alexdaoud-trainer-bagir-_4107

developer_uid: chai_backend_admin
submission_id: alexdaoud-trainer-bagir-_4107_v1
model_name: alexdaoud-trainer-bagir-_4107_v1
model_group: alexdaoud/trainer_bagir_
status: inactive
timestamp: 2024-12-16T17:46:07+00:00
num_battles: 39366
num_wins: 19978
celo_rating: 1268.22
family_friendly_score: 0.5778
family_friendly_standard_error: 0.006984943235273999
submission_type: basic
model_repo: alexdaoud/trainer_bagir_2024-12-11-checkpoint-65
model_architecture: LlamaForSequenceClassification
model_num_parameters: 8030261248.0
best_of: 1
max_input_tokens: 256
max_output_tokens: 1
display_name: alexdaoud-trainer-bagir-_4107_v1
ineligible_reason: max_output_tokens!=64
is_internal_developer: True
language_model: alexdaoud/trainer_bagir_2024-12-11-checkpoint-65
model_size: 8B
ranking_group: single
us_pacific_date: 2024-12-16
win_ratio: 0.5074937763552304
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'], 'max_input_tokens': 256, 'best_of': 1, 'max_output_tokens': 1}
formatter: {'memory_template': '', 'prompt_template': '', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '', '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 alexdaoud-trainer-bagir-4107-v1-mkmlizer
Waiting for job on alexdaoud-trainer-bagir-4107-v1-mkmlizer to finish
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║     _____            __           __                                ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║       /___/                                                         ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║  Version: 0.11.12                                                   ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║  https://mk1.ai                                                     ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║  belonging to:                                                      ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║  Chai Research Corp.                                                ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║  Expiration: 2025-01-15 23:59:59                                    ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-4107-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
alexdaoud-trainer-bagir-4107-v1-mkmlizer: Downloaded to shared memory in 30.584s
alexdaoud-trainer-bagir-4107-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:t0, folder:/tmp/tmp_85ygl_6, device:0
alexdaoud-trainer-bagir-4107-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
alexdaoud-trainer-bagir-4107-v1-mkmlizer: quantized model in 85.337s
alexdaoud-trainer-bagir-4107-v1-mkmlizer: Processed model alexdaoud/trainer_bagir_2024-12-11-checkpoint-65 in 115.922s
alexdaoud-trainer-bagir-4107-v1-mkmlizer: creating bucket guanaco-mkml-models
alexdaoud-trainer-bagir-4107-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
alexdaoud-trainer-bagir-4107-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/alexdaoud-trainer-bagir-4107-v1
alexdaoud-trainer-bagir-4107-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-4107-v1/config.json
alexdaoud-trainer-bagir-4107-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-4107-v1/special_tokens_map.json
alexdaoud-trainer-bagir-4107-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-4107-v1/tokenizer.json
alexdaoud-trainer-bagir-4107-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/alexdaoud-trainer-bagir-4107-v1/flywheel_model.0.safetensors
alexdaoud-trainer-bagir-4107-v1-mkmlizer: 
Loading 0:   0%|          | 0/291 [00:00<?, ?it/s]
Loading 0:   1%|          | 3/291 [00:00<00:55,  5.18it/s]
Loading 0:   1%|▏         | 4/291 [00:01<01:30,  3.16it/s]
Loading 0:   2%|▏         | 5/291 [00:01<02:01,  2.35it/s]
Loading 0:   3%|▎         | 8/291 [00:02<01:03,  4.49it/s]
Loading 0:   3%|▎         | 9/291 [00:02<01:02,  4.54it/s]
Loading 0:   3%|▎         | 10/291 [00:02<00:54,  5.19it/s]
Loading 0:   4%|▍         | 12/291 [00:02<01:04,  4.30it/s]
Loading 0:   4%|▍         | 13/291 [00:03<01:26,  3.22it/s]
Loading 0:   5%|▍         | 14/291 [00:04<01:48,  2.55it/s]
Loading 0:   6%|▌         | 17/291 [00:04<01:02,  4.39it/s]
Loading 0:   6%|▌         | 18/291 [00:04<00:58,  4.63it/s]
Loading 0:   7%|▋         | 19/291 [00:04<00:52,  5.23it/s]
Loading 0:   7%|▋         | 21/291 [00:05<01:01,  4.37it/s]
Loading 0:   8%|▊         | 22/291 [00:05<01:21,  3.29it/s]
Loading 0:   8%|▊         | 23/291 [00:06<01:43,  2.59it/s]
Loading 0:   9%|▉         | 26/291 [00:06<01:00,  4.40it/s]
Loading 0:   9%|▉         | 27/291 [00:06<00:57,  4.63it/s]
Loading 0:  10%|▉         | 28/291 [00:06<00:51,  5.16it/s]
Loading 0:  10%|█         | 30/291 [00:07<01:00,  4.34it/s]
Loading 0:  11%|█         | 31/291 [00:08<01:19,  3.28it/s]
Loading 0:  11%|█         | 32/291 [00:08<01:40,  2.58it/s]
Loading 0:  12%|█▏        | 35/291 [00:08<00:58,  4.39it/s]
Loading 0:  12%|█▏        | 36/291 [00:09<00:55,  4.63it/s]
Loading 0:  13%|█▎        | 39/291 [00:09<00:55,  4.55it/s]
Loading 0:  14%|█▎        | 40/291 [00:10<01:11,  3.53it/s]
Loading 0:  14%|█▍        | 41/291 [00:11<01:29,  2.78it/s]
Loading 0:  15%|█▌        | 44/291 [00:11<00:55,  4.45it/s]
Loading 0:  15%|█▌        | 45/291 [00:11<00:52,  4.66it/s]
Loading 0:  16%|█▌        | 46/291 [00:11<00:49,  4.99it/s]
Loading 0:  16%|█▋        | 48/291 [00:12<00:56,  4.29it/s]
Loading 0:  17%|█▋        | 49/291 [00:12<01:13,  3.28it/s]
Loading 0:  17%|█▋        | 50/291 [00:13<01:33,  2.59it/s]
Loading 0:  18%|█▊        | 53/291 [00:13<00:54,  4.36it/s]
Loading 0:  19%|█▊        | 54/291 [00:13<00:51,  4.59it/s]
Loading 0:  20%|█▉        | 57/291 [00:14<00:51,  4.52it/s]
Loading 0:  20%|█▉        | 58/291 [00:15<01:06,  3.52it/s]
Loading 0:  20%|██        | 59/291 [00:15<01:22,  2.81it/s]
Loading 0:  21%|██▏       | 62/291 [00:15<00:51,  4.47it/s]
Loading 0:  22%|██▏       | 63/291 [00:16<00:48,  4.67it/s]
Loading 0:  22%|██▏       | 64/291 [00:16<00:43,  5.22it/s]
Loading 0:  23%|██▎       | 66/291 [00:16<00:51,  4.39it/s]
Loading 0:  23%|██▎       | 67/291 [00:17<01:07,  3.32it/s]
Loading 0:  23%|██▎       | 68/291 [00:17<01:25,  2.60it/s]
Loading 0:  24%|██▍       | 71/291 [00:18<00:50,  4.38it/s]
Loading 0:  25%|██▍       | 72/291 [00:18<00:47,  4.61it/s]
Loading 0:  25%|██▌       | 73/291 [00:18<00:42,  5.10it/s]
Loading 0:  26%|██▌       | 75/291 [00:19<00:49,  4.33it/s]
Loading 0:  26%|██▌       | 76/291 [00:19<01:05,  3.29it/s]
Loading 0:  26%|██▋       | 77/291 [00:20<01:22,  2.61it/s]
Loading 0:  27%|██▋       | 80/291 [00:20<00:47,  4.41it/s]
Loading 0:  28%|██▊       | 81/291 [00:20<00:45,  4.64it/s]
Loading 0:  28%|██▊       | 82/291 [00:20<00:40,  5.22it/s]
Loading 0:  29%|██▊       | 83/291 [00:20<00:40,  5.13it/s]
Loading 0:  29%|██▉       | 84/291 [00:21<01:00,  3.44it/s]
Loading 0:  29%|██▉       | 85/291 [00:22<01:15,  2.73it/s]
Loading 0:  30%|██▉       | 86/291 [00:22<01:30,  2.26it/s]
Loading 0:  31%|███       | 89/291 [00:22<00:48,  4.21it/s]
Loading 0:  31%|███       | 90/291 [00:23<00:44,  4.48it/s]
Loading 0:  31%|███▏      | 91/291 [00:23<00:39,  5.11it/s]
Loading 0:  32%|███▏      | 93/291 [00:23<00:46,  4.30it/s]
Loading 0:  32%|███▏      | 94/291 [00:24<01:00,  3.25it/s]
Loading 0:  33%|███▎      | 95/291 [00:24<01:15,  2.58it/s]
Loading 0:  34%|███▎      | 98/291 [00:25<00:43,  4.47it/s]
Loading 0:  34%|███▍      | 99/291 [00:25<00:40,  4.71it/s]
Loading 0:  34%|███▍      | 100/291 [00:25<00:36,  5.29it/s]
Loading 0:  35%|███▌      | 102/291 [00:26<00:42,  4.40it/s]
Loading 0:  35%|███▌      | 103/291 [00:26<00:56,  3.32it/s]
Loading 0:  36%|███▌      | 104/291 [00:27<01:11,  2.61it/s]
Loading 0:  37%|███▋      | 107/291 [00:27<00:40,  4.50it/s]
Loading 0:  37%|███▋      | 108/291 [00:27<00:38,  4.73it/s]
Loading 0:  38%|███▊      | 111/291 [00:28<00:39,  4.61it/s]
Loading 0:  38%|███▊      | 112/291 [00:28<00:50,  3.57it/s]
Loading 0:  39%|███▉      | 113/291 [00:29<01:03,  2.82it/s]
Loading 0:  40%|███▉      | 116/291 [00:29<00:38,  4.52it/s]
Loading 0:  40%|████      | 117/291 [00:29<00:36,  4.74it/s]
Loading 0:  41%|████      | 119/291 [00:29<00:26,  6.41it/s]
Loading 0:  42%|████▏     | 121/291 [00:31<00:49,  3.42it/s]
Loading 0:  42%|████▏     | 122/291 [00:31<01:00,  2.80it/s]
Loading 0:  43%|████▎     | 125/291 [00:31<00:37,  4.41it/s]
Loading 0:  43%|████▎     | 126/291 [00:32<00:35,  4.64it/s]
Loading 0:  44%|████▎     | 127/291 [00:32<00:31,  5.16it/s]
Loading 0:  44%|████▍     | 129/291 [00:32<00:36,  4.38it/s]
Loading 0:  45%|████▍     | 130/291 [00:33<00:48,  3.33it/s]
Loading 0:  45%|████▌     | 131/291 [00:34<01:00,  2.64it/s]
Loading 0:  46%|████▌     | 134/291 [00:34<00:34,  4.49it/s]
Loading 0:  46%|████▋     | 135/291 [00:34<00:33,  4.72it/s]
Loading 0:  47%|████▋     | 136/291 [00:34<00:29,  5.32it/s]
Loading 0:  47%|████▋     | 138/291 [00:35<00:34,  4.43it/s]
Loading 0:  48%|████▊     | 139/291 [00:35<00:45,  3.33it/s]
Loading 0:  48%|████▊     | 140/291 [00:36<00:57,  2.61it/s]
Loading 0:  49%|████▉     | 143/291 [00:36<00:33,  4.47it/s]
Loading 0:  49%|████▉     | 144/291 [00:36<00:31,  4.71it/s]
Loading 0:  50%|████▉     | 145/291 [00:36<00:27,  5.30it/s]
Loading 0:  51%|█████     | 147/291 [00:37<00:32,  4.42it/s]
Loading 0:  51%|█████     | 148/291 [00:37<00:43,  3.32it/s]
Loading 0:  51%|█████     | 149/291 [00:38<00:54,  2.63it/s]
Loading 0:  52%|█████▏    | 152/291 [00:38<00:31,  4.46it/s]
Loading 0:  53%|█████▎    | 153/291 [00:38<00:29,  4.70it/s]
Loading 0:  53%|█████▎    | 154/291 [00:38<00:25,  5.29it/s]
Loading 0:  54%|█████▎    | 156/291 [00:39<00:30,  4.41it/s]
Loading 0:  54%|█████▍    | 157/291 [00:40<00:40,  3.33it/s]
Loading 0:  54%|█████▍    | 158/291 [00:40<00:50,  2.63it/s]
Loading 0:  55%|█████▌    | 161/291 [00:40<00:29,  4.46it/s]
Loading 0:  56%|█████▌    | 162/291 [00:41<00:27,  4.70it/s]
Loading 0:  56%|█████▌    | 163/291 [00:41<00:24,  5.30it/s]
Loading 0:  57%|█████▋    | 165/291 [00:41<00:28,  4.41it/s]
Loading 0:  57%|█████▋    | 166/291 [00:42<00:37,  3.33it/s]
Loading 0:  57%|█████▋    | 167/291 [00:43<00:47,  2.64it/s]
Loading 0:  58%|█████▊    | 170/291 [00:43<00:27,  4.47it/s]
Loading 0:  59%|█████▉    | 171/291 [00:43<00:25,  4.71it/s]
Loading 0:  59%|█████▉    | 172/291 [00:43<00:22,  5.31it/s]
Loading 0:  59%|█████▉    | 173/291 [00:44<00:32,  3.58it/s]
Loading 0:  60%|██████    | 175/291 [00:44<00:23,  4.91it/s]
Loading 0:  60%|██████    | 176/291 [00:44<00:22,  5.13it/s]
Loading 0:  61%|██████    | 177/291 [00:44<00:19,  5.77it/s]
Loading 0:  62%|██████▏   | 179/291 [00:45<00:24,  4.56it/s]
Loading 0:  62%|██████▏   | 180/291 [00:45<00:33,  3.35it/s]
Loading 0:  62%|██████▏   | 181/291 [00:46<00:41,  2.63it/s]
Loading 0:  63%|██████▎   | 184/291 [00:46<00:23,  4.59it/s]
Loading 0:  64%|██████▎   | 185/291 [00:46<00:22,  4.81it/s]
Loading 0:  64%|██████▍   | 186/291 [00:46<00:19,  5.39it/s]
Loading 0:  64%|██████▍   | 187/291 [00:46<00:19,  5.38it/s]
Loading 0:  65%|██████▍   | 188/291 [00:47<00:29,  3.53it/s]
Loading 0:  65%|██████▍   | 189/291 [00:48<00:38,  2.62it/s]
Loading 0:  66%|██████▌   | 192/291 [00:48<00:27,  3.57it/s]
Loading 0:  66%|██████▋   | 193/291 [00:49<00:33,  2.95it/s]
Loading 0:  67%|██████▋   | 194/291 [00:49<00:39,  2.47it/s]
Loading 0:  68%|██████▊   | 197/291 [00:50<00:22,  4.22it/s]
Loading 0:  68%|██████▊   | 198/291 [00:50<00:20,  4.48it/s]
Loading 0:  68%|██████▊   | 199/291 [00:50<00:18,  5.04it/s]
Loading 0:  69%|██████▉   | 201/291 [00:50<00:20,  4.31it/s]
Loading 0:  69%|██████▉   | 202/291 [00:51<00:27,  3.29it/s]
Loading 0:  70%|██████▉   | 203/291 [00:52<00:33,  2.63it/s]
Loading 0:  71%|███████   | 206/291 [00:52<00:19,  4.46it/s]
Loading 0:  71%|███████   | 207/291 [00:52<00:17,  4.70it/s]
Loading 0:  71%|███████▏  | 208/291 [00:52<00:16,  4.94it/s]
Loading 0:  72%|███████▏  | 210/291 [00:53<00:19,  4.26it/s]
Loading 0:  73%|███████▎  | 211/291 [00:53<00:25,  3.17it/s]
Loading 0:  73%|███████▎  | 212/291 [00:54<00:31,  2.55it/s]
Loading 0:  74%|███████▍  | 215/291 [00:54<00:17,  4.38it/s]
Loading 0:  74%|███████▍  | 216/291 [00:54<00:16,  4.64it/s]
Loading 0:  75%|███████▍  | 217/291 [00:55<00:14,  5.24it/s]
Loading 0:  75%|███████▌  | 219/291 [00:55<00:16,  4.39it/s]
Loading 0:  76%|███████▌  | 220/291 [00:56<00:21,  3.31it/s]
Loading 0:  76%|███████▌  | 221/291 [00:56<00:26,  2.63it/s]
Loading 0:  77%|███████▋  | 224/291 [00:56<00:14,  4.52it/s]
Loading 0:  77%|███████▋  | 225/291 [00:57<00:13,  4.76it/s]
Loading 0:  78%|███████▊  | 226/291 [00:57<00:12,  5.36it/s]
Loading 0:  78%|███████▊  | 228/291 [00:57<00:14,  4.45it/s]
Loading 0:  79%|███████▊  | 229/291 [00:58<00:18,  3.36it/s]
Loading 0:  79%|███████▉  | 230/291 [00:59<00:22,  2.66it/s]
Loading 0:  80%|████████  | 233/291 [00:59<00:12,  4.50it/s]
Loading 0:  80%|████████  | 234/291 [00:59<00:12,  4.75it/s]
Loading 0:  81%|████████  | 235/291 [00:59<00:10,  5.34it/s]
Loading 0:  81%|████████▏ | 237/291 [01:00<00:12,  4.47it/s]
Loading 0:  82%|████████▏ | 238/291 [01:00<00:16,  3.26it/s]
Loading 0:  82%|████████▏ | 239/291 [01:01<00:20,  2.57it/s]
Loading 0:  83%|████████▎ | 242/291 [01:01<00:11,  4.43it/s]
Loading 0:  84%|████████▎ | 243/291 [01:01<00:10,  4.68it/s]
Loading 0:  84%|████████▍ | 244/291 [01:01<00:08,  5.28it/s]
Loading 0:  85%|████████▍ | 246/291 [01:02<00:10,  4.42it/s]
Loading 0:  85%|████████▍ | 247/291 [01:02<00:13,  3.33it/s]
Loading 0:  85%|████████▌ | 248/291 [01:03<00:16,  2.64it/s]
Loading 0:  86%|████████▋ | 251/291 [01:03<00:08,  4.54it/s]
Loading 0:  87%|████████▋ | 252/291 [01:03<00:08,  4.77it/s]
Loading 0:  87%|████████▋ | 253/291 [01:04<00:07,  5.34it/s]
Loading 0:  88%|████████▊ | 255/291 [01:04<00:08,  4.43it/s]
Loading 0:  88%|████████▊ | 256/291 [01:05<00:10,  3.34it/s]
Loading 0:  88%|████████▊ | 257/291 [01:05<00:12,  2.65it/s]
Loading 0:  89%|████████▉ | 260/291 [01:05<00:06,  4.55it/s]
Loading 0:  90%|████████▉ | 261/291 [01:06<00:06,  4.79it/s]
Loading 0:  90%|█████████ | 262/291 [01:06<00:05,  5.39it/s]
Loading 0:  91%|█████████ | 264/291 [01:06<00:06,  4.46it/s]
Loading 0:  91%|█████████ | 265/291 [01:07<00:07,  3.36it/s]
Loading 0:  91%|█████████▏| 266/291 [01:08<00:09,  2.66it/s]
Loading 0:  92%|█████████▏| 269/291 [01:08<00:04,  4.57it/s]
Loading 0:  93%|█████████▎| 270/291 [01:08<00:04,  4.80it/s]
Loading 0:  93%|█████████▎| 272/291 [01:08<00:02,  6.57it/s]
Loading 0:  94%|█████████▍| 274/291 [01:09<00:04,  3.42it/s]
Loading 0:  95%|█████████▍| 275/291 [01:10<00:05,  2.78it/s]
Loading 0:  96%|█████████▌| 278/291 [01:10<00:02,  4.43it/s]
Loading 0:  96%|█████████▌| 279/291 [01:10<00:02,  4.51it/s]
Loading 0:  96%|█████████▌| 280/291 [01:10<00:02,  4.77it/s]
Loading 0:  97%|█████████▋| 281/291 [01:11<00:02,  3.45it/s]
Loading 0:  97%|█████████▋| 282/291 [01:12<00:03,  2.69it/s]
Loading 0:  98%|█████████▊| 284/291 [01:12<00:01,  3.83it/s]
Loading 0:  98%|█████████▊| 285/291 [01:12<00:01,  4.18it/s]
Loading 0:  98%|█████████▊| 286/291 [01:12<00:01,  4.86it/s]
Loading 0:  99%|█████████▊| 287/291 [01:12<00:00,  5.16it/s]
Loading 0:  99%|█████████▉| 288/291 [01:13<00:00,  3.36it/s]
                                                            
Job alexdaoud-trainer-bagir-4107-v1-mkmlizer completed after 135.25s with status: succeeded
Stopping job with name alexdaoud-trainer-bagir-4107-v1-mkmlizer
Pipeline stage MKMLizer completed in 135.75s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.16s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service alexdaoud-trainer-bagir-4107-v1
Waiting for inference service alexdaoud-trainer-bagir-4107-v1 to be ready
Inference service alexdaoud-trainer-bagir-4107-v1 ready after 220.8800973892212s
Pipeline stage MKMLDeployer completed in 221.43s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 4.645366907119751s
Received healthy response to inference request in 3.8328535556793213s
Received healthy response to inference request in 3.591447114944458s
Received healthy response to inference request in 4.966890811920166s
Received healthy response to inference request in 3.1730408668518066s
5 requests
0 failed requests
5th percentile: 3.256722116470337
10th percentile: 3.340403366088867
20th percentile: 3.507765865325928
30th percentile: 3.6397284030914308
40th percentile: 3.736290979385376
50th percentile: 3.8328535556793213
60th percentile: 4.157858896255493
70th percentile: 4.482864236831665
80th percentile: 4.709671688079834
90th percentile: 4.83828125
95th percentile: 4.902586030960083
99th percentile: 4.954029855728149
mean time: 4.041919851303101
%s, retrying in %s seconds...
Received healthy response to inference request in 3.4082884788513184s
Received healthy response to inference request in 3.54394793510437s
Received healthy response to inference request in 3.204986095428467s
Received healthy response to inference request in 3.617007255554199s
Received healthy response to inference request in 2.4939939975738525s
5 requests
0 failed requests
5th percentile: 2.6361924171447755
10th percentile: 2.7783908367156984
20th percentile: 3.062787675857544
30th percentile: 3.245646572113037
40th percentile: 3.3269675254821776
50th percentile: 3.4082884788513184
60th percentile: 3.4625522613525392
70th percentile: 3.5168160438537597
80th percentile: 3.558559799194336
90th percentile: 3.5877835273742678
95th percentile: 3.6023953914642335
99th percentile: 3.614084882736206
mean time: 3.2536447525024412
Pipeline stage StressChecker completed in 39.26s
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 2.30s
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 2.07s
Shutdown handler de-registered
alexdaoud-trainer-bagir-_4107_v1 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 0.14s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.12s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-4107-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-4107-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-4107-v1-profiler ready after 220.47737503051758s
Pipeline stage MKMLProfilerDeployer completed in 220.85s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bafacfa753d9d249761419db6d35d140cb-deplofn7wf:/code/chaiverse_profiler_1734371822 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-bafacfa753d9d249761419db6d35d140cb-deplofn7wf --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734371822 && python profiles.py profile --best_of_n 1 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 256 --output_tokens 1 --summary /code/chaiverse_profiler_1734371822/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bafacfa753d9d249761419db6d35d140cb-deplofn7wf:/code/chaiverse_profiler_1734374620 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-bafacfa753d9d249761419db6d35d140cb-deplofn7wf --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734374620 && python profiles.py profile --best_of_n 1 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 256 --output_tokens 1 --summary /code/chaiverse_profiler_1734374620/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-4107-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-4107-v1-profiler
Service alexdaoud-trainer-bagir-4107-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.39s
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-4107-v1-profiler is running
Skipping teardown as no inference service was found
Pipeline stage MKMLProfilerDeleter completed in 2.42s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.12s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-4107-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-4107-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-4107-v1-profiler ready after 210.48806643486023s
Pipeline stage MKMLProfilerDeployer completed in 210.78s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bafacfa753d9d249761419db6d35d140cb-deplo9gwtl:/code/chaiverse_profiler_1734375444 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-bafacfa753d9d249761419db6d35d140cb-deplo9gwtl --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734375444 && python profiles.py profile --best_of_n 1 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 256 --output_tokens 1 --summary /code/chaiverse_profiler_1734375444/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bafacfa753d9d249761419db6d35d140cb-deplo9gwtl:/code/chaiverse_profiler_1734378242 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-bafacfa753d9d249761419db6d35d140cb-deplo9gwtl --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734378242 && python profiles.py profile --best_of_n 1 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 256 --output_tokens 1 --summary /code/chaiverse_profiler_1734378242/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-4107-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-4107-v1-profiler
Service alexdaoud-trainer-bagir-4107-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.29s
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-4107-v1-profiler is running
Skipping teardown as no inference service was found
Pipeline stage MKMLProfilerDeleter completed in 2.58s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.14s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-4107-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-4107-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-4107-v1-profiler ready after 150.3490297794342s
Pipeline stage MKMLProfilerDeployer completed in 150.71s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bafacfa753d9d249761419db6d35d140cb-deplo26p88:/code/chaiverse_profiler_1734379013 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-bafacfa753d9d249761419db6d35d140cb-deplo26p88 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734379013 && python profiles.py profile --best_of_n 1 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 256 --output_tokens 1 --summary /code/chaiverse_profiler_1734379013/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bafacfa753d9d249761419db6d35d140cb-deplo26p88:/code/chaiverse_profiler_1734381790 --namespace tenant-chaiml-guanaco
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bafacfa753d9d249761419db6d35d140cb-deplo26p88:/code/chaiverse_profiler_1734381790 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-bafacfa753d9d249761419db6d35d140cb-deplo26p88 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734381790 && python profiles.py profile --best_of_n 1 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 256 --output_tokens 1 --summary /code/chaiverse_profiler_1734381790/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-4107-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-4107-v1-profiler
Service alexdaoud-trainer-bagir-4107-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.27s
Shutdown handler de-registered
alexdaoud-trainer-bagir-_4107_v1 status is now inactive due to auto deactivation removed underperforming models