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README.md
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library_name: peft
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---
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## Training procedure
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###
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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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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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#### Finetuning Details:
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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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- 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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#### Hyperparameters & Additional Details:
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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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### INSTRUCTION:
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[instruction]
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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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license: apache-2.0
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