alexdaoud-trainer-bagir-_9249

developer_uid: chai_backend_admin
submission_id: alexdaoud-trainer-bagir-_9249_v1
model_name: alexdaoud-trainer-bagir-_9249_v1
model_group: alexdaoud/trainer_bagir_
status: inactive
timestamp: 2024-12-12T18:24:05+00:00
num_battles: 27581
num_wins: 13849
celo_rating: 1264.42
family_friendly_score: 0.5840000000000001
family_friendly_standard_error: 0.006970566691453429
submission_type: basic
model_repo: alexdaoud/trainer_bagir_2024-12-11-checkpoint-18
model_architecture: LlamaForSequenceClassification
model_num_parameters: 8030261248.0
best_of: 1
max_input_tokens: 256
max_output_tokens: 1
display_name: alexdaoud-trainer-bagir-_9249_v1
ineligible_reason: max_output_tokens!=64
is_internal_developer: True
language_model: alexdaoud/trainer_bagir_2024-12-11-checkpoint-18
model_size: 8B
ranking_group: single
us_pacific_date: 2024-12-12
win_ratio: 0.5021210253435336
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-9249-v1-mkmlizer
Waiting for job on alexdaoud-trainer-bagir-9249-v1-mkmlizer to finish
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║     _____            __           __                                ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║       /___/                                                         ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║  Version: 0.11.12                                                   ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║  https://mk1.ai                                                     ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║  belonging to:                                                      ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║  Chai Research Corp.                                                ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║  Expiration: 2025-01-15 23:59:59                                    ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-9249-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
alexdaoud-trainer-bagir-9249-v1-mkmlizer: Downloaded to shared memory in 34.750s
alexdaoud-trainer-bagir-9249-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:t0, folder:/tmp/tmpj90cmf7h, device:0
alexdaoud-trainer-bagir-9249-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
alexdaoud-trainer-bagir-9249-v1-mkmlizer: quantized model in 87.666s
alexdaoud-trainer-bagir-9249-v1-mkmlizer: Processed model alexdaoud/trainer_bagir_2024-12-11-checkpoint-18 in 122.416s
alexdaoud-trainer-bagir-9249-v1-mkmlizer: creating bucket guanaco-mkml-models
alexdaoud-trainer-bagir-9249-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
alexdaoud-trainer-bagir-9249-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/alexdaoud-trainer-bagir-9249-v1
alexdaoud-trainer-bagir-9249-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-9249-v1/tokenizer.json
alexdaoud-trainer-bagir-9249-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/alexdaoud-trainer-bagir-9249-v1/flywheel_model.0.safetensors
alexdaoud-trainer-bagir-9249-v1-mkmlizer: 
Loading 0:   0%|          | 0/291 [00:00<?, ?it/s]
Loading 0:   1%|          | 3/291 [00:00<00:57,  5.02it/s]
Loading 0:   1%|▏         | 4/291 [00:01<01:33,  3.08it/s]
Loading 0:   2%|▏         | 5/291 [00:01<02:05,  2.28it/s]
Loading 0:   3%|▎         | 8/291 [00:02<01:04,  4.38it/s]
Loading 0:   3%|▎         | 9/291 [00:02<01:03,  4.44it/s]
Loading 0:   3%|▎         | 10/291 [00:02<00:56,  4.94it/s]
Loading 0:   4%|▍         | 12/291 [00:03<01:07,  4.14it/s]
Loading 0:   4%|▍         | 13/291 [00:03<01:28,  3.13it/s]
Loading 0:   5%|▍         | 14/291 [00:04<01:51,  2.49it/s]
Loading 0:   6%|▌         | 17/291 [00:04<01:03,  4.29it/s]
Loading 0:   6%|▌         | 18/291 [00:04<01:00,  4.53it/s]
Loading 0:   7%|▋         | 19/291 [00:04<00:53,  5.04it/s]
Loading 0:   7%|▋         | 21/291 [00:05<01:03,  4.24it/s]
Loading 0:   8%|▊         | 22/291 [00:05<01:23,  3.20it/s]
Loading 0:   8%|▊         | 23/291 [00:06<01:46,  2.52it/s]
Loading 0:   9%|▉         | 26/291 [00:06<01:01,  4.29it/s]
Loading 0:   9%|▉         | 27/291 [00:07<00:58,  4.53it/s]
Loading 0:  10%|▉         | 28/291 [00:07<00:51,  5.13it/s]
Loading 0:  10%|█         | 30/291 [00:07<01:01,  4.26it/s]
Loading 0:  11%|█         | 31/291 [00:08<01:20,  3.22it/s]
Loading 0:  11%|█         | 32/291 [00:08<01:41,  2.54it/s]
Loading 0:  12%|█▏        | 35/291 [00:09<00:59,  4.31it/s]
Loading 0:  12%|█▏        | 36/291 [00:09<00:56,  4.54it/s]
Loading 0:  13%|█▎        | 37/291 [00:09<00:50,  5.05it/s]
Loading 0:  13%|█▎        | 39/291 [00:10<00:59,  4.24it/s]
Loading 0:  14%|█▎        | 40/291 [00:10<01:18,  3.22it/s]
Loading 0:  14%|█▍        | 41/291 [00:11<01:38,  2.53it/s]
Loading 0:  15%|█▌        | 44/291 [00:11<00:56,  4.36it/s]
Loading 0:  15%|█▌        | 45/291 [00:11<00:53,  4.59it/s]
Loading 0:  16%|█▌        | 46/291 [00:11<00:47,  5.19it/s]
Loading 0:  16%|█▋        | 48/291 [00:12<00:56,  4.31it/s]
Loading 0:  17%|█▋        | 49/291 [00:12<01:14,  3.23it/s]
Loading 0:  17%|█▋        | 50/291 [00:13<01:35,  2.52it/s]
Loading 0:  18%|█▊        | 53/291 [00:13<00:55,  4.28it/s]
Loading 0:  19%|█▊        | 54/291 [00:14<00:52,  4.52it/s]
Loading 0:  19%|█▉        | 55/291 [00:14<00:46,  5.11it/s]
Loading 0:  20%|█▉        | 57/291 [00:14<00:54,  4.26it/s]
Loading 0:  20%|█▉        | 58/291 [00:15<01:12,  3.22it/s]
Loading 0:  20%|██        | 59/291 [00:16<01:31,  2.53it/s]
Loading 0:  21%|██▏       | 62/291 [00:16<00:52,  4.35it/s]
Loading 0:  22%|██▏       | 63/291 [00:16<00:49,  4.59it/s]
Loading 0:  22%|██▏       | 64/291 [00:16<00:44,  5.11it/s]
Loading 0:  23%|██▎       | 66/291 [00:17<00:52,  4.27it/s]
Loading 0:  23%|██▎       | 67/291 [00:17<01:09,  3.22it/s]
Loading 0:  23%|██▎       | 68/291 [00:18<01:27,  2.55it/s]
Loading 0:  24%|██▍       | 71/291 [00:18<00:50,  4.35it/s]
Loading 0:  25%|██▍       | 72/291 [00:18<00:47,  4.59it/s]
Loading 0:  25%|██▌       | 73/291 [00:18<00:42,  5.18it/s]
Loading 0:  26%|██▌       | 75/291 [00:19<00:50,  4.31it/s]
Loading 0:  26%|██▌       | 76/291 [00:19<01:06,  3.24it/s]
Loading 0:  26%|██▋       | 77/291 [00:20<01:24,  2.54it/s]
Loading 0:  27%|██▋       | 80/291 [00:20<00:49,  4.30it/s]
Loading 0:  28%|██▊       | 81/291 [00:21<00:46,  4.55it/s]
Loading 0:  28%|██▊       | 82/291 [00:21<00:40,  5.14it/s]
Loading 0:  29%|██▊       | 83/291 [00:21<00:42,  4.86it/s]
Loading 0:  29%|██▉       | 84/291 [00:21<01:02,  3.30it/s]
Loading 0:  29%|██▉       | 85/291 [00:22<01:18,  2.63it/s]
Loading 0:  30%|██▉       | 86/291 [00:23<01:33,  2.18it/s]
Loading 0:  31%|███       | 89/291 [00:23<00:49,  4.07it/s]
Loading 0:  31%|███       | 90/291 [00:23<00:46,  4.34it/s]
Loading 0:  31%|███▏      | 91/291 [00:23<00:40,  4.91it/s]
Loading 0:  32%|███▏      | 93/291 [00:24<00:48,  4.09it/s]
Loading 0:  32%|███▏      | 94/291 [00:24<01:03,  3.12it/s]
Loading 0:  33%|███▎      | 95/291 [00:25<01:18,  2.48it/s]
Loading 0:  34%|███▎      | 98/291 [00:25<00:45,  4.26it/s]
Loading 0:  34%|███▍      | 99/291 [00:25<00:42,  4.50it/s]
Loading 0:  34%|███▍      | 100/291 [00:26<00:37,  5.10it/s]
Loading 0:  35%|███▌      | 102/291 [00:26<00:44,  4.26it/s]
Loading 0:  35%|███▌      | 103/291 [00:27<00:58,  3.22it/s]
Loading 0:  36%|███▌      | 104/291 [00:27<01:12,  2.56it/s]
Loading 0:  37%|███▋      | 107/291 [00:28<00:41,  4.42it/s]
Loading 0:  37%|███▋      | 108/291 [00:28<00:39,  4.65it/s]
Loading 0:  37%|███▋      | 109/291 [00:28<00:34,  5.26it/s]
Loading 0:  38%|███▊      | 111/291 [00:28<00:41,  4.34it/s]
Loading 0:  38%|███▊      | 112/291 [00:29<00:54,  3.26it/s]
Loading 0:  39%|███▉      | 113/291 [00:30<01:09,  2.55it/s]
Loading 0:  40%|███▉      | 116/291 [00:30<00:40,  4.34it/s]
Loading 0:  40%|████      | 117/291 [00:30<00:38,  4.58it/s]
Loading 0:  41%|████      | 118/291 [00:30<00:33,  5.18it/s]
Loading 0:  41%|████      | 120/291 [00:31<00:39,  4.32it/s]
Loading 0:  42%|████▏     | 121/291 [00:31<00:52,  3.26it/s]
Loading 0:  42%|████▏     | 122/291 [00:32<01:05,  2.57it/s]
Loading 0:  43%|████▎     | 125/291 [00:32<00:37,  4.37it/s]
Loading 0:  43%|████▎     | 126/291 [00:32<00:36,  4.58it/s]
Loading 0:  44%|████▎     | 127/291 [00:32<00:31,  5.16it/s]
Loading 0:  44%|████▍     | 129/291 [00:33<00:37,  4.30it/s]
Loading 0:  45%|████▍     | 130/291 [00:34<00:49,  3.24it/s]
Loading 0:  45%|████▌     | 131/291 [00:34<01:02,  2.55it/s]
Loading 0:  46%|████▌     | 134/291 [00:35<00:35,  4.38it/s]
Loading 0:  46%|████▋     | 135/291 [00:35<00:33,  4.61it/s]
Loading 0:  47%|████▋     | 136/291 [00:35<00:29,  5.18it/s]
Loading 0:  47%|████▋     | 138/291 [00:35<00:35,  4.31it/s]
Loading 0:  48%|████▊     | 139/291 [00:36<00:46,  3.25it/s]
Loading 0:  48%|████▊     | 140/291 [00:37<00:59,  2.54it/s]
Loading 0:  49%|████▉     | 143/291 [00:37<00:34,  4.33it/s]
Loading 0:  49%|████▉     | 144/291 [00:37<00:32,  4.57it/s]
Loading 0:  50%|████▉     | 145/291 [00:37<00:28,  5.15it/s]
Loading 0:  51%|█████     | 147/291 [00:38<00:33,  4.30it/s]
Loading 0:  51%|█████     | 148/291 [00:38<00:43,  3.25it/s]
Loading 0:  51%|█████     | 149/291 [00:39<00:55,  2.57it/s]
Loading 0:  52%|█████▏    | 152/291 [00:39<00:31,  4.41it/s]
Loading 0:  53%|█████▎    | 153/291 [00:39<00:29,  4.64it/s]
Loading 0:  53%|█████▎    | 154/291 [00:39<00:26,  5.25it/s]
Loading 0:  54%|█████▎    | 156/291 [00:40<00:31,  4.32it/s]
Loading 0:  54%|█████▍    | 157/291 [00:41<00:41,  3.27it/s]
Loading 0:  54%|█████▍    | 158/291 [00:41<00:51,  2.59it/s]
Loading 0:  55%|█████▌    | 161/291 [00:41<00:29,  4.39it/s]
Loading 0:  56%|█████▌    | 162/291 [00:42<00:27,  4.63it/s]
Loading 0:  56%|█████▌    | 163/291 [00:42<00:24,  5.14it/s]
Loading 0:  57%|█████▋    | 165/291 [00:42<00:29,  4.31it/s]
Loading 0:  57%|█████▋    | 166/291 [00:43<00:38,  3.25it/s]
Loading 0:  57%|█████▋    | 167/291 [00:44<00:48,  2.56it/s]
Loading 0:  58%|█████▊    | 170/291 [00:44<00:27,  4.40it/s]
Loading 0:  59%|█████▉    | 171/291 [00:44<00:25,  4.63it/s]
Loading 0:  59%|█████▉    | 172/291 [00:44<00:22,  5.22it/s]
Loading 0:  59%|█████▉    | 173/291 [00:45<00:33,  3.51it/s]
Loading 0:  60%|██████    | 175/291 [00:45<00:24,  4.70it/s]
Loading 0:  60%|██████    | 176/291 [00:45<00:23,  4.93it/s]
Loading 0:  61%|██████    | 177/291 [00:45<00:20,  5.62it/s]
Loading 0:  62%|██████▏   | 179/291 [00:46<00:25,  4.45it/s]
Loading 0:  62%|██████▏   | 180/291 [00:46<00:33,  3.27it/s]
Loading 0:  62%|██████▏   | 181/291 [00:47<00:42,  2.56it/s]
Loading 0:  63%|██████▎   | 184/291 [00:47<00:23,  4.49it/s]
Loading 0:  64%|██████▎   | 185/291 [00:47<00:22,  4.72it/s]
Loading 0:  64%|██████▍   | 186/291 [00:47<00:19,  5.29it/s]
Loading 0:  64%|██████▍   | 187/291 [00:48<00:19,  5.23it/s]
Loading 0:  65%|██████▍   | 188/291 [00:48<00:29,  3.45it/s]
Loading 0:  65%|██████▍   | 189/291 [00:49<00:39,  2.60it/s]
Loading 0:  66%|██████▌   | 192/291 [00:49<00:28,  3.52it/s]
Loading 0:  66%|██████▋   | 193/291 [00:50<00:33,  2.89it/s]
Loading 0:  67%|██████▋   | 194/291 [00:51<00:40,  2.39it/s]
Loading 0:  68%|██████▊   | 197/291 [00:51<00:23,  4.04it/s]
Loading 0:  68%|██████▊   | 198/291 [00:51<00:21,  4.30it/s]
Loading 0:  68%|██████▊   | 199/291 [00:51<00:18,  4.87it/s]
Loading 0:  69%|██████▉   | 201/291 [00:52<00:21,  4.20it/s]
Loading 0:  69%|██████▉   | 202/291 [00:52<00:27,  3.21it/s]
Loading 0:  70%|██████▉   | 203/291 [00:53<00:34,  2.57it/s]
Loading 0:  71%|███████   | 206/291 [00:53<00:19,  4.39it/s]
Loading 0:  71%|███████   | 207/291 [00:53<00:18,  4.63it/s]
Loading 0:  71%|███████▏  | 208/291 [00:53<00:16,  5.16it/s]
Loading 0:  72%|███████▏  | 210/291 [00:54<00:18,  4.32it/s]
Loading 0:  73%|███████▎  | 211/291 [00:55<00:24,  3.26it/s]
Loading 0:  73%|███████▎  | 212/291 [00:55<00:30,  2.59it/s]
Loading 0:  74%|███████▍  | 215/291 [00:55<00:17,  4.46it/s]
Loading 0:  74%|███████▍  | 216/291 [00:56<00:15,  4.76it/s]
Loading 0:  75%|███████▍  | 217/291 [00:56<00:13,  5.35it/s]
Loading 0:  75%|███████▌  | 219/291 [00:56<00:16,  4.41it/s]
Loading 0:  76%|███████▌  | 220/291 [00:57<00:21,  3.31it/s]
Loading 0:  76%|███████▌  | 221/291 [00:58<00:26,  2.60it/s]
Loading 0:  77%|███████▋  | 224/291 [00:58<00:14,  4.49it/s]
Loading 0:  77%|███████▋  | 225/291 [00:58<00:13,  4.72it/s]
Loading 0:  78%|███████▊  | 226/291 [00:58<00:12,  5.32it/s]
Loading 0:  78%|███████▊  | 228/291 [00:59<00:14,  4.38it/s]
Loading 0:  79%|███████▊  | 229/291 [00:59<00:18,  3.30it/s]
Loading 0:  79%|███████▉  | 230/291 [01:00<00:23,  2.60it/s]
Loading 0:  80%|████████  | 233/291 [01:00<00:13,  4.34it/s]
Loading 0:  80%|████████  | 234/291 [01:00<00:12,  4.58it/s]
Loading 0:  81%|████████  | 235/291 [01:00<00:10,  5.12it/s]
Loading 0:  81%|████████▏ | 237/291 [01:01<00:12,  4.29it/s]
Loading 0:  82%|████████▏ | 238/291 [01:01<00:16,  3.24it/s]
Loading 0:  82%|████████▏ | 239/291 [01:02<00:20,  2.56it/s]
Loading 0:  83%|████████▎ | 242/291 [01:02<00:11,  4.34it/s]
Loading 0:  84%|████████▎ | 243/291 [01:03<00:10,  4.58it/s]
Loading 0:  84%|████████▍ | 244/291 [01:03<00:09,  5.13it/s]
Loading 0:  85%|████████▍ | 246/291 [01:03<00:10,  4.30it/s]
Loading 0:  85%|████████▍ | 247/291 [01:04<00:13,  3.26it/s]
Loading 0:  85%|████████▌ | 248/291 [01:04<00:16,  2.59it/s]
Loading 0:  86%|████████▋ | 251/291 [01:05<00:09,  4.44it/s]
Loading 0:  87%|████████▋ | 252/291 [01:05<00:08,  4.67it/s]
Loading 0:  87%|████████▋ | 253/291 [01:05<00:07,  5.24it/s]
Loading 0:  88%|████████▊ | 255/291 [01:05<00:08,  4.34it/s]
Loading 0:  88%|████████▊ | 256/291 [01:06<00:10,  3.23it/s]
Loading 0:  88%|████████▊ | 257/291 [01:07<00:13,  2.56it/s]
Loading 0:  89%|████████▉ | 260/291 [01:07<00:07,  4.41it/s]
Loading 0:  90%|████████▉ | 261/291 [01:07<00:06,  4.64it/s]
Loading 0:  90%|█████████ | 262/291 [01:07<00:05,  5.22it/s]
Loading 0:  91%|█████████ | 264/291 [01:08<00:06,  4.34it/s]
Loading 0:  91%|█████████ | 265/291 [01:08<00:07,  3.26it/s]
Loading 0:  91%|█████████▏| 266/291 [01:09<00:09,  2.58it/s]
Loading 0:  92%|█████████▏| 269/291 [01:09<00:04,  4.45it/s]
Loading 0:  93%|█████████▎| 270/291 [01:09<00:04,  4.68it/s]
Loading 0:  93%|█████████▎| 271/291 [01:09<00:03,  5.26it/s]
Loading 0:  94%|█████████▍| 273/291 [01:10<00:04,  4.35it/s]
Loading 0:  94%|█████████▍| 274/291 [01:11<00:05,  3.27it/s]
Loading 0:  95%|█████████▍| 275/291 [01:11<00:06,  2.56it/s]
Loading 0:  96%|█████████▌| 278/291 [01:12<00:02,  4.36it/s]
Loading 0:  96%|█████████▌| 279/291 [01:12<00:02,  4.60it/s]
Loading 0:  96%|█████████▌| 280/291 [01:12<00:02,  5.18it/s]
Loading 0:  97%|█████████▋| 281/291 [01:12<00:02,  3.50it/s]
Loading 0:  97%|█████████▋| 282/291 [01:13<00:03,  2.66it/s]
Loading 0:  98%|█████████▊| 284/291 [01:13<00:01,  3.82it/s]
Loading 0:  98%|█████████▊| 285/291 [01:13<00:01,  4.16it/s]
Loading 0:  98%|█████████▊| 286/291 [01:14<00:01,  4.81it/s]
Loading 0:  99%|█████████▊| 287/291 [01:14<00:00,  4.83it/s]
Loading 0:  99%|█████████▉| 288/291 [01:14<00:00,  3.23it/s]
                                                            
Job alexdaoud-trainer-bagir-9249-v1-mkmlizer completed after 145.03s with status: succeeded
Stopping job with name alexdaoud-trainer-bagir-9249-v1-mkmlizer
Pipeline stage MKMLizer completed in 145.56s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.68s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service alexdaoud-trainer-bagir-9249-v1
Waiting for inference service alexdaoud-trainer-bagir-9249-v1 to be ready
Inference service alexdaoud-trainer-bagir-9249-v1 ready after 190.66242742538452s
Pipeline stage MKMLDeployer completed in 191.21s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.9804916381835938s
Received healthy response to inference request in 6.2191243171691895s
Received healthy response to inference request in 3.1866295337677s
Received healthy response to inference request in 4.801101446151733s
Received healthy response to inference request in 3.1630499362945557s
5 requests
0 failed requests
5th percentile: 3.017003297805786
10th percentile: 3.0535149574279785
20th percentile: 3.1265382766723633
30th percentile: 3.1677658557891846
40th percentile: 3.1771976947784424
50th percentile: 3.1866295337677
60th percentile: 3.832418298721313
70th percentile: 4.478207063674926
80th percentile: 5.084706020355225
90th percentile: 5.651915168762207
95th percentile: 5.935519742965698
99th percentile: 6.162403402328491
mean time: 4.070079374313354
%s, retrying in %s seconds...
Received healthy response to inference request in 4.7636706829071045s
Received healthy response to inference request in 3.7871315479278564s
Received healthy response to inference request in 4.0230631828308105s
Received healthy response to inference request in 2.3094635009765625s
Received healthy response to inference request in 3.636575698852539s
5 requests
0 failed requests
5th percentile: 2.574885940551758
10th percentile: 2.8403083801269533
20th percentile: 3.3711532592773437
30th percentile: 3.6666868686676026
40th percentile: 3.7269092082977293
50th percentile: 3.7871315479278564
60th percentile: 3.881504201889038
70th percentile: 3.9758768558502195
80th percentile: 4.17118468284607
90th percentile: 4.467427682876587
95th percentile: 4.615549182891845
99th percentile: 4.734046382904053
mean time: 3.7039809226989746
%s, retrying in %s seconds...
Received healthy response to inference request in 2.3937489986419678s
Received healthy response to inference request in 4.155958890914917s
Received healthy response to inference request in 2.6016950607299805s
Received healthy response to inference request in 2.5644500255584717s
Received healthy response to inference request in 2.7527058124542236s
5 requests
0 failed requests
5th percentile: 2.4278892040252686
10th percentile: 2.4620294094085695
20th percentile: 2.530309820175171
30th percentile: 2.5718990325927735
40th percentile: 2.5867970466613768
50th percentile: 2.6016950607299805
60th percentile: 2.6620993614196777
70th percentile: 2.722503662109375
80th percentile: 3.0333564281463623
90th percentile: 3.5946576595306396
95th percentile: 3.8753082752227783
99th percentile: 4.099828767776489
mean time: 2.8937117576599123
Pipeline stage StressChecker completed in 57.59s
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 3.25s
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 2.52s
Shutdown handler de-registered
alexdaoud-trainer-bagir-_9249_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 0.11s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-9249-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-9249-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-9249-v1-profiler ready after 200.4829716682434s
Pipeline stage MKMLProfilerDeployer completed in 200.85s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba0960aadacce31caee5774c1884b3bc0a-deplopbrw7:/code/chaiverse_profiler_1734028475 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba0960aadacce31caee5774c1884b3bc0a-deplopbrw7 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734028475 && 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_1734028475/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba0960aadacce31caee5774c1884b3bc0a-deplopbrw7:/code/chaiverse_profiler_1734031260 --namespace tenant-chaiml-guanaco
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba0960aadacce31caee5774c1884b3bc0a-deplopbrw7:/code/chaiverse_profiler_1734031261 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba0960aadacce31caee5774c1884b3bc0a-deplopbrw7 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734031261 && 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_1734031261/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-9249-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-9249-v1-profiler
Service alexdaoud-trainer-bagir-9249-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.47s
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-9249-v1-profiler is running
Skipping teardown as no inference service was found
Pipeline stage MKMLProfilerDeleter completed in 2.10s
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-9249-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-9249-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-9249-v1-profiler ready after 190.45555663108826s
Pipeline stage MKMLProfilerDeployer completed in 190.78s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba0960aadacce31caee5774c1884b3bc0a-deplok8mch:/code/chaiverse_profiler_1734032101 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba0960aadacce31caee5774c1884b3bc0a-deplok8mch --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734032101 && 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_1734032101/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba0960aadacce31caee5774c1884b3bc0a-deplok8mch:/code/chaiverse_profiler_1734034899 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba0960aadacce31caee5774c1884b3bc0a-deplok8mch --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734034899 && 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_1734034899/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-9249-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-9249-v1-profiler
Service alexdaoud-trainer-bagir-9249-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.18s
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-9249-v1-profiler is running
Skipping teardown as no inference service was found
Pipeline stage MKMLProfilerDeleter completed in 2.11s
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-9249-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-9249-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-9249-v1-profiler ready after 200.4543137550354s
Pipeline stage MKMLProfilerDeployer completed in 200.80s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba0960aadacce31caee5774c1884b3bc0a-deplod8s5t:/code/chaiverse_profiler_1734035735 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba0960aadacce31caee5774c1884b3bc0a-deplod8s5t --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734035735 && 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_1734035735/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba0960aadacce31caee5774c1884b3bc0a-deplod8s5t:/code/chaiverse_profiler_1734038519 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba0960aadacce31caee5774c1884b3bc0a-deplod8s5t --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734038519 && 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_1734038519/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-9249-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-9249-v1-profiler
Service alexdaoud-trainer-bagir-9249-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.06s
Shutdown handler de-registered
alexdaoud-trainer-bagir-_9249_v1 status is now inactive due to auto deactivation removed underperforming models