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  ---
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  library_name: peft
 
 
 
 
 
 
 
 
 
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  ---
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- ## Training procedure
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- ### Framework versions
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- - PEFT 0.5.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  library_name: peft
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+ tags:
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+ - gpt
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+ - code
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+ - instruct
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+ - WizardLM
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+ datasets:
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+ - WizardLM/WizardLM_evol_instruct_70k
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+ base_model: gpt2
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+ license: apache-2.0
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  ---
 
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+ ### Finetuning Overview:
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+ **Model Used:** gpt2
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+ **Dataset:** WizardLM/WizardLM_evol_instruct_70k
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+ #### Dataset Insights:
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+
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+ The WizardLM/WizardLM_evol_instruct_70k dataset, tailored specifically for enhancing interactive capabilities, was developed using the EVOL-Instruct method. This method enhances a smaller dataset with tougher questions for the LLM to perform.
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+
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+ #### Finetuning Details:
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+
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+ With the utilization of [MonsterAPI](https://monsterapi.ai)'s [LLM finetuner](https://docs.monsterapi.ai/fine-tune-a-large-language-model-llm), this finetuning:
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+
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+ - Was achieved with great cost-effectiveness.
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+ - Completed in a total duration of 14mins for 1 epoch.
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+ - Costed `$0.525` for the entire epoch.
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+
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+ #### Hyperparameters & Additional Details:
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+
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+ - **Epochs:** 1
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+ - **Cost Per Epoch:** $0.525
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+ - **Total Finetuning Cost:** $0.525
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+ - **Model Path:** gpt2
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+ - **Learning Rate:** 0.0002
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+ - **Data Split:** 90% train 10% validation
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+ - **Gradient Accumulation Steps:** 4
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+
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+ ```
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+ ### INSTRUCTION:
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+ [instruction]
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+
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+ ### RESPONSE:
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+ [output]
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+ ```
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+ Training loss :
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+ ![training loss](train-loss.png "Training loss")
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+
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+ ---
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+ license: apache-2.0