phi3.5-mini-adapter_v1

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: 0.0998

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: 3e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • 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
14.2062 0.6061 10 13.2015
5.0286 1.2121 20 3.9207
0.248 1.8182 30 0.2396
0.1801 2.4242 40 0.1860
0.1496 3.0303 50 0.1639
0.212 3.6364 60 0.1333
0.0822 4.2424 70 0.1134
0.07 4.8485 80 0.1061
0.0871 5.4545 90 0.1178
0.0645 6.0606 100 0.1017
0.0558 6.6667 110 0.0998

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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