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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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- llama2 |
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datasets: |
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- HuggingFaceH4/no_robots |
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base_model: meta-llama/Llama-2-7b-hf |
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license: apache-2.0 |
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--- |
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### Finetuning Overview: |
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**Model Used:** meta-llama/Llama-2-7b-hf |
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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 39mins 4secs for 1 epoch using an A6000 48GB GPU. |
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- Costed `$1.313` for the entire epoch. |
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#### Hyperparameters & Additional Details: |
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- **Epochs:** 1 |
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- **Cost Per Epoch:** $1.313 |
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- **Total Finetuning Cost:** $1.313 |
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- **Model Path:** meta-llama/Llama-2-7b-hf |
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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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- **lora r:** 32 |
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- **lora alpha:** 64 |
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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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Train loss : |
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![eval loss](https://cdn-uploads.huggingface.co/production/uploads/63ba46aa0a9866b28cb19a14/D84FFl8hAorzJbtSfiiIT.png) |
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license: apache-2.0 |