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This model is a fine-tuned version of google/gemma-7b on gnumanth/gita dataset.

Model description

Experimental fine tune gemma-7b model

Intended uses & limitations

Gita interpretation, no limitations.

Training procedure

SFTTrainer

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0002
  • train_batch_size: 1
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 4
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 2
  • training_steps: 10
  • mixed_precision_training: Native AMP

Training results

TrainOutput(global_step=10, training_loss=0.5232708215713501, metrics={'train_runtime': 13.8846, 'train_samples_per_second': 2.881, 'train_steps_per_second': 0.72, 'total_flos': 55989006336000.0, 'train_loss': 0.5232708215713501, 'epoch': 10.0})

Framework versions

  • PEFT 0.8.2
  • Transformers 4.38.1
  • Pytorch 2.1.0+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.2
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google/gemma-7b
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Dataset used to train gnumanth/gemma-gita