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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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+ datasets:
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+ - sahil2801/CodeAlpaca-20k
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  library_name: peft
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+ tags:
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+ - facebook-opt-1.3b
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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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+ - opt-1.3b
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  ---
 
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+ We finetuned Facebook/OPT-1.3B on Code-Alpaca-Instruct Dataset (sahil2801/CodeAlpaca-20k) for 5 epochs 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 1 hour and 30 minutes and costed us only `$6` for the entire finetuning run!
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+
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+ #### Hyperparameters & Run details:
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+ - Model Path: facebook/opt-1.3b
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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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+
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+ ---
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+ license: apache-2.0
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+ ---