riverise-model-trained-o_9186

developer_uid: Riverise
submission_id: riverise-model-trained-o_9186_v2
model_name: sonnet_and_daily
model_group: Riverise/model_trained_o
status: torndown
timestamp: 2024-08-31T07:25:34+00:00
num_battles: 10787
num_wins: 5408
celo_rating: 1235.03
family_friendly_score: 0.0
submission_type: basic
model_repo: Riverise/model_trained_on_sonnet_and_daily
model_architecture: LlamaForCausalLM
model_num_parameters: 8030261248.0
best_of: 16
max_input_tokens: 512
max_output_tokens: 64
display_name: sonnet_and_daily
is_internal_developer: False
language_model: Riverise/model_trained_on_sonnet_and_daily
model_size: 8B
ranking_group: single
us_pacific_date: 2024-08-31
win_ratio: 0.5013442106238991
generation_params: {'temperature': 1.15, 'top_p': 0.9, 'min_p': 0.1, 'top_k': 60, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 512, 'best_of': 16, 'max_output_tokens': 64}
formatter: {'memory_template': "{bot_name}'s Persona: {memory}\n####\n", 'prompt_template': '{prompt}\n<START>\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '{bot_name}:', 'truncate_by_message': False}
Resubmit model
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name riverise-model-trained-o-9186-v2-mkmlizer
Waiting for job on riverise-model-trained-o-9186-v2-mkmlizer to finish
Stopping job with name riverise-model-trained-o-9186-v2-mkmlizer
%s, retrying in %s seconds...
Starting job with name riverise-model-trained-o-9186-v2-mkmlizer
Waiting for job on riverise-model-trained-o-9186-v2-mkmlizer to finish
riverise-model-trained-o-9186-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
riverise-model-trained-o-9186-v2-mkmlizer: ║     _____            __           __                                ║
riverise-model-trained-o-9186-v2-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
riverise-model-trained-o-9186-v2-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
riverise-model-trained-o-9186-v2-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
riverise-model-trained-o-9186-v2-mkmlizer: ║       /___/                                                         ║
riverise-model-trained-o-9186-v2-mkmlizer: ║                                                                     ║
riverise-model-trained-o-9186-v2-mkmlizer: ║  Version: 0.10.1                                                    ║
riverise-model-trained-o-9186-v2-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
riverise-model-trained-o-9186-v2-mkmlizer: ║  https://mk1.ai                                                     ║
riverise-model-trained-o-9186-v2-mkmlizer: ║                                                                     ║
riverise-model-trained-o-9186-v2-mkmlizer: ║  The license key for the current software has been verified as      ║
riverise-model-trained-o-9186-v2-mkmlizer: ║  belonging to:                                                      ║
riverise-model-trained-o-9186-v2-mkmlizer: ║                                                                     ║
riverise-model-trained-o-9186-v2-mkmlizer: ║  Chai Research Corp.                                                ║
riverise-model-trained-o-9186-v2-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
riverise-model-trained-o-9186-v2-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
riverise-model-trained-o-9186-v2-mkmlizer: ║                                                                     ║
riverise-model-trained-o-9186-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
riverise-model-trained-o-9186-v2-mkmlizer: Downloaded to shared memory in 62.668s
riverise-model-trained-o-9186-v2-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpf95jszw7, device:0
riverise-model-trained-o-9186-v2-mkmlizer: Saving flywheel model at /dev/shm/model_cache
riverise-model-trained-o-9186-v2-mkmlizer: quantized model in 28.482s
riverise-model-trained-o-9186-v2-mkmlizer: Processed model Riverise/model_trained_on_sonnet_and_daily in 91.150s
riverise-model-trained-o-9186-v2-mkmlizer: creating bucket guanaco-mkml-models
riverise-model-trained-o-9186-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
riverise-model-trained-o-9186-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/riverise-model-trained-o-9186-v2
riverise-model-trained-o-9186-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/riverise-model-trained-o-9186-v2/config.json
riverise-model-trained-o-9186-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/riverise-model-trained-o-9186-v2/special_tokens_map.json
riverise-model-trained-o-9186-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/riverise-model-trained-o-9186-v2/tokenizer_config.json
riverise-model-trained-o-9186-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/riverise-model-trained-o-9186-v2/tokenizer.json
riverise-model-trained-o-9186-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/riverise-model-trained-o-9186-v2/flywheel_model.0.safetensors
riverise-model-trained-o-9186-v2-mkmlizer: 
Loading 0:   0%|          | 0/291 [00:00<?, ?it/s]
Loading 0:   2%|▏         | 5/291 [00:00<00:11, 25.61it/s]
Loading 0:   4%|▍         | 12/291 [00:00<00:06, 40.38it/s]
Loading 0:   6%|▌         | 17/291 [00:00<00:07, 38.47it/s]
Loading 0:   8%|▊         | 22/291 [00:00<00:06, 38.81it/s]
Loading 0:   9%|▉         | 27/291 [00:00<00:06, 41.58it/s]
Loading 0:  11%|█         | 32/291 [00:00<00:06, 41.93it/s]
Loading 0:  13%|█▎        | 37/291 [00:01<00:09, 26.93it/s]
Loading 0:  14%|█▍        | 41/291 [00:01<00:09, 25.99it/s]
Loading 0:  16%|█▋        | 48/291 [00:01<00:07, 33.71it/s]
Loading 0:  18%|█▊        | 52/291 [00:01<00:07, 33.82it/s]
Loading 0:  20%|█▉        | 57/291 [00:01<00:06, 37.32it/s]
Loading 0:  21%|██▏       | 62/291 [00:01<00:06, 35.20it/s]
Loading 0:  23%|██▎       | 66/291 [00:01<00:06, 35.44it/s]
Loading 0:  24%|██▍       | 70/291 [00:02<00:06, 33.12it/s]
Loading 0:  25%|██▌       | 74/291 [00:02<00:06, 32.86it/s]
Loading 0:  27%|██▋       | 78/291 [00:02<00:06, 32.78it/s]
Loading 0:  28%|██▊       | 82/291 [00:02<00:08, 23.57it/s]
Loading 0:  30%|██▉       | 86/291 [00:02<00:07, 26.43it/s]
Loading 0:  31%|███▏      | 91/291 [00:02<00:06, 29.82it/s]
Loading 0:  33%|███▎      | 95/291 [00:02<00:06, 31.09it/s]
Loading 0:  34%|███▍      | 100/291 [00:03<00:05, 33.26it/s]
Loading 0:  36%|███▋      | 106/291 [00:03<00:05, 35.70it/s]
Loading 0:  38%|███▊      | 110/291 [00:03<00:05, 32.65it/s]
Loading 0:  40%|███▉      | 116/291 [00:03<00:04, 38.19it/s]
Loading 0:  42%|████▏     | 122/291 [00:03<00:04, 41.72it/s]
Loading 0:  44%|████▎     | 127/291 [00:03<00:04, 38.51it/s]
Loading 0:  46%|████▌     | 133/291 [00:03<00:04, 34.24it/s]
Loading 0:  47%|████▋     | 137/291 [00:04<00:04, 31.76it/s]
Loading 0:  48%|████▊     | 141/291 [00:04<00:05, 29.17it/s]
Loading 0:  51%|█████     | 147/291 [00:04<00:04, 33.42it/s]
Loading 0:  52%|█████▏    | 151/291 [00:04<00:04, 32.37it/s]
Loading 0:  54%|█████▎    | 156/291 [00:04<00:03, 36.15it/s]
Loading 0:  55%|█████▍    | 160/291 [00:04<00:03, 34.74it/s]
Loading 0:  57%|█████▋    | 165/291 [00:04<00:03, 37.04it/s]
Loading 0:  58%|█████▊    | 169/291 [00:05<00:03, 34.71it/s]
Loading 0:  60%|█████▉    | 174/291 [00:05<00:03, 38.32it/s]
Loading 0:  61%|██████    | 178/291 [00:05<00:03, 37.15it/s]
Loading 0:  64%|██████▎   | 185/291 [00:05<00:02, 41.41it/s]
Loading 0:  65%|██████▌   | 190/291 [00:05<00:03, 28.52it/s]
Loading 0:  67%|██████▋   | 194/291 [00:05<00:03, 27.55it/s]
Loading 0:  69%|██████▉   | 201/291 [00:05<00:02, 33.94it/s]
Loading 0:  70%|███████   | 205/291 [00:06<00:02, 33.10it/s]
Loading 0:  72%|███████▏  | 210/291 [00:06<00:02, 36.82it/s]
Loading 0:  74%|███████▍  | 215/291 [00:06<00:02, 37.23it/s]
Loading 0:  75%|███████▌  | 219/291 [00:06<00:01, 36.94it/s]
Loading 0:  77%|███████▋  | 223/291 [00:06<00:01, 34.96it/s]
Loading 0:  78%|███████▊  | 227/291 [00:06<00:01, 35.76it/s]
Loading 0:  79%|███████▉  | 231/291 [00:06<00:01, 34.28it/s]
Loading 0:  81%|████████  | 235/291 [00:07<00:02, 26.35it/s]
Loading 0:  82%|████████▏ | 239/291 [00:07<00:02, 24.41it/s]
Loading 0:  85%|████████▍ | 246/291 [00:07<00:01, 31.39it/s]
Loading 0:  86%|████████▌ | 250/291 [00:07<00:01, 31.43it/s]
Loading 0:  88%|████████▊ | 255/291 [00:07<00:01, 35.07it/s]
Loading 0:  89%|████████▉ | 259/291 [00:07<00:00, 34.54it/s]
Loading 0:  91%|█████████ | 264/291 [00:07<00:00, 38.26it/s]
Loading 0:  92%|█████████▏| 269/291 [00:07<00:00, 38.22it/s]
Loading 0:  94%|█████████▍| 274/291 [00:08<00:00, 37.97it/s]
Loading 0:  96%|█████████▌| 278/291 [00:08<00:00, 37.16it/s]
Loading 0:  97%|█████████▋| 283/291 [00:08<00:00, 39.79it/s]
Loading 0:  99%|█████████▉| 288/291 [00:13<00:01,  2.77it/s]
Loading 0: 100%|██████████| 291/291 [00:13<00:00,  3.42it/s]
                                                            
Job riverise-model-trained-o-9186-v2-mkmlizer completed after 115.71s with status: succeeded
Stopping job with name riverise-model-trained-o-9186-v2-mkmlizer
Pipeline stage MKMLizer completed in 117.26s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.11s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service riverise-model-trained-o-9186-v2
Waiting for inference service riverise-model-trained-o-9186-v2 to be ready
Inference service riverise-model-trained-o-9186-v2 ready after 191.05276250839233s
Pipeline stage MKMLDeployer completed in 191.42s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 3.3743650913238525s
Received healthy response to inference request in 3.4440929889678955s
Received healthy response to inference request in 2.4770889282226562s
Received healthy response to inference request in 1.4366438388824463s
Received healthy response to inference request in 1.2667467594146729s
5 requests
0 failed requests
5th percentile: 1.3007261753082275
10th percentile: 1.3347055912017822
20th percentile: 1.4026644229888916
30th percentile: 1.6447328567504882
40th percentile: 2.0609108924865724
50th percentile: 2.4770889282226562
60th percentile: 2.8359993934631347
70th percentile: 3.194909858703613
80th percentile: 3.388310670852661
90th percentile: 3.4162018299102783
95th percentile: 3.430147409439087
99th percentile: 3.4413038730621337
mean time: 2.3997875213623048
Pipeline stage StressChecker completed in 12.75s
run pipeline stage %s
Running pipeline stage TriggerMKMLProfilingPipeline
starting trigger_guanaco_pipeline %s
Pipeline stage TriggerMKMLProfilingPipeline completed in 4.40s
riverise-model-trained-o_9186_v2 status is now deployed due to DeploymentManager action
run pipeline %s
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 riverise-model-trained-o-9186-v2-profiler
Waiting for inference service riverise-model-trained-o-9186-v2-profiler to be ready
Inference service riverise-model-trained-o-9186-v2-profiler ready after 190.52065181732178s
Pipeline stage MKMLProfilerDeployer completed in 190.93s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
script pods %s
Pipeline stage MKMLProfilerRunner completed in 0.36s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service riverise-model-trained-o-9186-v2-profiler is running
Tearing down inference service riverise-model-trained-o-9186-v2-profiler
Service riverise-model-trained-o-9186-v2-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 1.95s
riverise-model-trained-o_9186_v2 status is now inactive due to auto deactivation removed underperforming models
riverise-model-trained-o_9186_v2 status is now torndown due to DeploymentManager action