alexdaoud-trainer-bagir-_1681

developer_uid: chai_backend_admin
submission_id: alexdaoud-trainer-bagir-_1681_v1
model_name: alexdaoud-trainer-bagir-_1681_v1
model_group: alexdaoud/trainer_bagir_
status: inactive
timestamp: 2024-12-19T00:34:36+00:00
num_battles: 25959
num_wins: 13226
celo_rating: 1270.14
family_friendly_score: 0.5776
family_friendly_standard_error: 0.006985388178190243
submission_type: basic
model_repo: alexdaoud/trainer_bagir_2024-12-11-checkpoint-99
model_architecture: LlamaForSequenceClassification
model_num_parameters: 8030261248.0
best_of: 1
max_input_tokens: 256
max_output_tokens: 1
display_name: alexdaoud-trainer-bagir-_1681_v1
ineligible_reason: max_output_tokens!=64
is_internal_developer: True
language_model: alexdaoud/trainer_bagir_2024-12-11-checkpoint-99
model_size: 8B
ranking_group: single
us_pacific_date: 2024-12-18
win_ratio: 0.5094957432874918
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-1681-v1-mkmlizer
Waiting for job on alexdaoud-trainer-bagir-1681-v1-mkmlizer to finish
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║     _____            __           __                                ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║       /___/                                                         ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║  Version: 0.11.12                                                   ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║  https://mk1.ai                                                     ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║  belonging to:                                                      ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║  Chai Research Corp.                                                ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║  Expiration: 2025-01-15 23:59:59                                    ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-1681-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
alexdaoud-trainer-bagir-1681-v1-mkmlizer: Downloaded to shared memory in 34.546s
alexdaoud-trainer-bagir-1681-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:t0, folder:/tmp/tmpjilvi9g3, device:0
alexdaoud-trainer-bagir-1681-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
alexdaoud-trainer-bagir-1681-v1-mkmlizer: quantized model in 87.004s
alexdaoud-trainer-bagir-1681-v1-mkmlizer: Processed model alexdaoud/trainer_bagir_2024-12-11-checkpoint-99 in 121.550s
alexdaoud-trainer-bagir-1681-v1-mkmlizer: creating bucket guanaco-mkml-models
alexdaoud-trainer-bagir-1681-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
alexdaoud-trainer-bagir-1681-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1681-v1
alexdaoud-trainer-bagir-1681-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1681-v1/config.json
alexdaoud-trainer-bagir-1681-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1681-v1/special_tokens_map.json
alexdaoud-trainer-bagir-1681-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1681-v1/tokenizer_config.json
alexdaoud-trainer-bagir-1681-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1681-v1/flywheel_model.0.safetensors
alexdaoud-trainer-bagir-1681-v1-mkmlizer: 
Loading 0:   0%|          | 0/291 [00:00<?, ?it/s]
Loading 0:   1%|          | 3/291 [00:00<00:56,  5.10it/s]
Loading 0:   1%|▏         | 4/291 [00:01<01:32,  3.12it/s]
Loading 0:   2%|▏         | 5/291 [00:01<02:03,  2.32it/s]
Loading 0:   3%|▎         | 8/291 [00:02<01:03,  4.45it/s]
Loading 0:   3%|▎         | 9/291 [00:02<01:02,  4.50it/s]
Loading 0:   3%|▎         | 10/291 [00:02<00:55,  5.05it/s]
Loading 0:   4%|▍         | 12/291 [00:02<01:05,  4.24it/s]
Loading 0:   4%|▍         | 13/291 [00:03<01:26,  3.20it/s]
Loading 0:   5%|▍         | 14/291 [00:04<01:49,  2.54it/s]
Loading 0:   6%|▌         | 17/291 [00:04<01:02,  4.36it/s]
Loading 0:   6%|▌         | 18/291 [00:04<00:59,  4.60it/s]
Loading 0:   7%|▋         | 19/291 [00:04<00:53,  5.13it/s]
Loading 0:   7%|▋         | 21/291 [00:05<01:02,  4.31it/s]
Loading 0:   8%|▊         | 22/291 [00:05<01:23,  3.23it/s]
Loading 0:   8%|▊         | 23/291 [00:06<01:44,  2.55it/s]
Loading 0:   9%|▉         | 26/291 [00:06<01:00,  4.35it/s]
Loading 0:   9%|▉         | 27/291 [00:06<00:57,  4.59it/s]
Loading 0:  10%|█         | 30/291 [00:07<00:58,  4.49it/s]
Loading 0:  11%|█         | 31/291 [00:08<01:14,  3.49it/s]
Loading 0:  11%|█         | 32/291 [00:08<01:34,  2.75it/s]
Loading 0:  12%|█▏        | 35/291 [00:09<01:01,  4.15it/s]
Loading 0:  12%|█▏        | 36/291 [00:09<00:58,  4.36it/s]
Loading 0:  13%|█▎        | 37/291 [00:09<00:52,  4.88it/s]
Loading 0:  13%|█▎        | 39/291 [00:10<00:59,  4.20it/s]
Loading 0:  14%|█▎        | 40/291 [00:10<01:17,  3.23it/s]
Loading 0:  14%|█▍        | 41/291 [00:11<01:37,  2.56it/s]
Loading 0:  15%|█▌        | 44/291 [00:11<00:56,  4.34it/s]
Loading 0:  15%|█▌        | 45/291 [00:11<00:53,  4.59it/s]
Loading 0:  16%|█▌        | 46/291 [00:11<00:47,  5.11it/s]
Loading 0:  16%|█▋        | 48/291 [00:12<00:56,  4.33it/s]
Loading 0:  17%|█▋        | 49/291 [00:12<01:13,  3.27it/s]
Loading 0:  17%|█▋        | 50/291 [00:13<01:33,  2.57it/s]
Loading 0:  18%|█▊        | 53/291 [00:13<00:53,  4.41it/s]
Loading 0:  19%|█▊        | 54/291 [00:13<00:50,  4.65it/s]
Loading 0:  19%|█▉        | 55/291 [00:14<00:45,  5.23it/s]
Loading 0:  20%|█▉        | 57/291 [00:14<00:53,  4.36it/s]
Loading 0:  20%|█▉        | 58/291 [00:15<01:10,  3.29it/s]
Loading 0:  20%|██        | 59/291 [00:15<01:29,  2.60it/s]
Loading 0:  21%|██▏       | 62/291 [00:16<00:51,  4.44it/s]
Loading 0:  22%|██▏       | 63/291 [00:16<00:48,  4.66it/s]
Loading 0:  22%|██▏       | 64/291 [00:16<00:43,  5.18it/s]
Loading 0:  23%|██▎       | 66/291 [00:16<00:52,  4.31it/s]
Loading 0:  23%|██▎       | 67/291 [00:17<01:10,  3.19it/s]
Loading 0:  23%|██▎       | 68/291 [00:18<01:29,  2.50it/s]
Loading 0:  24%|██▍       | 71/291 [00:18<00:51,  4.25it/s]
Loading 0:  25%|██▍       | 72/291 [00:18<00:48,  4.51it/s]
Loading 0:  25%|██▌       | 73/291 [00:18<00:42,  5.11it/s]
Loading 0:  26%|██▌       | 75/291 [00:19<00:50,  4.25it/s]
Loading 0:  26%|██▌       | 76/291 [00:19<01:06,  3.24it/s]
Loading 0:  26%|██▋       | 77/291 [00:20<01:23,  2.56it/s]
Loading 0:  27%|██▋       | 80/291 [00:20<00:48,  4.34it/s]
Loading 0:  28%|██▊       | 81/291 [00:20<00:45,  4.57it/s]
Loading 0:  28%|██▊       | 82/291 [00:21<00:42,  4.93it/s]
Loading 0:  29%|██▊       | 83/291 [00:21<00:41,  5.07it/s]
Loading 0:  29%|██▉       | 84/291 [00:21<01:01,  3.38it/s]
Loading 0:  29%|██▉       | 85/291 [00:22<01:17,  2.67it/s]
Loading 0:  30%|██▉       | 86/291 [00:23<01:33,  2.20it/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,  4.95it/s]
Loading 0:  32%|███▏      | 93/291 [00:24<00:47,  4.21it/s]
Loading 0:  32%|███▏      | 94/291 [00:24<01:01,  3.19it/s]
Loading 0:  33%|███▎      | 95/291 [00:25<01:17,  2.53it/s]
Loading 0:  34%|███▎      | 98/291 [00:25<00:43,  4.39it/s]
Loading 0:  34%|███▍      | 99/291 [00:25<00:41,  4.62it/s]
Loading 0:  34%|███▍      | 100/291 [00:25<00:36,  5.20it/s]
Loading 0:  35%|███▌      | 102/291 [00:26<00:43,  4.32it/s]
Loading 0:  35%|███▌      | 103/291 [00:27<00:57,  3.25it/s]
Loading 0:  36%|███▌      | 104/291 [00:27<01:12,  2.57it/s]
Loading 0:  37%|███▋      | 107/291 [00:27<00:41,  4.43it/s]
Loading 0:  37%|███▋      | 108/291 [00:28<00:39,  4.65it/s]
Loading 0:  37%|███▋      | 109/291 [00:28<00:34,  5.24it/s]
Loading 0:  38%|███▊      | 111/291 [00:28<00:41,  4.35it/s]
Loading 0:  38%|███▊      | 112/291 [00:29<00:56,  3.19it/s]
Loading 0:  39%|███▉      | 113/291 [00:30<01:10,  2.54it/s]
Loading 0:  40%|███▉      | 116/291 [00:30<00:39,  4.38it/s]
Loading 0:  40%|████      | 117/291 [00:30<00:38,  4.49it/s]
Loading 0:  41%|████      | 118/291 [00:30<00:35,  4.91it/s]
Loading 0:  41%|████      | 120/291 [00:31<00:40,  4.22it/s]
Loading 0:  42%|████▏     | 121/291 [00:31<00:52,  3.22it/s]
Loading 0:  42%|████▏     | 122/291 [00:32<01:06,  2.55it/s]
Loading 0:  43%|████▎     | 125/291 [00:32<00:37,  4.41it/s]
Loading 0:  43%|████▎     | 126/291 [00:32<00:35,  4.65it/s]
Loading 0:  44%|████▍     | 128/291 [00:32<00:25,  6.39it/s]
Loading 0:  45%|████▍     | 130/291 [00:33<00:48,  3.32it/s]
Loading 0:  45%|████▌     | 131/291 [00:34<00:59,  2.71it/s]
Loading 0:  46%|████▌     | 134/291 [00:34<00:36,  4.29it/s]
Loading 0:  46%|████▋     | 135/291 [00:35<00:34,  4.52it/s]
Loading 0:  47%|████▋     | 136/291 [00:35<00:30,  5.08it/s]
Loading 0:  47%|████▋     | 138/291 [00:35<00:35,  4.31it/s]
Loading 0:  48%|████▊     | 139/291 [00:36<00:46,  3.26it/s]
Loading 0:  48%|████▊     | 140/291 [00:36<00:59,  2.56it/s]
Loading 0:  49%|████▉     | 143/291 [00:37<00:34,  4.30it/s]
Loading 0:  49%|████▉     | 144/291 [00:37<00:32,  4.54it/s]
Loading 0:  50%|████▉     | 145/291 [00:37<00:28,  5.12it/s]
Loading 0:  51%|█████     | 147/291 [00:38<00:33,  4.29it/s]
Loading 0:  51%|█████     | 148/291 [00:38<00:44,  3.24it/s]
Loading 0:  51%|█████     | 149/291 [00:39<00:55,  2.57it/s]
Loading 0:  52%|█████▏    | 152/291 [00:39<00:31,  4.35it/s]
Loading 0:  53%|█████▎    | 153/291 [00:39<00:30,  4.59it/s]
Loading 0:  53%|█████▎    | 154/291 [00:39<00:26,  5.18it/s]
Loading 0:  54%|█████▎    | 156/291 [00:40<00:31,  4.34it/s]
Loading 0:  54%|█████▍    | 157/291 [00:40<00:41,  3.26it/s]
Loading 0:  54%|█████▍    | 158/291 [00:41<00:51,  2.57it/s]
Loading 0:  55%|█████▌    | 161/291 [00:41<00:29,  4.34it/s]
Loading 0:  56%|█████▌    | 162/291 [00:41<00:28,  4.59it/s]
Loading 0:  56%|█████▌    | 163/291 [00:42<00:24,  5.17it/s]
Loading 0:  57%|█████▋    | 165/291 [00:42<00:29,  4.32it/s]
Loading 0:  57%|█████▋    | 166/291 [00:43<00:38,  3.26it/s]
Loading 0:  57%|█████▋    | 167/291 [00:43<00:47,  2.58it/s]
Loading 0:  58%|█████▊    | 170/291 [00:44<00:27,  4.38it/s]
Loading 0:  59%|█████▉    | 171/291 [00:44<00:26,  4.62it/s]
Loading 0:  59%|█████▉    | 172/291 [00:44<00:22,  5.21it/s]
Loading 0:  59%|█████▉    | 173/291 [00:44<00:33,  3.52it/s]
Loading 0:  60%|██████    | 175/291 [00:45<00:24,  4.82it/s]
Loading 0:  60%|██████    | 176/291 [00:45<00:22,  5.04it/s]
Loading 0:  61%|██████    | 177/291 [00:45<00:20,  5.67it/s]
Loading 0:  62%|██████▏   | 179/291 [00:45<00:25,  4.48it/s]
Loading 0:  62%|██████▏   | 180/291 [00:46<00:33,  3.29it/s]
Loading 0:  62%|██████▏   | 181/291 [00:47<00:42,  2.56it/s]
Loading 0:  63%|██████▎   | 184/291 [00:47<00:23,  4.48it/s]
Loading 0:  64%|██████▎   | 185/291 [00:47<00:22,  4.70it/s]
Loading 0:  64%|██████▍   | 186/291 [00:47<00:19,  5.29it/s]
Loading 0:  64%|██████▍   | 187/291 [00:47<00:18,  5.48it/s]
Loading 0:  65%|██████▍   | 188/291 [00:48<00:29,  3.51it/s]
Loading 0:  65%|██████▍   | 189/291 [00:49<00:39,  2.61it/s]
Loading 0:  66%|██████▌   | 192/291 [00:49<00:28,  3.52it/s]
Loading 0:  66%|██████▋   | 193/291 [00:50<00:33,  2.90it/s]
Loading 0:  67%|██████▋   | 194/291 [00:50<00:40,  2.42it/s]
Loading 0:  68%|██████▊   | 197/291 [00:51<00:22,  4.14it/s]
Loading 0:  68%|██████▊   | 198/291 [00:51<00:21,  4.40it/s]
Loading 0:  68%|██████▊   | 199/291 [00:51<00:18,  4.99it/s]
Loading 0:  69%|██████▉   | 201/291 [00:51<00:21,  4.26it/s]
Loading 0:  69%|██████▉   | 202/291 [00:52<00:27,  3.23it/s]
Loading 0:  70%|██████▉   | 203/291 [00:53<00:34,  2.57it/s]
Loading 0:  71%|███████   | 206/291 [00:53<00:19,  4.36it/s]
Loading 0:  71%|███████   | 207/291 [00:53<00:18,  4.60it/s]
Loading 0:  71%|███████▏  | 208/291 [00:53<00:15,  5.20it/s]
Loading 0:  72%|███████▏  | 210/291 [00:54<00:18,  4.36it/s]
Loading 0:  73%|███████▎  | 211/291 [00:54<00:24,  3.27it/s]
Loading 0:  73%|███████▎  | 212/291 [00:55<00:30,  2.57it/s]
Loading 0:  74%|███████▍  | 215/291 [00:55<00:17,  4.41it/s]
Loading 0:  74%|███████▍  | 216/291 [00:55<00:16,  4.65it/s]
Loading 0:  75%|███████▍  | 217/291 [00:55<00:14,  5.22it/s]
Loading 0:  75%|███████▌  | 219/291 [00:56<00:16,  4.35it/s]
Loading 0:  76%|███████▌  | 220/291 [00:57<00:21,  3.27it/s]
Loading 0:  76%|███████▌  | 221/291 [00:57<00:27,  2.58it/s]
Loading 0:  77%|███████▋  | 224/291 [00:57<00:15,  4.42it/s]
Loading 0:  77%|███████▋  | 225/291 [00:58<00:14,  4.66it/s]
Loading 0:  78%|███████▊  | 226/291 [00:58<00:12,  5.23it/s]
Loading 0:  78%|███████▊  | 228/291 [00:58<00:14,  4.34it/s]
Loading 0:  79%|███████▊  | 229/291 [00:59<00:18,  3.27it/s]
Loading 0:  79%|███████▉  | 230/291 [01:00<00:23,  2.58it/s]
Loading 0:  80%|████████  | 233/291 [01:00<00:13,  4.43it/s]
Loading 0:  80%|████████  | 234/291 [01:00<00:12,  4.66it/s]
Loading 0:  81%|████████  | 235/291 [01:00<00:10,  5.26it/s]
Loading 0:  81%|████████▏ | 237/291 [01:01<00:12,  4.35it/s]
Loading 0:  82%|████████▏ | 238/291 [01:01<00:16,  3.28it/s]
Loading 0:  82%|████████▏ | 239/291 [01:02<00:20,  2.60it/s]
Loading 0:  83%|████████▎ | 242/291 [01:02<00:10,  4.47it/s]
Loading 0:  84%|████████▎ | 243/291 [01:02<00:10,  4.70it/s]
Loading 0:  84%|████████▍ | 244/291 [01:02<00:08,  5.29it/s]
Loading 0:  85%|████████▍ | 246/291 [01:03<00:10,  4.37it/s]
Loading 0:  85%|████████▍ | 247/291 [01:03<00:13,  3.29it/s]
Loading 0:  85%|████████▌ | 248/291 [01:04<00:16,  2.62it/s]
Loading 0:  86%|████████▋ | 251/291 [01:04<00:08,  4.47it/s]
Loading 0:  87%|████████▋ | 252/291 [01:04<00:08,  4.71it/s]
Loading 0:  87%|████████▋ | 253/291 [01:05<00:07,  5.29it/s]
Loading 0:  88%|████████▊ | 255/291 [01:05<00:08,  4.38it/s]
Loading 0:  88%|████████▊ | 256/291 [01:06<00:10,  3.28it/s]
Loading 0:  88%|████████▊ | 257/291 [01:06<00:13,  2.60it/s]
Loading 0:  89%|████████▉ | 260/291 [01:07<00:06,  4.43it/s]
Loading 0:  90%|████████▉ | 261/291 [01:07<00:06,  4.66it/s]
Loading 0:  91%|█████████ | 264/291 [01:07<00:05,  4.52it/s]
Loading 0:  91%|█████████ | 265/291 [01:08<00:07,  3.50it/s]
Loading 0:  91%|█████████▏| 266/291 [01:09<00:08,  2.78it/s]
Loading 0:  92%|█████████▏| 269/291 [01:09<00:04,  4.50it/s]
Loading 0:  93%|█████████▎| 270/291 [01:09<00:04,  4.71it/s]
Loading 0:  93%|█████████▎| 271/291 [01:09<00:03,  5.27it/s]
Loading 0:  94%|█████████▍| 273/291 [01:10<00:04,  4.35it/s]
Loading 0:  94%|█████████▍| 274/291 [01:10<00:05,  3.29it/s]
Loading 0:  95%|█████████▍| 275/291 [01:11<00:06,  2.60it/s]
Loading 0:  96%|█████████▌| 278/291 [01:11<00:02,  4.42it/s]
Loading 0:  96%|█████████▌| 279/291 [01:11<00:02,  4.65it/s]
Loading 0:  96%|█████████▌| 280/291 [01:11<00:02,  5.24it/s]
Loading 0:  97%|█████████▋| 281/291 [01:12<00:02,  3.52it/s]
Loading 0:  97%|█████████▋| 282/291 [01:13<00:03,  2.66it/s]
Loading 0:  98%|█████████▊| 284/291 [01:13<00:01,  3.81it/s]
Loading 0:  98%|█████████▊| 285/291 [01:13<00:01,  4.15it/s]
Loading 0:  98%|█████████▊| 286/291 [01:13<00:01,  4.77it/s]
Loading 0:  99%|█████████▊| 287/291 [01:13<00:00,  4.97it/s]
Loading 0:  99%|█████████▉| 288/291 [01:14<00:00,  3.28it/s]
                                                            
Job alexdaoud-trainer-bagir-1681-v1-mkmlizer completed after 145.35s with status: succeeded
Stopping job with name alexdaoud-trainer-bagir-1681-v1-mkmlizer
Pipeline stage MKMLizer completed in 145.84s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.15s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service alexdaoud-trainer-bagir-1681-v1
Waiting for inference service alexdaoud-trainer-bagir-1681-v1 to be ready
Connection pool is full, discarding connection: %s. Connection pool size: %s
Inference service alexdaoud-trainer-bagir-1681-v1 ready after 251.19065761566162s
Pipeline stage MKMLDeployer completed in 251.86s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 3.3723084926605225s
Received healthy response to inference request in 3.849756956100464s
Received healthy response to inference request in 5.161068439483643s
Received healthy response to inference request in 3.0752811431884766s
Received healthy response to inference request in 3.878511667251587s
5 requests
0 failed requests
5th percentile: 3.1346866130828857
10th percentile: 3.1940920829772947
20th percentile: 3.3129030227661134
30th percentile: 3.467798185348511
40th percentile: 3.6587775707244874
50th percentile: 3.849756956100464
60th percentile: 3.861258840560913
70th percentile: 3.8727607250213625
80th percentile: 4.135023021697998
90th percentile: 4.6480457305908205
95th percentile: 4.904557085037231
99th percentile: 5.10976616859436
mean time: 3.8673853397369387
%s, retrying in %s seconds...
Received healthy response to inference request in 4.273240804672241s
Received healthy response to inference request in 3.596473455429077s
Received healthy response to inference request in 4.780409097671509s
Received healthy response to inference request in 2.2519476413726807s
Received healthy response to inference request in 3.6314597129821777s
5 requests
0 failed requests
5th percentile: 2.52085280418396
10th percentile: 2.7897579669952393
20th percentile: 3.327568292617798
30th percentile: 3.603470706939697
40th percentile: 3.6174652099609377
50th percentile: 3.6314597129821777
60th percentile: 3.888172149658203
70th percentile: 4.1448845863342285
80th percentile: 4.374674463272095
90th percentile: 4.577541780471802
95th percentile: 4.678975439071655
99th percentile: 4.760122365951538
mean time: 3.706706142425537
%s, retrying in %s seconds...
Received healthy response to inference request in 3.618990659713745s
Received healthy response to inference request in 3.358586311340332s
Received healthy response to inference request in 3.316563606262207s
Received healthy response to inference request in 1.5650749206542969s
Received healthy response to inference request in 4.118686676025391s
5 requests
0 failed requests
5th percentile: 1.915372657775879
10th percentile: 2.265670394897461
20th percentile: 2.966265869140625
30th percentile: 3.324968147277832
40th percentile: 3.341777229309082
50th percentile: 3.358586311340332
60th percentile: 3.4627480506896973
70th percentile: 3.5669097900390625
80th percentile: 3.7189298629760743
90th percentile: 3.9188082695007322
95th percentile: 4.018747472763062
99th percentile: 4.098698835372925
mean time: 3.1955804347991945
Pipeline stage StressChecker completed in 58.38s
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 3.15s
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 2.30s
Shutdown handler de-registered
alexdaoud-trainer-bagir-_1681_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 0.15s
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-1681-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-1681-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-1681-v1-profiler ready after 240.52884650230408s
Pipeline stage MKMLProfilerDeployer completed in 240.91s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baf9de37e5edfc4c88b5289227aea24f9d-deplov9mtz:/code/chaiverse_profiler_1734569212 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-baf9de37e5edfc4c88b5289227aea24f9d-deplov9mtz --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734569212 && 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_1734569212/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baf9de37e5edfc4c88b5289227aea24f9d-deplov9mtz:/code/chaiverse_profiler_1734571980 --namespace tenant-chaiml-guanaco
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baf9de37e5edfc4c88b5289227aea24f9d-deplov9mtz:/code/chaiverse_profiler_1734571981 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-baf9de37e5edfc4c88b5289227aea24f9d-deplov9mtz --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734571981 && 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_1734571981/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1681-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-1681-v1-profiler
Service alexdaoud-trainer-bagir-1681-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.73s
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1681-v1-profiler is running
Skipping teardown as no inference service was found
Pipeline stage MKMLProfilerDeleter completed in 2.65s
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-1681-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-1681-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-1681-v1-profiler ready after 150.3846254348755s
Pipeline stage MKMLProfilerDeployer completed in 150.73s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baf9de37e5edfc4c88b5289227aea24f9d-deploz2brb:/code/chaiverse_profiler_1734572752 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-baf9de37e5edfc4c88b5289227aea24f9d-deploz2brb --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734572752 && 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_1734572752/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baf9de37e5edfc4c88b5289227aea24f9d-deploz2brb:/code/chaiverse_profiler_1734575537 --namespace tenant-chaiml-guanaco
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baf9de37e5edfc4c88b5289227aea24f9d-deploz2brb:/code/chaiverse_profiler_1734575537 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-baf9de37e5edfc4c88b5289227aea24f9d-deploz2brb --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734575537 && 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_1734575537/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1681-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-1681-v1-profiler
Service alexdaoud-trainer-bagir-1681-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.50s
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1681-v1-profiler is running
Skipping teardown as no inference service was found
Pipeline stage MKMLProfilerDeleter completed in 2.53s
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-1681-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-1681-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-1681-v1-profiler ready after 140.31914114952087s
Pipeline stage MKMLProfilerDeployer completed in 140.66s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baf9de37e5edfc4c88b5289227aea24f9d-deplomlmmj:/code/chaiverse_profiler_1734576368 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-baf9de37e5edfc4c88b5289227aea24f9d-deplomlmmj --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734576368 && 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_1734576368/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baf9de37e5edfc4c88b5289227aea24f9d-deplomlmmj:/code/chaiverse_profiler_1734579143 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-baf9de37e5edfc4c88b5289227aea24f9d-deplomlmmj --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734579143 && 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_1734579143/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1681-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-1681-v1-profiler
Service alexdaoud-trainer-bagir-1681-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.91s
Shutdown handler de-registered
alexdaoud-trainer-bagir-_1681_v1 status is now inactive due to auto deactivation removed underperforming models