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souvik-biswas/codegemma-webdev-lora

sourceHugging Faceotherupdated 15d agoView on Hugging Face
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codegemma-webdev-lora

This model is a fine-tuned version of google/codegemma-1.1-2b on the vulcan dataset. It achieves the following results on the evaluation set:

  • —Loss: 0.0283

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: 2
  • —evalbatchsize: 2
  • —seed: 42
  • —distributed_type: multi-GPU
  • —num_devices: 2
  • —gradientaccumulationsteps: 4
  • —totaltrainbatch_size: 16
  • —totalevalbatch_size: 4
  • —optimizer: Use OptimizerNames.PAGEDADAMW8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • —lrschedulertype: cosine
  • —lrschedulerwarmup_steps: 0.05
  • —num_epochs: 3
  • —mixedprecisiontraining: Native AMP

Training results

Training LossEpochStepValidation Loss
0.02550.74842000.0289
0.02791.49394000.0286
0.02622.23956000.0285
0.02602.98788000.0283

Framework versions

  • —PEFT 0.18.1
  • —Transformers 5.0.0
  • —Pytorch 2.10.0+cu128
  • —Datasets 4.0.0
  • —Tokenizers 0.22.2