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SFTCodePhi-3-mini-4k-instructAPPS3k

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

  • Loss: 0.7239

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: 5e-06
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 100
  • training_steps: 3000

Training results

Training Loss Epoch Step Validation Loss
0.8413 0.6740 200 0.7941
0.7599 1.3479 400 0.7499
0.7385 2.0219 600 0.7340
0.724 2.6959 800 0.7309
0.7263 3.3698 1000 0.7300
0.7194 4.0438 1200 0.7287
0.7186 4.7178 1400 0.7262
0.7204 5.3917 1600 0.7250
0.72 6.0657 1800 0.7243
0.7151 6.7397 2000 0.7244
0.7156 7.4136 2200 0.7238
0.7173 8.0876 2400 0.7240
0.7156 8.7616 2600 0.7240
0.7136 9.4356 2800 0.7239
0.7227 10.1095 3000 0.7239

Framework versions

  • PEFT 0.11.0
  • Transformers 4.40.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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