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phi-3-mini-QLoRA

This model is a fine-tuned version of microsoft/Phi-3-mini-4k-instruct on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1546

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: 2
  • total_train_batch_size: 8
  • 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
2.2359 0.1416 50 1.9291
1.5215 0.2833 100 1.2761
1.287 0.4249 150 1.2268
1.2613 0.5666 200 1.2073
1.2341 0.7082 250 1.1996
1.2037 0.8499 300 1.1953
1.2117 0.9915 350 1.1871
1.2023 1.1331 400 1.1813
1.1635 1.2748 450 1.1770
1.1689 1.4164 500 1.1732
1.2013 1.5581 550 1.1720
1.1853 1.6997 600 1.1675
1.1933 1.8414 650 1.1648
1.1774 1.9830 700 1.1619
1.1633 2.1246 750 1.1626
1.1756 2.2663 800 1.1593
1.1597 2.4079 850 1.1587
1.1599 2.5496 900 1.1562
1.1145 2.6912 950 1.1567
1.162 2.8329 1000 1.1553
1.1507 2.9745 1050 1.1546

Framework versions

  • PEFT 0.12.0
  • Transformers 4.43.3
  • Pytorch 2.2.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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