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---
library_name: peft
tags:
- meta-llama
- code
- instruct
- WizardLM
- Mistral-7B-v0.1
datasets:
- WizardLM/WizardLM_evol_instruct_70k
base_model: HuggingFaceH4/zephyr-7b-alpha
license: apache-2.0
---
### Finetuning Overview:
**Model Used:** HuggingFaceH4/zephyr-7b-alpha
**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 5hrs 18mins for 1 epoch using an A6000 48GB GPU.
- Costed `$10` for the entire epoch.
#### Hyperparameters & Additional Details:
- **Epochs:** 1
- **Cost Per Epoch:** $10.5
- **Total Finetuning Cost:** $10.5
- **Model Path:** HuggingFaceH4/zephyr-7b-alpha
- **Learning Rate:** 0.0002
- **Data Split:** 90% train 10% validation
- **Gradient Accumulation Steps:** 4
---
Prompt Structure
```
### INSTRUCTION:
[instruction]
### RESPONSE:
[output]
```
Training loss :
---
license: apache-2.0
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