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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: 0.5761

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: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_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: 3

Training results

Training Loss Epoch Step Validation Loss
1.1336 0.1809 100 0.6788
0.6283 0.3618 200 0.6030
0.5944 0.5427 300 0.5931
0.5953 0.7237 400 0.5879
0.5793 0.9046 500 0.5852
0.5908 1.0855 600 0.5832
0.5717 1.2664 700 0.5812
0.5748 1.4473 800 0.5802
0.5876 1.6282 900 0.5787
0.5725 1.8091 1000 0.5778
0.5749 1.9900 1100 0.5772
0.5646 2.1710 1200 0.5769
0.5806 2.3519 1300 0.5764
0.5679 2.5328 1400 0.5762
0.5683 2.7137 1500 0.5761
0.5715 2.8946 1600 0.5761

Framework versions

  • PEFT 0.11.1
  • Transformers 4.41.2
  • Pytorch 2.1.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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