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