PEFT
code
instruct
zephyr
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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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+ library_name: transformers
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+ tags:
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+ - code
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+ - instruct
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+ - zephyr
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+ datasets:
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+ - Zangs3011/no_robots_FalconChatFormated
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+ base_model: HuggingFaceH4/zephyr-7b-alpha
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+ license: apache-2.0
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  ---
 
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+ ### Finetuning Overview:
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+ **Model Used:** HuggingFaceH4/zephyr-7b-alpha
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+ **Dataset:** Zangs3011/no_robots_FalconChatFormated
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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, it was developed using EVOL-Instruct method.Which will basically enhance a smaller dataset, with tougher quesitons for the LLM to perform
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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 36mins 47secs for 1 epoch using an A6000 48GB GPU.
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+ - Costed `$1.212` 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:** $1.212
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+ - **Total Finetuning Cost:** $1.212
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+ - **Model Path:** HuggingFaceH4/zephyr-7b-alpha
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+ - **Learning Rate:** 0.0002
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+ - **Data Split:** 99% train 1% validation
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+ - **Gradient Accumulation Steps:** 4
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+
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+ ---
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+ Prompt Structure
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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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+ [text]
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+ ```
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+ Eval loss :
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+
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+ ![training loss](https://cdn-uploads.huggingface.co/production/uploads/63ba46aa0a9866b28cb19a14/ZltGlksaxy6uCIiQ45X-L.png)
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+
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+ license: apache-2.0