A remarkable 68% boost in performance over the base model.
Completed in a total duration of 2d 7h 45m for 10 epochs using an A6000 48GB GPU.
Demonstrated cost-effectiveness, with a single epoch costing only $11.3.
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Hyperparameters & Additional Details:
Epochs: 10
Total Finetuning Cost: $113
Model Path: google/gemma-2b
Learning Rate: 0.0001
Gradient Accumulation Steps: 32
lora_alpha: 128
lora_r: 64
Benchmarking Performance Details:
Finetuned Gemma-2B using MonsterAPI achieved a remarkable score of 20.02 on the GSM Plus benchmark.
This represents a 68% improvement over its base model performance.
Notably, it outperformed larger models like LLaMA-2-13B and Code-LLaMA-7B
This result suggests that targeted fine-tuning can significantly improve model performance.
