developer_uid: chai_backend_admin
submission_id: alexdaoud-trainer-bagir-_1971_v1
model_name: alexdaoud-trainer-bagir-_1971_v1
model_group: alexdaoud/trainer_bagir_
status: inactive
timestamp: 2024-12-15T21:59:19+00:00
num_battles: 21574
num_wins: 11041
celo_rating: 1260.22
family_friendly_score: 0.5806
family_friendly_standard_error: 0.0069785906886705995
submission_type: basic
model_repo: alexdaoud/trainer_bagir_2024-12-11-checkpoint-44
model_architecture: LlamaForSequenceClassification
model_num_parameters: 8030261248.0
best_of: 1
max_input_tokens: 256
max_output_tokens: 1
display_name: alexdaoud-trainer-bagir-_1971_v1
ineligible_reason: max_output_tokens!=64
is_internal_developer: True
language_model: alexdaoud/trainer_bagir_2024-12-11-checkpoint-44
model_size: 8B
ranking_group: single
us_pacific_date: 2024-12-15
win_ratio: 0.5117734309817373
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-1971-v1-mkmlizer
Waiting for job on alexdaoud-trainer-bagir-1971-v1-mkmlizer to finish
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ _____ __ __ ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ /___/ ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ Version: 0.11.12 ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ https://mk1.ai ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ The license key for the current software has been verified as ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ belonging to: ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ Chai Research Corp. ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ Expiration: 2025-01-15 23:59:59 ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ║ ║
alexdaoud-trainer-bagir-1971-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
alexdaoud-trainer-bagir-1971-v1-mkmlizer: Downloaded to shared memory in 35.724s
alexdaoud-trainer-bagir-1971-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:t0, folder:/tmp/tmp3d4evd93, device:0
alexdaoud-trainer-bagir-1971-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
Connection pool is full, discarding connection: %s. Connection pool size: %s
alexdaoud-trainer-bagir-1971-v1-mkmlizer: quantized model in 86.076s
alexdaoud-trainer-bagir-1971-v1-mkmlizer: Processed model alexdaoud/trainer_bagir_2024-12-11-checkpoint-44 in 121.800s
alexdaoud-trainer-bagir-1971-v1-mkmlizer: creating bucket guanaco-mkml-models
alexdaoud-trainer-bagir-1971-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
alexdaoud-trainer-bagir-1971-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1971-v1
alexdaoud-trainer-bagir-1971-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1971-v1/config.json
alexdaoud-trainer-bagir-1971-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1971-v1/special_tokens_map.json
alexdaoud-trainer-bagir-1971-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1971-v1/tokenizer_config.json
alexdaoud-trainer-bagir-1971-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1971-v1/tokenizer.json
alexdaoud-trainer-bagir-1971-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1971-v1/flywheel_model.0.safetensors
alexdaoud-trainer-bagir-1971-v1-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 1%| | 3/291 [00:00<00:57, 5.05it/s] Loading 0: 1%|▏ | 4/291 [00:01<01:32, 3.11it/s] Loading 0: 2%|▏ | 5/291 [00:01<02:04, 2.31it/s] Loading 0: 3%|▎ | 8/291 [00:02<01:04, 4.42it/s] Loading 0: 3%|▎ | 9/291 [00:02<01:02, 4.49it/s] Loading 0: 3%|▎ | 10/291 [00:02<00:54, 5.12it/s] Loading 0: 4%|▍ | 12/291 [00:02<01:05, 4.29it/s] Loading 0: 4%|▍ | 13/291 [00:03<01:26, 3.22it/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, 4.59it/s] Loading 0: 7%|▋ | 19/291 [00:04<00:52, 5.15it/s] Loading 0: 7%|▋ | 21/291 [00:05<01:02, 4.31it/s] Loading 0: 8%|▊ | 22/291 [00:05<01:22, 3.25it/s] Loading 0: 8%|▊ | 23/291 [00:06<01:45, 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%|▉ | 28/291 [00:07<00:50, 5.20it/s] Loading 0: 10%|█ | 30/291 [00:07<00:59, 4.36it/s] Loading 0: 11%|█ | 31/291 [00:08<01:19, 3.29it/s] Loading 0: 11%|█ | 32/291 [00:08<01:40, 2.57it/s] Loading 0: 12%|█▏ | 35/291 [00:09<00:58, 4.37it/s] Loading 0: 12%|█▏ | 36/291 [00:09<00:55, 4.60it/s] Loading 0: 13%|█▎ | 37/291 [00:09<00:49, 5.10it/s] Loading 0: 13%|█▎ | 39/291 [00:09<00:58, 4.31it/s] Loading 0: 14%|█▎ | 40/291 [00:10<01:16, 3.26it/s] Loading 0: 14%|█▍ | 41/291 [00:11<01:37, 2.56it/s] Loading 0: 15%|█▌ | 44/291 [00:11<00:56, 4.35it/s] Loading 0: 15%|█▌ | 45/291 [00:11<00:53, 4.56it/s] Loading 0: 16%|█▌ | 46/291 [00:11<00:48, 5.07it/s] Loading 0: 16%|█▋ | 48/291 [00:12<00:56, 4.28it/s] Loading 0: 17%|█▋ | 49/291 [00:12<01:14, 3.26it/s] Loading 0: 17%|█▋ | 50/291 [00:13<01:34, 2.56it/s] Loading 0: 18%|█▊ | 53/291 [00:13<00:54, 4.35it/s] Loading 0: 19%|█▊ | 54/291 [00:13<00:51, 4.60it/s] Loading 0: 19%|█▉ | 55/291 [00:13<00:45, 5.18it/s] Loading 0: 20%|█▉ | 57/291 [00:14<00:53, 4.35it/s] Loading 0: 20%|█▉ | 58/291 [00:15<01:10, 3.30it/s] Loading 0: 20%|██ | 59/291 [00:15<01:29, 2.58it/s] Loading 0: 21%|██▏ | 62/291 [00:15<00:51, 4.44it/s] Loading 0: 22%|██▏ | 63/291 [00:16<00:48, 4.68it/s] Loading 0: 22%|██▏ | 64/291 [00:16<00:43, 5.27it/s] Loading 0: 23%|██▎ | 66/291 [00:16<00:51, 4.40it/s] Loading 0: 23%|██▎ | 67/291 [00:17<01:07, 3.31it/s] Loading 0: 23%|██▎ | 68/291 [00:18<01:25, 2.60it/s] Loading 0: 24%|██▍ | 71/291 [00:18<00:49, 4.48it/s] Loading 0: 25%|██▍ | 72/291 [00:18<00:46, 4.70it/s] Loading 0: 25%|██▌ | 73/291 [00:18<00:41, 5.30it/s] Loading 0: 26%|██▌ | 75/291 [00:19<00:49, 4.39it/s] Loading 0: 26%|██▌ | 76/291 [00:19<01:05, 3.29it/s] Loading 0: 26%|██▋ | 77/291 [00:20<01:23, 2.57it/s] Loading 0: 27%|██▋ | 80/291 [00:20<00:48, 4.38it/s] Loading 0: 28%|██▊ | 81/291 [00:20<00:45, 4.62it/s] Loading 0: 28%|██▊ | 82/291 [00:20<00:40, 5.21it/s] Loading 0: 29%|██▊ | 83/291 [00:20<00:39, 5.24it/s] Loading 0: 29%|██▉ | 84/291 [00:21<00:59, 3.47it/s] Loading 0: 29%|██▉ | 85/291 [00:22<01:15, 2.73it/s] Loading 0: 30%|██▉ | 86/291 [00:22<01:31, 2.25it/s] Loading 0: 31%|███ | 89/291 [00:23<00:48, 4.15it/s] Loading 0: 31%|███ | 90/291 [00:23<00:45, 4.43it/s] Loading 0: 31%|███▏ | 91/291 [00:23<00:39, 5.05it/s] Loading 0: 32%|███▏ | 93/291 [00:23<00:46, 4.25it/s] Loading 0: 32%|███▏ | 94/291 [00:24<01:01, 3.20it/s] Loading 0: 33%|███▎ | 95/291 [00:25<01:17, 2.54it/s] Loading 0: 34%|███▎ | 98/291 [00:25<00:43, 4.39it/s] Loading 0: 34%|███▍ | 99/291 [00:25<00:41, 4.63it/s] Loading 0: 34%|███▍ | 100/291 [00:25<00:36, 5.18it/s] Loading 0: 35%|███▌ | 102/291 [00:26<00:43, 4.32it/s] Loading 0: 35%|███▌ | 103/291 [00:26<00:57, 3.27it/s] Loading 0: 36%|███▌ | 104/291 [00:27<01:12, 2.58it/s] Loading 0: 37%|███▋ | 107/291 [00:27<00:41, 4.38it/s] Loading 0: 37%|███▋ | 108/291 [00:27<00:39, 4.62it/s] Loading 0: 37%|███▋ | 109/291 [00:27<00:34, 5.21it/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 [00:29<01:08, 2.59it/s] Loading 0: 40%|███▉ | 116/291 [00:29<00:39, 4.44it/s] Loading 0: 40%|████ | 117/291 [00:30<00:37, 4.68it/s] Loading 0: 41%|████ | 118/291 [00:30<00:32, 5.26it/s] Loading 0: 41%|████ | 120/291 [00:30<00:38, 4.38it/s] Loading 0: 42%|████▏ | 121/291 [00:31<00:51, 3.30it/s] Loading 0: 42%|████▏ | 122/291 [00:31<01:05, 2.57it/s] Loading 0: 43%|████▎ | 125/291 [00:32<00:37, 4.38it/s] Loading 0: 43%|████▎ | 126/291 [00:32<00:35, 4.62it/s] Loading 0: 44%|████▎ | 127/291 [00:32<00:31, 5.20it/s] Loading 0: 44%|████▍ | 129/291 [00:33<00:37, 4.35it/s] Loading 0: 45%|████▍ | 130/291 [00:33<00:48, 3.29it/s] Loading 0: 45%|████▌ | 131/291 [00:34<01:01, 2.60it/s] Loading 0: 46%|████▌ | 134/291 [00:34<00:35, 4.40it/s] Loading 0: 46%|████▋ | 135/291 [00:34<00:33, 4.65it/s] Loading 0: 47%|████▋ | 136/291 [00:34<00:29, 5.25it/s] Loading 0: 47%|████▋ | 138/291 [00:35<00:34, 4.38it/s] Loading 0: 48%|████▊ | 139/291 [00:35<00:46, 3.30it/s] Loading 0: 48%|████▊ | 140/291 [00:36<00:58, 2.60it/s] Loading 0: 49%|████▉ | 143/291 [00:36<00:33, 4.40it/s] Loading 0: 49%|████▉ | 144/291 [00:36<00:31, 4.65it/s] Loading 0: 50%|████▉ | 145/291 [00:37<00:27, 5.24it/s] Loading 0: 51%|█████ | 147/291 [00:37<00:32, 4.37it/s] Loading 0: 51%|█████ | 148/291 [00:38<00:43, 3.30it/s] Loading 0: 51%|█████ | 149/291 [00:38<00:55, 2.55it/s] Loading 0: 52%|█████▏ | 152/291 [00:39<00:31, 4.39it/s] Loading 0: 53%|█████▎ | 153/291 [00:39<00:29, 4.63it/s] Loading 0: 53%|█████▎ | 154/291 [00:39<00:26, 5.23it/s] Loading 0: 54%|█████▎ | 156/291 [00:39<00:30, 4.38it/s] Loading 0: 54%|█████▍ | 157/291 [00:40<00:40, 3.30it/s] Loading 0: 54%|█████▍ | 158/291 [00:41<00:51, 2.61it/s] Loading 0: 55%|█████▌ | 161/291 [00:41<00:29, 4.48it/s] Loading 0: 56%|█████▌ | 162/291 [00:41<00:27, 4.71it/s] Loading 0: 56%|█████▌ | 163/291 [00:41<00:24, 5.29it/s] Loading 0: 57%|█████▋ | 165/291 [00:42<00:28, 4.39it/s] Loading 0: 57%|█████▋ | 166/291 [00:42<00:37, 3.30it/s] Loading 0: 57%|█████▋ | 167/291 [00:43<00:47, 2.61it/s] Loading 0: 58%|█████▊ | 170/291 [00:43<00:26, 4.49it/s] Loading 0: 59%|█████▉ | 171/291 [00:43<00:25, 4.71it/s] Loading 0: 59%|█████▉ | 172/291 [00:43<00:22, 5.21it/s] Loading 0: 59%|█████▉ | 173/291 [00:44<00:33, 3.53it/s] Loading 0: 60%|██████ | 175/291 [00:44<00:24, 4.77it/s] Loading 0: 60%|██████ | 176/291 [00:44<00:22, 5.01it/s] Loading 0: 61%|██████ | 177/291 [00:44<00:20, 5.67it/s] Loading 0: 62%|██████▏ | 179/291 [00:45<00:24, 4.49it/s] Loading 0: 62%|██████▏ | 180/291 [00:46<00:33, 3.31it/s] Loading 0: 62%|██████▏ | 181/291 [00:46<00:42, 2.60it/s] Loading 0: 63%|██████▎ | 184/291 [00:46<00:23, 4.55it/s] Loading 0: 64%|██████▎ | 185/291 [00:47<00:22, 4.78it/s] Loading 0: 64%|██████▍ | 186/291 [00:47<00:19, 5.39it/s] Loading 0: 64%|██████▍ | 187/291 [00:47<00:19, 5.40it/s] Loading 0: 65%|██████▍ | 188/291 [00:47<00:29, 3.53it/s] Loading 0: 65%|██████▍ | 189/291 [00:48<00:38, 2.63it/s] Loading 0: 66%|██████▌ | 192/291 [00:49<00:27, 3.57it/s] Loading 0: 66%|██████▋ | 193/291 [00:49<00:33, 2.93it/s] Loading 0: 67%|██████▋ | 194/291 [00:50<00:39, 2.45it/s] Loading 0: 68%|██████▊ | 197/291 [00:50<00:22, 4.19it/s] Loading 0: 68%|██████▊ | 198/291 [00:50<00:20, 4.45it/s] Loading 0: 68%|██████▊ | 199/291 [00:50<00:18, 5.04it/s] Loading 0: 69%|██████▉ | 201/291 [00:51<00:20, 4.29it/s] Loading 0: 69%|██████▉ | 202/291 [00:51<00:27, 3.27it/s] Loading 0: 70%|██████▉ | 203/291 [00:52<00:33, 2.60it/s] Loading 0: 71%|███████ | 206/291 [00:52<00:19, 4.40it/s] Loading 0: 71%|███████ | 207/291 [00:52<00:18, 4.64it/s] Loading 0: 71%|███████▏ | 208/291 [00:53<00:16, 5.13it/s] Loading 0: 72%|███████▏ | 210/291 [00:53<00:18, 4.33it/s] Loading 0: 73%|███████▎ | 211/291 [00:54<00:24, 3.27it/s] Loading 0: 73%|███████▎ | 212/291 [00:54<00:30, 2.60it/s] Loading 0: 74%|███████▍ | 215/291 [00:55<00:17, 4.46it/s] Loading 0: 74%|███████▍ | 216/291 [00:55<00:15, 4.69it/s] Loading 0: 75%|███████▍ | 217/291 [00:55<00:14, 5.25it/s] Loading 0: 75%|███████▌ | 219/291 [00:55<00:16, 4.37it/s] Loading 0: 76%|███████▌ | 220/291 [00:56<00:21, 3.30it/s] Loading 0: 76%|███████▌ | 221/291 [00:57<00:26, 2.60it/s] Loading 0: 77%|███████▋ | 224/291 [00:57<00:15, 4.41it/s] Loading 0: 77%|███████▋ | 225/291 [00:57<00:14, 4.65it/s] Loading 0: 78%|███████▊ | 226/291 [00:57<00:12, 5.23it/s] Loading 0: 78%|███████▊ | 228/291 [00:58<00:14, 4.36it/s] Loading 0: 79%|███████▊ | 229/291 [00:58<00:18, 3.27it/s] Loading 0: 79%|███████▉ | 230/291 [00:59<00:23, 2.60it/s] Loading 0: 80%|████████ | 233/291 [00:59<00:12, 4.48it/s] Loading 0: 80%|████████ | 234/291 [00:59<00:12, 4.71it/s] Loading 0: 81%|████████ | 235/291 [00:59<00:10, 5.31it/s] Loading 0: 81%|████████▏ | 237/291 [01:00<00:12, 4.41it/s] Loading 0: 82%|████████▏ | 238/291 [01:01<00:15, 3.32it/s] Loading 0: 82%|████████▏ | 239/291 [01:01<00:19, 2.63it/s] Loading 0: 83%|████████▎ | 242/291 [01:01<00:10, 4.52it/s] Loading 0: 84%|████████▎ | 243/291 [01:02<00:10, 4.74it/s] Loading 0: 84%|████████▍ | 244/291 [01:02<00:08, 5.32it/s] Loading 0: 85%|████████▍ | 246/291 [01:02<00:10, 4.35it/s] Loading 0: 85%|████████▍ | 247/291 [01:03<00:13, 3.29it/s] Loading 0: 85%|████████▌ | 248/291 [01:04<00:16, 2.61it/s] Loading 0: 86%|████████▋ | 251/291 [01:04<00:09, 4.43it/s] Loading 0: 87%|████████▋ | 252/291 [01:04<00:08, 4.66it/s] Loading 0: 87%|████████▋ | 253/291 [01:04<00:07, 5.22it/s] Loading 0: 88%|████████▊ | 255/291 [01:05<00:08, 4.36it/s] Loading 0: 88%|████████▊ | 256/291 [01:05<00:10, 3.29it/s] Loading 0: 88%|████████▊ | 257/291 [01:06<00:13, 2.61it/s] Loading 0: 89%|████████▉ | 260/291 [01:06<00:06, 4.48it/s] Loading 0: 90%|████████▉ | 261/291 [01:06<00:06, 4.72it/s] Loading 0: 90%|█████████ | 262/291 [01:06<00:05, 5.32it/s] Loading 0: 91%|█████████ | 264/291 [01:07<00:06, 4.41it/s] Loading 0: 91%|█████████ | 265/291 [01:07<00:07, 3.32it/s] Loading 0: 91%|█████████▏| 266/291 [01:08<00:09, 2.62it/s] Loading 0: 92%|█████████▏| 269/291 [01:08<00:04, 4.43it/s] Loading 0: 93%|█████████▎| 270/291 [01:08<00:04, 4.68it/s] Loading 0: 93%|█████████▎| 271/291 [01:09<00:03, 5.22it/s] Loading 0: 94%|█████████▍| 273/291 [01:09<00:04, 4.36it/s] Loading 0: 94%|█████████▍| 274/291 [01:10<00:05, 3.30it/s] Loading 0: 95%|█████████▍| 275/291 [01:10<00:06, 2.61it/s] Loading 0: 96%|█████████▌| 278/291 [01:11<00:02, 4.50it/s] Loading 0: 96%|█████████▌| 279/291 [01:11<00:02, 4.73it/s] Loading 0: 96%|█████████▌| 280/291 [01:11<00:02, 5.32it/s] Loading 0: 97%|█████████▋| 281/291 [01:11<00:02, 3.56it/s] Loading 0: 97%|█████████▋| 282/291 [01:12<00:03, 2.70it/s] Loading 0: 98%|█████████▊| 284/291 [01:12<00:01, 3.87it/s] Loading 0: 98%|█████████▊| 285/291 [01:12<00:01, 4.22it/s] Loading 0: 98%|█████████▊| 286/291 [01:12<00:01, 4.90it/s] Loading 0: 99%|█████████▊| 287/291 [01:13<00:00, 5.08it/s] Loading 0: 99%|█████████▉| 288/291 [01:13<00:00, 3.33it/s]
Job alexdaoud-trainer-bagir-1971-v1-mkmlizer completed after 145.97s with status: succeeded
Stopping job with name alexdaoud-trainer-bagir-1971-v1-mkmlizer
Pipeline stage MKMLizer completed in 146.50s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.17s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service alexdaoud-trainer-bagir-1971-v1
Waiting for inference service alexdaoud-trainer-bagir-1971-v1 to be ready
Inference service alexdaoud-trainer-bagir-1971-v1 ready after 210.7488112449646s
Pipeline stage MKMLDeployer completed in 211.33s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 4.172849416732788s
Received healthy response to inference request in 3.7789106369018555s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Received healthy response to inference request in 3.0925285816192627s
Received healthy response to inference request in 2.949739694595337s
Received healthy response to inference request in 6.4130144119262695s
5 requests
0 failed requests
5th percentile: 2.978297472000122
10th percentile: 3.0068552494049072
20th percentile: 3.0639708042144775
30th percentile: 3.2298049926757812
40th percentile: 3.5043578147888184
50th percentile: 3.7789106369018555
60th percentile: 3.9364861488342284
70th percentile: 4.094061660766601
80th percentile: 4.620882415771485
90th percentile: 5.516948413848877
95th percentile: 5.964981412887573
99th percentile: 6.32340781211853
mean time: 4.081408548355102
%s, retrying in %s seconds...
Received healthy response to inference request in 4.102492332458496s
Received healthy response to inference request in 2.6918177604675293s
Received healthy response to inference request in 3.147243022918701s
Received healthy response to inference request in 4.927749395370483s
Received healthy response to inference request in 3.813133955001831s
5 requests
0 failed requests
5th percentile: 2.7829028129577638
10th percentile: 2.8739878654479982
20th percentile: 3.0561579704284667
30th percentile: 3.2804212093353273
40th percentile: 3.546777582168579
50th percentile: 3.813133955001831
60th percentile: 3.9288773059844972
70th percentile: 4.044620656967163
80th percentile: 4.267543745040894
90th percentile: 4.597646570205688
95th percentile: 4.762697982788086
99th percentile: 4.894739112854004
mean time: 3.736487293243408
%s, retrying in %s seconds...
Received healthy response to inference request in 3.9305579662323s
Received healthy response to inference request in 2.990488290786743s
Received healthy response to inference request in 2.7272446155548096s
Received healthy response to inference request in 3.411628007888794s
Received healthy response to inference request in 3.702521562576294s
5 requests
0 failed requests
5th percentile: 2.7798933506011965
10th percentile: 2.832542085647583
20th percentile: 2.9378395557403563
30th percentile: 3.0747162342071532
40th percentile: 3.243172121047974
50th percentile: 3.411628007888794
60th percentile: 3.527985429763794
70th percentile: 3.6443428516387937
80th percentile: 3.7481288433074953
90th percentile: 3.8393434047698975
95th percentile: 3.8849506855010985
99th percentile: 3.9214365100860595
mean time: 3.352488088607788
Pipeline stage StressChecker completed in 60.04s
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 2.84s
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 2.01s
Shutdown handler de-registered
alexdaoud-trainer-bagir-_1971_v1 status is now deployed due to DeploymentManager action
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
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 0.13s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-1971-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-1971-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-1971-v1-profiler ready after 210.48788595199585s
Pipeline stage MKMLProfilerDeployer completed in 210.93s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3034c0d2420e2b2f70b452b24db92892-deplo2dv2j:/code/chaiverse_profiler_1734300648 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba3034c0d2420e2b2f70b452b24db92892-deplo2dv2j --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734300648 && 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_1734300648/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3034c0d2420e2b2f70b452b24db92892-deplo2dv2j:/code/chaiverse_profiler_1734303445 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba3034c0d2420e2b2f70b452b24db92892-deplo2dv2j --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734303445 && 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_1734303445/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1971-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-1971-v1-profiler
Service alexdaoud-trainer-bagir-1971-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.64s
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1971-v1-profiler is running
Skipping teardown as no inference service was found
Pipeline stage MKMLProfilerDeleter completed in 2.29s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.13s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-1971-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-1971-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-1971-v1-profiler ready after 210.48367762565613s
Pipeline stage MKMLProfilerDeployer completed in 210.79s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3034c0d2420e2b2f70b452b24db92892-deplop2vfh:/code/chaiverse_profiler_1734304274 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba3034c0d2420e2b2f70b452b24db92892-deplop2vfh --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734304274 && 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_1734304274/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3034c0d2420e2b2f70b452b24db92892-deplop2vfh:/code/chaiverse_profiler_1734307072 --namespace tenant-chaiml-guanaco
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3034c0d2420e2b2f70b452b24db92892-deplop2vfh:/code/chaiverse_profiler_1734307073 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba3034c0d2420e2b2f70b452b24db92892-deplop2vfh --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734307073 && 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_1734307073/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1971-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-1971-v1-profiler
Service alexdaoud-trainer-bagir-1971-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.28s
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1971-v1-profiler is running
Skipping teardown as no inference service was found
Pipeline stage MKMLProfilerDeleter completed in 2.36s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.13s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-1971-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-1971-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-1971-v1-profiler ready after 70.273606300354s
Pipeline stage MKMLProfilerDeployer completed in 70.63s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3034c0d2420e2b2f70b452b24db92892-deplorlh9s:/code/chaiverse_profiler_1734307759 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba3034c0d2420e2b2f70b452b24db92892-deplorlh9s --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734307759 && 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_1734307759/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3034c0d2420e2b2f70b452b24db92892-deplorlh9s:/code/chaiverse_profiler_1734310535 --namespace tenant-chaiml-guanaco
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3034c0d2420e2b2f70b452b24db92892-deplorlh9s:/code/chaiverse_profiler_1734310536 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba3034c0d2420e2b2f70b452b24db92892-deplorlh9s --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734310536 && 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_1734310536/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1971-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-1971-v1-profiler
Service alexdaoud-trainer-bagir-1971-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.64s
Shutdown handler de-registered
alexdaoud-trainer-bagir-_1971_v1 status is now inactive due to auto deactivation removed underperforming models