metadata
library_name: transformers
tags:
- code
- instruct
- llama2
datasets:
- Zangs3011/no_robots_FalconChatFormated
base_model: llama/Llama-2-7b-hf
license: apache-2.0
Finetuning Overview:
Model Used: llama/Llama-2-7b-hf Dataset: Zangs3011/no_robots_FalconChatFormated
Dataset Insights:
The WizardLM/WizardLM_evol_instruct_70k dataset, tailored specifically for enhancing interactive capabilities, it was developed using EVOL-Instruct method.Which will basically enhance a smaller dataset, with tougher quesitons for the LLM to perform
Finetuning Details:
With the utilization of MonsterAPI's LLM finetuner, this finetuning:
- Was achieved with great cost-effectiveness.
- Completed in a total duration of 39mins 4secs for 1 epoch using an A6000 48GB GPU.
- Costed
$1.313for the entire epoch.
Hyperparameters & Additional Details:
- Epochs: 1
- Cost Per Epoch: $1.313
- Total Finetuning Cost: $1.313
- Model Path: llama/Llama-2-7b-hf
- Learning Rate: 0.0002
- Data Split: 99% train 1% validation
- Gradient Accumulation Steps: 4
Prompt Structure
### INSTRUCTION:
[instruction]
### RESPONSE:
[text]
Eval loss :
license: apache-2.0