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library_name: peft
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---
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## Training procedure
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datasets:
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- sahil2801/CodeAlpaca-20k
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library_name: peft
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tags:
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- codellama7b
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- code
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- instruct
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- instruct-code
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- code-alpaca
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- alpaca-instruct
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- alpaca
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- codellama7b
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- gpt2
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We finetuned CodeLlama7B on Code-Alpaca-Instruct Dataset (sahil2801/CodeAlpaca-20k) for 5 epochs or ~ 25,000 steps using [MonsterAPI](https://monsterapi.ai) no-code [LLM finetuner](https://docs.monsterapi.ai/fine-tune-a-large-language-model-llm).
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This dataset is HuggingFaceH4/CodeAlpaca_20K unfiltered, removing 36 instances of blatant alignment.
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The finetuning session got completed in 4 hours and costed us only `$16` for the entire finetuning run!
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#### Hyperparameters & Run details:
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- Model Path: meta-llama/CodeLlama7B
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- Dataset: sahil2801/CodeAlpaca-20k
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- Learning rate: 0.0003
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- Number of epochs: 5
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- Data split: Training: 90% / Validation: 10%
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- Gradient accumulation steps: 1
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---
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license: apache-2.0
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