outputs
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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Base model
google/gemma-7b