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README.md
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---
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library_name:
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---
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## Training procedure
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###
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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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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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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 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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#### Hyperparameters & Additional Details:
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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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Prompt Structure
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```
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### INSTRUCTION:
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[instruction]
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### RESPONSE:
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[text]
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```
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Eval loss :
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![training loss](https://cdn-uploads.huggingface.co/production/uploads/63ba46aa0a9866b28cb19a14/ZltGlksaxy6uCIiQ45X-L.png)
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license: apache-2.0
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