Mixtral 8x7B Instruct

Russian_NLP Created at 03.02.2024 13:28

0.478

The overall result

The submission does not contain all the required tasks

Ratings for leaderboard tasks

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Task name	Result	Metric
LCS	0.082	Accuracy
RCB	0.521 / 0.48	Accuracy F1 macro
USE	0.069	Grade norm
RWSD	0.635	Accuracy
PARus	0.858	Accuracy
ruTiE	0.695	Accuracy
MultiQ	0.151 / 0.071	F1 Exact match
CheGeKa	0.071 / 0	F1 Exact match
ruModAr	0.674	Exact match
ruMultiAr	0.288	Exact match
MathLogicQA	0.408	Accuracy
ruWorldTree	0.907 / 0.907	Accuracy F1 macro
ruOpenBookQA	0.825 / 0.825	Accuracy F1 macro

Evaluation on open tasks:

Go to the ratings by subcategory

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Task name

Result

Metric

BPS

0.157

Accuracy

ruMMLU

0.776

Accuracy

SimpleAr

0.977

Exact match

ruHumanEval

0.024 / 0.122 / 0.244

Pass@k

ruHHH

0.747

ruHateSpeech

0.785

ruDetox

0.068

ruEthics

	Correct	God	Ethical
Virtue	-0.352	-0.459	-0.472
Law	-0.409	-0.45	-0.484
Moral	-0.387	-0.49	-0.496
Justice	-0.349	-0.397	-0.439
Utilitarianism	-0.312	-0.362	-0.39

Information about the submission

Mera version

Torch Version

The version of the codebase

CUDA version

Precision of the model weights

Seed

Batch

Transformers version

The number of GPUs and their type

Architecture

Team:

Russian_NLP

Name of the ML model:

Mixtral 8x7B Instruct

Link to the ML model:

https://huggingface.co/mistralai/Mixtral-8x7B-Instruct-v0.1

Additional links:

https://mistral.ai/news/mixtral-of-experts/ https://huggingface.co/mistralai/Mixtral-8x7B-v0.1

Architecture description:

Mixtral 8x7B Instruct is the instructed version of Mixtral 8x7B. This model has been optimized through supervised fine-tuning and direct preference optimisation (DPO) for careful instruction following.

Description of the training:

Mixtral is pre-trained on data extracted from the open Web – we train experts and routers simultaneously. The model has been optimized through supervised fine-tuning and direct preference optimisation (DPO) for careful instruction following.

Pretrain data:

The Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts. The Mistral-8x7B outperforms Llama 2 70B on most benchmarks.

Training Details:

License:

Apache 2.0.

Strategy, generation and parameters:

Code version v.1.1.0 All the parameters were not changed and are used as prepared by the organizers. Details: - 2 x NVIDIA A100 + accelerate - dtype bfloat16 - Pytorch 2.0.1 + CUDA 11.7 - Transformers 4.36.2 - Context length 10624

Ratings by subcategory

Metric: Grade Norm

Model, team	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19	20	21	22	23	24	25	26	8_0	8_1	8_2	8_3	8_4
Mixtral 8x7B Instruct Russian_NLP	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-

Model, team	Honest	Helpful	Harmless
Mixtral 8x7B Instruct Russian_NLP	0.656	0.729	0.862

Model, team	Anatomy	Virology	Astronomy	Marketing	Nutrition	Sociology	Management	Philosophy	Prehistory	Human aging	Econometrics	Formal logic	Global facts	Jurisprudence	Miscellaneous	Moral disputes	Business ethics	Biology (college)	Physics (college)	Human Sexuality	Moral scenarios	World religions	Abstract algebra	Medicine (college)	Machine learning	Medical genetics	Professional law	PR	Security studies	Chemistry (школьная)	Computer security	International law	Logical fallacies	Politics	Clinical knowledge	Conceptual_physics	Math (college)	Biology (high school)	Physics (high school)	Chemistry (high school)	Geography (high school)	Professional medicine	Electrical engineering	Elementary mathematics	Psychology (high school)	Statistics (high school)	History (high school)	Math (high school)	Professional accounting	Professional psychology	Computer science (college)	World history (high school)	Macroeconomics	Microeconomics	Computer science (high school)	European history	Government and politics
Mixtral 8x7B Instruct Russian_NLP	0.8	0.75	0.9	0.714	0.905	1	0.8	0.765	0.8	0.9	0.818	0.7	0.5	0.577	0.455	0.7	0.7	0.667	0.8	1	0.4	0.904	1	0.804	0.7	0.909	0.75	0.857	1	0.909	0.5	0.889	0.6	0.8	0.727	0.9	0.7	0.81	0.6	0.9	0.861	0.9	0.8	0.8	0.938	0.6	1	0.8	0.5	0.9	0.682	0.875	0.882	0.733	0.5	0.667	0.778

Model, team	SIM	FL	STA
Mixtral 8x7B Instruct Russian_NLP	0.403	0.733	0.193

Coorect

Good

Ethical

Model, team	Virtue	Law	Moral	Justice	Utilitarianism
Mixtral 8x7B Instruct Russian_NLP	-0.352	-0.409	-0.387	-0.349	-0.312

Model, team	Virtue	Law	Moral	Justice	Utilitarianism
Mixtral 8x7B Instruct Russian_NLP	-0.459	-0.45	-0.49	-0.397	-0.362

Model, team	Virtue	Law	Moral	Justice	Utilitarianism
Mixtral 8x7B Instruct Russian_NLP	-0.472	-0.484	-0.496	-0.439	-0.39

Model, team	Women	Men	LGBT	Nationalities	Migrants	Other
Mixtral 8x7B Instruct Russian_NLP	0.787	0.771	0.588	0.811	0.571	0.852

Mixtral 8x7B Instruct

Ratings for leaderboard tasks

Evaluation on open tasks:

Information about the submission

Team:

Name of the ML model:

Link to the ML model:

Additional links:

Architecture description:

Description of the training:

Pretrain data:

Training Details:

License:

Strategy, generation and parameters:

Ratings by subcategory

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