phi3.5-mini-adapter_v2

This model is a fine-tuned version of microsoft/Phi-3.5-mini-instruct on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1344

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: 1e-05
  • train_batch_size: 24
  • eval_batch_size: 24
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 48
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 50

Training results

Training Loss Epoch Step Validation Loss
17.6422 0.4545 10 17.2166
13.0308 0.9091 20 12.5267
8.4662 1.3636 30 7.9483
2.4521 1.8182 40 1.3982
0.3917 2.2727 50 0.3427
0.3042 2.7273 60 0.3092
0.2051 3.1818 70 0.2451
0.2043 3.6364 80 0.2022
0.1599 4.0909 90 0.1907
0.1658 4.5455 100 0.1727
0.1527 5.0 110 0.1595
0.1281 5.4545 120 0.1501
0.1079 5.9091 130 0.1435
0.0896 6.3636 140 0.1369
0.097 6.8182 150 0.1340
0.0841 7.2727 160 0.1449
0.0771 7.7273 170 0.1344

Framework versions

  • PEFT 0.11.1
  • Transformers 4.43.1
  • Pytorch 2.4.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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