| --- |
| library_name: peft |
| tags: |
| - meta-llama |
| - code |
| - instruct |
| - WizardLM |
| datasets: |
| - WizardLM/WizardLM_evol_instruct_70k |
| base_model: meta-llama/Llama-2-7b-hf |
| license: apache-2.0 |
| --- |
| |
| ### Finetuning Overview: |
|
|
| **Model Used:** meta-llama/Llama-2-7b-hf |
| **Dataset:** WizardLM/WizardLM_evol_instruct_70k |
| |
| #### Dataset Insights: |
| |
| The WizardLM/WizardLM_evol_instruct_70k dataset, tailored specifically for enhancing interactive capabilities, was developed using the EVOL-Instruct method. This method enhances a smaller dataset with tougher questions for the LLM to perform. |
|
|
| #### Finetuning Details: |
|
|
| With the utilization of [MonsterAPI](https://monsterapi.ai)'s [LLM finetuner](https://docs.monsterapi.ai/fine-tune-a-large-language-model-llm), this finetuning: |
|
|
| - Was achieved with great cost-effectiveness. |
| - Completed in a total duration of 6hrs 48mins for 1 epoch. |
|
|
| #### Hyperparameters & Additional Details: |
|
|
| - **Epochs:** 1 |
| - **Model Path:** meta-llama/Llama-2-7b-hf |
| - **Learning Rate:** 0.0002 |
| - **Data Split:** 90% train 10% validation |
| - **Gradient Accumulation Steps:** 4 |
|
|
| ``` |
| |
| ### INSTRUCTION: |
| [instruction] |
| |
| ### RESPONSE: |
| [output] |
| ``` |
| Training loss : |
|  |
|
|
| --- |
|
|
| license: apache-2.0 |
|
|
