
0.5668 2.5334 1400 0.5745
0.5675 2.7143 1500 0.5742
0.5693 2.8953 1600 0.5741

Framework versions

  • PEFT 0.10.0
  • Transformers 4.40.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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