Finetuning Overview:
Model Used: EleutherAI/gpt-j-6b
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's LLM finetuner, this finetuning:
- Was achieved with great cost-effectiveness.
- Completed in a total duration of 9hrs 45mins for 1 epoch.
Hyperparameters & Additional Details:
- Epochs: 1
- Model Path: EleutherAI/gpt-j-6b
- Learning Rate: 0.0002
- Data Split: 90% train 10% validation
- Gradient Accumulation Steps: 4
### INSTRUCTION:
[instruction]
### RESPONSE:
[output]
Training loss :
license: apache-2.0
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Model tree for monsterapi/gptj_6b_WizardLMEvolInstruct70k
Base model
EleutherAI/gpt-j-6b
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-j-6b") model = PeftModel.from_pretrained(base_model, "monsterapi/gptj_6b_WizardLMEvolInstruct70k")