chaiml-cs-feed-score-v3_82897

developer_uid: chai_backend_admin

submission_id: chaiml-cs-feed-score-v3_82897_v2

model_name: chaiml-cs-feed-score-v3_82897_v2

model_group: ChaiML/cs-feed-score-v3-

status: inactive

timestamp: 2025-10-14T05:30:49+00:00

num_battles: 5466

num_wins: 2924

celo_rating: 1301.32

family_friendly_score: 0.5142

family_friendly_standard_error: 0.0070682156164056

submission_type: basic

model_repo: ChaiML/cs-feed-score-v3-dpo-test

model_architecture: MistralForCausalLM

model_num_parameters: 24096691200.0

best_of: 8

max_input_tokens: 2048

max_output_tokens: 64

reward_model: default

latencies: [{'batch_size': 1, 'throughput': 0.3827872429153936, 'latency_mean': 2.612316988706589, 'latency_p50': 2.603481888771057, 'latency_p90': 2.868465971946716}, {'batch_size': 2, 'throughput': 0.5786161592928616, 'latency_mean': 3.4491811847686766, 'latency_p50': 3.445620894432068, 'latency_p90': 3.7539142370224}, {'batch_size': 3, 'throughput': 0.7168318858933385, 'latency_mean': 4.172994199991226, 'latency_p50': 4.155544638633728, 'latency_p90': 4.782274866104125}, {'batch_size': 4, 'throughput': 0.818226508618976, 'latency_mean': 4.869705797433853, 'latency_p50': 4.865781784057617, 'latency_p90': 5.5331285953521725}, {'batch_size': 5, 'throughput': 0.8775059542565472, 'latency_mean': 5.677266147136688, 'latency_p50': 5.7316659688949585, 'latency_p90': 6.457981038093567}]

gpu_counts: {'NVIDIA L40S': 1}

display_name: chaiml-cs-feed-score-v3_82897_v2

is_internal_developer: True

language_model: ChaiML/cs-feed-score-v3-dpo-test

model_size: 24B

ranking_group: single

throughput_3p7s: 0.63

us_pacific_date: 2025-10-13

win_ratio: 0.5349432857665569

generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['####', '\n', 'You:', '</s>'], 'max_input_tokens': 2048, 'best_of': 8, 'max_output_tokens': 64}

formatter: {'memory_template': "{bot_name}'s persona: {memory}", 'prompt_template': '', 'bot_template': '{bot_name}: {message}\n', 'user_template': 'You: {message}\n', 'response_template': '####\n{bot_name}:', 'truncate_by_message': True}

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-cs-feed-score-v3-82897-v2-mkmlizer
Waiting for job on chaiml-cs-feed-score-v3-82897-v2-mkmlizer to finish
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║                                                                     ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║   ░███░░███ ░███   ░███████      ░███                               ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║   ░███ ░░░  ░███   ░███░░███     ░███                               ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║                                                                     ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║  Version: 0.30.2                                                    ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║  https://mk1.ai                                                     ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║                                                                     ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║  The license key for the current software has been verified as      ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║  belonging to:                                                      ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║                                                                     ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║  Chai Research Corp.                                                ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ║                                                                     ║
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: Downloaded to shared memory in 49.758s
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: Checking if ChaiML/cs-feed-score-v3-dpo-test already exists in ChaiML
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpxy1733c2, device:0
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: quantized model in 41.847s
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: Processed model ChaiML/cs-feed-score-v3-dpo-test in 91.606s
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: creating bucket guanaco-mkml-models
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-cs-feed-score-v3-82897-v2/nvidia
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-cs-feed-score-v3-82897-v2/nvidia/config.json
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-cs-feed-score-v3-82897-v2/nvidia/special_tokens_map.json
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-cs-feed-score-v3-82897-v2/nvidia/tokenizer_config.json
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-cs-feed-score-v3-82897-v2/nvidia/tokenizer.json
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.1.safetensors s3://guanaco-mkml-models/chaiml-cs-feed-score-v3-82897-v2/nvidia/flywheel_model.1.safetensors
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-cs-feed-score-v3-82897-v2/nvidia/flywheel_model.0.safetensors
chaiml-cs-feed-score-v3-82897-v2-mkmlizer: 
Loading 0:   0%|          | 0/363 [00:00<?, ?it/s]
Loading 0:   1%|▏         | 5/363 [00:00<00:15, 23.27it/s]
Loading 0:   4%|▎         | 13/363 [00:00<00:08, 39.79it/s]
Loading 0:   5%|▌         | 19/363 [00:00<00:08, 40.87it/s]
Loading 0:   7%|▋         | 24/363 [00:00<00:09, 35.51it/s]
Loading 0:   9%|▉         | 32/363 [00:00<00:07, 45.18it/s]
Loading 0:  10%|█         | 37/363 [00:01<00:10, 30.07it/s]
Loading 0:  11%|█▏        | 41/363 [00:01<00:11, 27.32it/s]
Loading 0:  13%|█▎        | 48/363 [00:01<00:09, 34.89it/s]
Loading 0:  15%|█▍        | 53/363 [00:01<00:09, 33.86it/s]
Loading 0:  16%|█▌        | 58/363 [00:01<00:08, 34.44it/s]
Loading 0:  17%|█▋        | 62/363 [00:01<00:08, 35.14it/s]
Loading 0:  18%|█▊        | 67/363 [00:01<00:07, 38.36it/s]
Loading 0:  20%|█▉        | 72/363 [00:02<00:09, 29.48it/s]
Loading 0:  21%|██        | 76/363 [00:02<00:09, 30.08it/s]
Loading 0:  22%|██▏       | 80/363 [00:02<00:10, 27.31it/s]
Loading 0:  24%|██▎       | 86/363 [00:02<00:08, 33.02it/s]
Loading 0:  25%|██▍       | 90/363 [00:02<00:08, 31.81it/s]
Loading 0:  26%|██▌       | 94/363 [00:02<00:08, 30.66it/s]
Loading 0:  27%|██▋       | 99/363 [00:02<00:07, 34.03it/s]
Loading 0:  28%|██▊       | 103/363 [00:03<00:08, 32.27it/s]
Loading 0:  29%|██▉       | 107/363 [00:03<00:09, 27.35it/s]
Loading 0:  31%|███       | 112/363 [00:03<00:08, 30.27it/s]
Loading 0:  32%|███▏      | 116/363 [00:03<00:07, 31.14it/s]
Loading 0:  33%|███▎      | 121/363 [00:03<00:07, 32.23it/s]
Loading 0:  34%|███▍      | 125/363 [00:03<00:07, 32.37it/s]
Loading 0:  36%|███▌      | 129/363 [00:03<00:06, 34.07it/s]
Loading 0:  37%|███▋      | 133/363 [00:04<00:07, 32.25it/s]
Loading 0:  38%|███▊      | 138/363 [00:04<00:06, 35.63it/s]
Loading 0:  39%|███▉      | 142/363 [00:04<00:06, 32.42it/s]
Loading 0:  41%|████      | 149/363 [00:04<00:05, 38.64it/s]
Loading 0:  42%|████▏     | 153/363 [00:04<00:08, 25.23it/s]
Loading 0:  44%|████▎     | 158/363 [00:04<00:08, 25.18it/s]
Loading 0:  45%|████▌     | 165/363 [00:05<00:06, 32.32it/s]
Loading 0:  47%|████▋     | 169/363 [00:05<00:06, 31.44it/s]
Loading 0:  48%|████▊     | 174/363 [00:05<00:05, 34.51it/s]
Loading 0:  49%|████▉     | 178/363 [00:05<00:05, 32.85it/s]
Loading 0:  50%|█████     | 182/363 [00:05<00:05, 33.51it/s]
Loading 0:  52%|█████▏    | 187/363 [00:05<00:05, 30.62it/s]
Loading 0:  53%|█████▎    | 191/363 [00:05<00:05, 29.90it/s]
Loading 0:  54%|█████▎    | 195/363 [00:06<00:06, 26.74it/s]
Loading 0:  55%|█████▌    | 201/363 [00:19<02:13,  1.21it/s]
Loading 0:  56%|█████▌    | 203/363 [00:19<01:54,  1.40it/s]
Loading 0:  57%|█████▋    | 208/363 [00:19<01:13,  2.12it/s]
Loading 0:  58%|█████▊    | 212/363 [00:19<00:53,  2.82it/s]
Loading 0:  60%|██████    | 218/363 [00:19<00:32,  4.40it/s]
Loading 0:  61%|██████    | 222/363 [00:19<00:24,  5.74it/s]
Loading 0:  62%|██████▏   | 226/363 [00:20<00:19,  7.05it/s]
Loading 0:  63%|██████▎   | 230/363 [00:20<00:15,  8.68it/s]
Loading 0:  65%|██████▌   | 237/363 [00:20<00:09, 13.43it/s]
Loading 0:  66%|██████▋   | 241/363 [00:20<00:07, 15.55it/s]
Loading 0:  68%|██████▊   | 246/363 [00:20<00:06, 19.50it/s]
Loading 0:  69%|██████▉   | 250/363 [00:20<00:05, 21.13it/s]
Loading 0:  70%|███████   | 255/363 [00:20<00:04, 25.43it/s]
Loading 0:  71%|███████▏  | 259/363 [00:20<00:03, 26.03it/s]
Loading 0:  73%|███████▎  | 266/363 [00:21<00:02, 33.04it/s]
Loading 0:  75%|███████▍  | 271/363 [00:21<00:03, 24.87it/s]
Loading 0:  76%|███████▌  | 275/363 [00:21<00:03, 23.43it/s]
Loading 0:  78%|███████▊  | 282/363 [00:21<00:02, 30.48it/s]
Loading 0:  79%|███████▉  | 286/363 [00:21<00:02, 29.82it/s]
Loading 0:  80%|████████  | 291/363 [00:22<00:02, 33.06it/s]
Loading 0:  81%|████████▏ | 295/363 [00:22<00:02, 31.57it/s]
Loading 0:  82%|████████▏ | 299/363 [00:22<00:01, 32.39it/s]
Loading 0:  84%|████████▎ | 304/363 [00:22<00:01, 29.62it/s]
Loading 0:  85%|████████▍ | 308/363 [00:22<00:01, 29.16it/s]
Loading 0:  86%|████████▌ | 312/363 [00:22<00:01, 26.40it/s]
Loading 0:  88%|████████▊ | 318/363 [00:22<00:01, 32.20it/s]
Loading 0:  89%|████████▊ | 322/363 [00:23<00:01, 31.25it/s]
Loading 0:  90%|█████████ | 327/363 [00:23<00:01, 34.64it/s]
Loading 0:  91%|█████████ | 331/363 [00:23<00:01, 31.78it/s]
Loading 0:  92%|█████████▏| 335/363 [00:23<00:00, 32.59it/s]
Loading 0:  93%|█████████▎| 339/363 [00:23<00:00, 33.55it/s]
Loading 0:  94%|█████████▍| 343/363 [00:23<00:00, 20.34it/s]
Loading 0:  96%|█████████▌| 348/363 [00:24<00:00, 21.99it/s]
Loading 0:  98%|█████████▊| 355/363 [00:24<00:00, 29.51it/s]
Loading 0:  99%|█████████▉| 359/363 [00:24<00:00, 23.02it/s]
                                                            
Job chaiml-cs-feed-score-v3-82897-v2-mkmlizer completed after 164.09s with status: succeeded
Stopping job with name chaiml-cs-feed-score-v3-82897-v2-mkmlizer
Pipeline stage MKMLizer completed in 164.59s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.37s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service chaiml-cs-feed-score-v3-82897-v2
Waiting for inference service chaiml-cs-feed-score-v3-82897-v2 to be ready
Inference service chaiml-cs-feed-score-v3-82897-v2 ready after 60.22399306297302s
Pipeline stage MKMLDeployer completed in 60.62s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.4865825176239014s
Received healthy response to inference request in 2.16981840133667s
Received healthy response to inference request in 2.1668004989624023s
Received healthy response to inference request in 2.0839571952819824s
Received healthy response to inference request in 2.1385867595672607s
5 requests
0 failed requests
5th percentile: 2.094883108139038
10th percentile: 2.1058090209960936
20th percentile: 2.127660846710205
30th percentile: 2.144229507446289
40th percentile: 2.1555150032043455
50th percentile: 2.1668004989624023
60th percentile: 2.168007659912109
70th percentile: 2.1692148208618165
80th percentile: 2.233171224594116
90th percentile: 2.359876871109009
95th percentile: 2.423229694366455
99th percentile: 2.4739119529724123
mean time: 2.2091490745544435
Pipeline stage StressChecker completed in 12.16s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyTriggerPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
triggered trigger_guanaco_pipeline args=%s
Pipeline stage OfflineFamilyFriendlyTriggerPipeline completed in 0.59s
run pipeline stage %s
Running pipeline stage TriggerMKMLProfilingPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
triggered trigger_guanaco_pipeline args=%s
Pipeline stage TriggerMKMLProfilingPipeline completed in 0.71s
Shutdown handler de-registered
chaiml-cs-feed-score-v3_82897_v2 status is now deployed due to DeploymentManager action
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLProfilerDeleter completed in 0.12s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.08s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service chaiml-cs-feed-score-v3-82897-v2-profiler
Waiting for inference service chaiml-cs-feed-score-v3-82897-v2-profiler to be ready
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
Pipeline stage OfflineFamilyFriendlyScorer completed in 2812.05s
Shutdown handler de-registered
chaiml-cs-feed-score-v3_82897_v2 status is now inactive due to auto deactivation removed underperforming models