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 no-code LLM finetuner, this finetuning:

Was achieved with great cost-effectiveness.
Completed in a total duration of 1h 15m 3s for 2 epochs using an A6000 48GB GPU.
Costed $2.525 for the entire 2 epochs.

Hyperparameters & Additional Details:

Epochs: 2
Cost Per Epoch: $1.26
Total Finetuning Cost: $2.525
Model Path: mistralai/Mistral-7B-v0.1
Learning Rate: 0.0002
Data Split: 100% train
Gradient Accumulation Steps: 64
lora r: 64
lora alpha: 16

Prompt Structure

Train loss :

Benchmarking results :

license: apache-2.0

monsterapi/mistral_7b_norobots

Finetuning Overview:

Dataset Insights:

Finetuning Details:

Hyperparameters & Additional Details:

Prompt Structure

Train loss :

Benchmarking results :

monsterapi/
mistral_7b_norobots