chaiml-mistral-nemo-dpo-_4706

developer_uid: azuruce

submission_id: chaiml-mistral-nemo-dpo-_4706_v1

model_name: chaiml-mistral-nemo-dpo-_4706_v1

model_group: ChaiML/mistral_nemo_dpo_

status: inactive

timestamp: 2024-12-19T15:57:53+00:00

num_battles: 13110

num_wins: 6511

celo_rating: 1261.1

family_friendly_score: 0.5788

family_friendly_standard_error: 0.006982700910106346

submission_type: basic

model_repo: ChaiML/mistral_nemo_dpo_241217_albert_v1-checkpoint-5928

model_architecture: MistralForCausalLM

model_num_parameters: 12772070400.0

best_of: 4

max_input_tokens: 1024

max_output_tokens: 64

latencies: [{'batch_size': 1, 'throughput': 0.6358743600028948, 'latency_mean': 1.572563591003418, 'latency_p50': 1.5666050910949707, 'latency_p90': 1.7246995449066163}, {'batch_size': 3, 'throughput': 1.2700107865123154, 'latency_mean': 2.348499997854233, 'latency_p50': 2.349436402320862, 'latency_p90': 2.630470108985901}, {'batch_size': 5, 'throughput': 1.6183578174300852, 'latency_mean': 3.0768230104446412, 'latency_p50': 3.067487597465515, 'latency_p90': 3.504495906829834}, {'batch_size': 6, 'throughput': 1.7269375234019306, 'latency_mean': 3.4530131232738497, 'latency_p50': 3.4100688695907593, 'latency_p90': 3.917102909088135}, {'batch_size': 8, 'throughput': 1.885586714640626, 'latency_mean': 4.209317348003387, 'latency_p50': 4.225842833518982, 'latency_p90': 4.696979975700378}, {'batch_size': 10, 'throughput': 1.9817451738428815, 'latency_mean': 5.0106280839443205, 'latency_p50': 5.03821861743927, 'latency_p90': 5.636007332801819}]

gpu_counts: {'NVIDIA RTX A5000': 1}

display_name: chaiml-mistral-nemo-dpo-_4706_v1

is_internal_developer: True

language_model: ChaiML/mistral_nemo_dpo_241217_albert_v1-checkpoint-5928

model_size: 13B

ranking_group: single

throughput_3p7s: 1.8

us_pacific_date: 2024-12-19

win_ratio: 0.49664378337147214

generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 100, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '</s>', '####', 'Bot:', 'User:', 'You:', '<|im_end|>', '<|eot_id|>'], 'max_input_tokens': 1024, 'best_of': 4, 'max_output_tokens': 64}

formatter: {'memory_template': '', 'prompt_template': '', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '{bot_name}:', 'truncate_by_message': False}

Resubmit model

Shutdown handler not registered because Python interpreter is not running in the main thread
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name chaiml-mistral-nemo-dpo-4706-v1-mkmlizer
Waiting for job on chaiml-mistral-nemo-dpo-4706-v1-mkmlizer to finish
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║     _____            __           __                                ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║       /___/                                                         ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║                                                                     ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║  Version: 0.11.12                                                   ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║  https://mk1.ai                                                     ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║                                                                     ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║  belonging to:                                                      ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║                                                                     ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║  Chai Research Corp.                                                ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║  Expiration: 2025-01-15 23:59:59                                    ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ║                                                                     ║
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: Downloaded to shared memory in 40.962s
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp2onujg5k, device:0
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: quantized model in 36.750s
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: Processed model ChaiML/mistral_nemo_dpo_241217_albert_v1-checkpoint-5928 in 77.712s
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: creating bucket guanaco-mkml-models
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-mistral-nemo-dpo-4706-v1
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-mistral-nemo-dpo-4706-v1/config.json
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-mistral-nemo-dpo-4706-v1/special_tokens_map.json
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-mistral-nemo-dpo-4706-v1/tokenizer_config.json
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-mistral-nemo-dpo-4706-v1/tokenizer.json
chaiml-mistral-nemo-dpo-4706-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-mistral-nemo-dpo-4706-v1/flywheel_model.0.safetensors
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Job chaiml-mistral-nemo-dpo-4706-v1-mkmlizer completed after 105.57s with status: succeeded
Stopping job with name chaiml-mistral-nemo-dpo-4706-v1-mkmlizer
Pipeline stage MKMLizer completed in 106.22s
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Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.18s
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Running pipeline stage MKMLDeployer
Creating inference service chaiml-mistral-nemo-dpo-4706-v1
Waiting for inference service chaiml-mistral-nemo-dpo-4706-v1 to be ready
Inference service chaiml-mistral-nemo-dpo-4706-v1 ready after 240.8543803691864s
Pipeline stage MKMLDeployer completed in 241.44s
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Running pipeline stage StressChecker
Received healthy response to inference request in 1.756883144378662s
Received healthy response to inference request in 0.7132151126861572s
Received healthy response to inference request in 1.234480857849121s
Received healthy response to inference request in 1.1594321727752686s
Received healthy response to inference request in 1.9784486293792725s
5 requests
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5th percentile: 0.8024585247039795
10th percentile: 0.8917019367218018
20th percentile: 1.0701887607574463
30th percentile: 1.1744419097900392
40th percentile: 1.2044613838195801
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50th percentile: 1.234480857849121
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70th percentile: 1.6524026870727537
80th percentile: 1.8011962413787843
90th percentile: 1.8898224353790283
95th percentile: 1.9341355323791503
99th percentile: 1.969586009979248
mean time: 1.3684919834136964
Pipeline stage StressChecker completed in 8.26s
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Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
Pipeline stage OfflineFamilyFriendlyScorer completed in 2984.11s
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chaiml-mistral-nemo-dpo-_4706_v1 status is now inactive due to auto deactivation removed underperforming models