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chansung/coding_llamaduo_60k

sourceHugging Facegemmaupdated 2y agoView on Hugging Face
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Model Card

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codingllamaduo60k

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: 1.6318

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: 4
  • gradientaccumulationsteps: 2
  • totaltrainbatch_size: 16
  • totalevalbatch_size: 8
  • 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
0.66181.02521.2071
0.57312.05041.1436
0.51983.07561.1346
0.47834.010081.1536
0.43785.012601.2225
0.38366.015121.2893
0.33817.017641.4050
0.30438.020161.5185
0.27789.022681.6143
0.274810.025201.6318

Framework versions

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