phi-3-mini-LoRA / README.md
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metadata
base_model: microsoft/Phi-3-mini-128k-instruct
library_name: peft
license: mit
tags:
  - trl
  - sft
  - generated_from_trainer
model-index:
  - name: phi-3-mini-LoRA
    results: []

phi-3-mini-LoRA

This model is a fine-tuned version of microsoft/Phi-3-mini-128k-instruct on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3525

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: 1
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 2
  • 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
0.3351 0.17 500 0.3755
0.3312 0.34 1000 0.3644
0.3079 0.51 1500 0.3597
0.3195 0.68 2000 0.3577
0.3218 0.85 2500 0.3557
0.3034 1.02 3000 0.3553
0.296 1.19 3500 0.3543
0.3175 1.36 4000 0.3539
0.3257 1.53 4500 0.3533
0.3263 1.7 5000 0.3526
0.3209 1.87 5500 0.3522
0.3221 2.04 6000 0.3528
0.2927 2.21 6500 0.3526
0.2922 2.38 7000 0.3527
0.2968 2.55 7500 0.3525
0.2968 2.72 8000 0.3526
0.3094 2.89 8500 0.3525

Framework versions

  • PEFT 0.8.2
  • Transformers 4.38.0
  • Pytorch 2.2.1
  • Datasets 2.17.0
  • Tokenizers 0.15.2