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phi2 fine-tuned with full dataset and high learning rate: Loss dropped to 0.02
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metadata
license: mit
library_name: peft
tags:
  - trl
  - sft
  - generated_from_trainer
datasets:
  - generator
base_model: microsoft/phi-2
model-index:
  - name: phi2_fine_tune_istanbul_rugs
    results: []

phi2_fine_tune_istanbul_rugs

This model is a fine-tuned version of microsoft/phi-2 on the generator dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8105

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: 0.0008
  • train_batch_size: 2
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • training_steps: 300

Training results

Training Loss Epoch Step Validation Loss
0.6408 0.72 10 0.5720
0.4116 1.45 20 0.5234
0.3467 2.17 30 0.5068
0.328 2.9 40 0.4990
0.3013 3.62 50 0.5022
0.267 4.34 60 0.5051
0.2407 5.07 70 0.5151
0.2084 5.79 80 0.5329
0.1821 6.52 90 0.5566
0.1635 7.24 100 0.5996
0.1431 7.96 110 0.6137
0.1164 8.69 120 0.6461
0.1045 9.41 130 0.6714
0.0903 10.14 140 0.6719
0.0773 10.86 150 0.6802
0.0653 11.58 160 0.7234
0.0595 12.31 170 0.7497
0.0523 13.03 180 0.7281
0.0453 13.76 190 0.7439
0.0405 14.48 200 0.7655
0.0363 15.2 210 0.7674
0.0323 15.93 220 0.7835
0.0293 16.65 230 0.7924
0.0276 17.38 240 0.7981
0.0257 18.1 250 0.8023
0.0252 18.82 260 0.8019
0.0236 19.55 270 0.8040
0.023 20.27 280 0.8089
0.0232 21.0 290 0.8104
0.0231 21.72 300 0.8105

Framework versions

  • PEFT 0.9.0
  • Transformers 4.38.1
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.1
  • Tokenizers 0.15.2