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--- |
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library_name: peft |
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tags: |
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- code |
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- instruct |
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- falcon |
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datasets: |
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- HuggingFaceH4/no_robots |
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base_model: tiiuae/falcon-7b |
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license: apache-2.0 |
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--- |
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### Finetuning Overview: |
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**Model Used:** tiiuae/falcon-7b |
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**Dataset:** HuggingFaceH4/no_robots |
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#### Dataset Insights: |
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[No Robots](https://huggingface.co/datasets/HuggingFaceH4/no_robots) is a high-quality dataset of 10,000 instructions and demonstrations created by skilled human annotators. This data can be used for supervised fine-tuning (SFT) to make language models follow instructions better. |
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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 1h 21m 21s for 3 epochs using an A6000 48GB GPU. |
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- Costed `$0.909` for 1 epoch. |
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#### Hyperparameters & Additional Details: |
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- **Epochs:** 3 |
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- **Cost Per Epoch:** $0.909 |
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- **Total Finetuning Cost:** $2.727 |
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- **Model Path:** tiiuae/falcon-7b |
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- **Learning Rate:** 0.0002 |
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- **Data Split:** 100% train |
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- **Gradient Accumulation Steps:** 4 |
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- **lora r:** 32 |
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- **lora alpha:** 64 |
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#### Prompt Structure |
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``` |
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<|system|> <|endoftext|> <|user|> [USER PROMPT]<|endoftext|> <|assistant|> [ASSISTANT ANSWER] <|endoftext|> |
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``` |
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#### Train loss : |
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license: apache-2.0 |
