No Robots is a high-quality dataset of 10,000 instructions and demonstrations created by skilled human annotators. This data can be used for supervised fine-tuning (SFT) to make language models follow instructions better.

Finetuning Details:

With the utilization of MonsterAPI's LLM finetuner, this finetuning:

Was achieved with great cost-effectiveness.
Completed in a total duration of 36mins 47secs for 1 epoch using an A6000 48GB GPU.
Costed $1.212 for the entire epoch.

Hyperparameters & Additional Details:

Epochs: 1
Cost Per Epoch: $1.212
Total Finetuning Cost: $1.212
Model Path: HuggingFaceH4/zephyr-7b-alpha
Learning Rate: 0.0002
Data Split: 100% train
Gradient Accumulation Steps: 4
lora r: 32
lora alpha: 64

Prompt Structure

Train loss :

license: apache-2.0

monsterapi/zephyr_7b_norobots

Finetuning Overview:

Dataset Insights:

Finetuning Details:

Hyperparameters & Additional Details:

Prompt Structure

Train loss :

monsterapi/
zephyr_7b_norobots