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coding_llamaduo_60k_v0.2

This model is a fine-tuned version of google/gemma-7b on the chansung/merged_ds_coding 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
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss
0.7499 1.0 126 1.2580
0.6058 2.0 252 1.1687
0.5571 3.0 378 1.1492
0.5118 4.0 504 1.1551
0.4711 5.0 630 1.1767
0.4287 6.0 756 1.1948
0.3943 7.0 882 1.2383
0.3612 8.0 1008 1.2904
0.3457 9.0 1134 1.3253
0.3328 10.0 1260 1.3326

Framework versions

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

Dataset used to train chansung/coding_llamaduo_60k_v0.2