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chansung/coding_llamaduo_60k_v0.2

sourceHugging Facegemmaupdated 2y agoView on Hugging Face
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codingllamaduo60k_v0.2

This model is a fine-tuned version of google/gemma-7b on the chansung/mergeddscoding dataset. It achieves the following results on the evaluation set:

  • —Loss: 1.3326

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: 0.0002
  • —trainbatchsize: 4
  • —evalbatchsize: 4
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 4
  • —gradientaccumulationsteps: 2
  • —totaltrainbatch_size: 32
  • —totalevalbatch_size: 16
  • —optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_ratio: 0.1
  • —num_epochs: 10

Training results

Training LossEpochStepValidation Loss
0.74991.01261.2580
0.60582.02521.1687
0.55713.03781.1492
0.51184.05041.1551
0.47115.06301.1767
0.42876.07561.1948
0.39437.08821.2383
0.36128.010081.2904
0.34579.011341.3253
0.332810.012601.3326

Framework versions

  • —PEFT 0.7.1
  • —Transformers 4.40.1
  • —Pytorch 2.2.2+cu121
  • —Datasets 2.19.0
  • —Tokenizers 0.19.1