submission_id: rica40325-feedback-7000_v1
developer_uid: rica40325
best_of: 16
celo_rating: 1247.17
display_name: rica40325-feedback-7000_v1
family_friendly_score: 0.0
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}
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': 512, 'best_of': 16, 'max_output_tokens': 64}
gpu_counts: {'NVIDIA RTX A5000': 1}
is_internal_developer: False
language_model: rica40325/feedback_7000
latencies: [{'batch_size': 1, 'throughput': 0.9218640214281145, 'latency_mean': 1.0846773529052733, 'latency_p50': 1.0797662734985352, 'latency_p90': 1.2191179037094115}, {'batch_size': 4, 'throughput': 1.8281990275475044, 'latency_mean': 2.1816142916679384, 'latency_p50': 2.189477801322937, 'latency_p90': 2.4715282678604127}, {'batch_size': 5, 'throughput': 1.892040693158459, 'latency_mean': 2.629677965641022, 'latency_p50': 2.660887360572815, 'latency_p90': 2.9338236808776856}, {'batch_size': 8, 'throughput': 2.0579337103301922, 'latency_mean': 3.862643687725067, 'latency_p50': 3.8872724771499634, 'latency_p90': 4.317816996574401}, {'batch_size': 10, 'throughput': 2.0626430839556797, 'latency_mean': 4.79650648355484, 'latency_p50': 4.798105001449585, 'latency_p90': 5.567922163009643}, {'batch_size': 12, 'throughput': 2.059600220551777, 'latency_mean': 5.752856893539429, 'latency_p50': 5.802332520484924, 'latency_p90': 6.642658352851868}, {'batch_size': 15, 'throughput': 2.043122877142347, 'latency_mean': 7.1838078272342685, 'latency_p50': 7.317056894302368, 'latency_p90': 8.01842279434204}]
max_input_tokens: 512
max_output_tokens: 64
model_architecture: LlamaForCausalLM
model_group: rica40325/feedback_7000
model_name: rica40325-feedback-7000_v1
model_num_parameters: 8030261248.0
model_repo: rica40325/feedback_7000
model_size: 8B
num_battles: 11249
num_wins: 5726
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 2.06
timestamp: 2024-09-09T09:24:35+00:00
us_pacific_date: 2024-09-09
win_ratio: 0.5090230242688238
Download Preference Data
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 rica40325-feedback-7000-v1-mkmlizer
Waiting for job on rica40325-feedback-7000-v1-mkmlizer to finish
rica40325-feedback-7000-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
rica40325-feedback-7000-v1-mkmlizer: ║ _____ __ __ ║
rica40325-feedback-7000-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
rica40325-feedback-7000-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
rica40325-feedback-7000-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
rica40325-feedback-7000-v1-mkmlizer: ║ /___/ ║
rica40325-feedback-7000-v1-mkmlizer: ║ ║
rica40325-feedback-7000-v1-mkmlizer: ║ Version: 0.10.1 ║
rica40325-feedback-7000-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
rica40325-feedback-7000-v1-mkmlizer: ║ https://mk1.ai ║
rica40325-feedback-7000-v1-mkmlizer: ║ ║
rica40325-feedback-7000-v1-mkmlizer: ║ The license key for the current software has been verified as ║
rica40325-feedback-7000-v1-mkmlizer: ║ belonging to: ║
rica40325-feedback-7000-v1-mkmlizer: ║ ║
rica40325-feedback-7000-v1-mkmlizer: ║ Chai Research Corp. ║
rica40325-feedback-7000-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
rica40325-feedback-7000-v1-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
rica40325-feedback-7000-v1-mkmlizer: ║ ║
rica40325-feedback-7000-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
rica40325-feedback-7000-v1-mkmlizer: Downloaded to shared memory in 60.774s
rica40325-feedback-7000-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpqjltp04s, device:0
rica40325-feedback-7000-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
rica40325-feedback-7000-v1-mkmlizer: quantized model in 29.267s
rica40325-feedback-7000-v1-mkmlizer: Processed model rica40325/feedback_7000 in 90.041s
rica40325-feedback-7000-v1-mkmlizer: creating bucket guanaco-mkml-models
rica40325-feedback-7000-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
rica40325-feedback-7000-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/rica40325-feedback-7000-v1
rica40325-feedback-7000-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/rica40325-feedback-7000-v1/config.json
rica40325-feedback-7000-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/rica40325-feedback-7000-v1/special_tokens_map.json
rica40325-feedback-7000-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/rica40325-feedback-7000-v1/tokenizer_config.json
rica40325-feedback-7000-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/rica40325-feedback-7000-v1/tokenizer.json
rica40325-feedback-7000-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/rica40325-feedback-7000-v1/flywheel_model.0.safetensors
rica40325-feedback-7000-v1-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 2%|▏ | 5/291 [00:00<00:11, 25.77it/s] Loading 0: 4%|▍ | 12/291 [00:00<00:07, 35.91it/s] Loading 0: 5%|▌ | 16/291 [00:00<00:08, 32.80it/s] Loading 0: 7%|▋ | 21/291 [00:00<00:07, 35.72it/s] Loading 0: 9%|▊ | 25/291 [00:00<00:08, 32.49it/s] Loading 0: 10%|█ | 30/291 [00:00<00:07, 36.12it/s] Loading 0: 12%|█▏ | 34/291 [00:01<00:10, 23.98it/s] Loading 0: 13%|█▎ | 37/291 [00:01<00:10, 23.23it/s] Loading 0: 14%|█▍ | 41/291 [00:01<00:10, 23.09it/s] Loading 0: 16%|█▋ | 48/291 [00:01<00:07, 31.25it/s] Loading 0: 18%|█▊ | 52/291 [00:01<00:07, 30.88it/s] Loading 0: 20%|█▉ | 57/291 [00:01<00:06, 33.60it/s] Loading 0: 21%|██ | 61/291 [00:02<00:07, 32.22it/s] Loading 0: 23%|██▎ | 66/291 [00:02<00:06, 33.56it/s] Loading 0: 24%|██▍ | 70/291 [00:02<00:06, 31.84it/s] Loading 0: 25%|██▌ | 74/291 [00:02<00:06, 31.83it/s] Loading 0: 27%|██▋ | 78/291 [00:02<00:06, 32.07it/s] Loading 0: 28%|██▊ | 82/291 [00:02<00:09, 23.20it/s] Loading 0: 29%|██▉ | 85/291 [00:02<00:08, 23.40it/s] Loading 0: 31%|███ | 90/291 [00:03<00:07, 27.55it/s] Loading 0: 32%|███▏ | 94/291 [00:03<00:07, 27.59it/s] Loading 0: 34%|███▍ | 99/291 [00:03<00:06, 31.51it/s] Loading 0: 35%|███▌ | 103/291 [00:03<00:06, 30.93it/s] Loading 0: 37%|███▋ | 108/291 [00:03<00:05, 33.28it/s] Loading 0: 38%|███▊ | 112/291 [00:03<00:05, 31.87it/s] Loading 0: 40%|███▉ | 116/291 [00:03<00:05, 32.59it/s] Loading 0: 42%|████▏ | 122/291 [00:03<00:04, 35.92it/s] Loading 0: 44%|████▎ | 127/291 [00:04<00:04, 33.87it/s] Loading 0: 46%|████▌ | 133/291 [00:04<00:05, 30.03it/s] Loading 0: 47%|████▋ | 137/291 [00:04<00:05, 29.80it/s] Loading 0: 48%|████▊ | 141/291 [00:04<00:05, 27.55it/s] Loading 0: 51%|█████ | 147/291 [00:04<00:04, 31.58it/s] Loading 0: 52%|█████▏ | 151/291 [00:04<00:04, 30.72it/s] Loading 0: 54%|█████▎ | 156/291 [00:05<00:04, 33.26it/s] Loading 0: 55%|█████▍ | 160/291 [00:05<00:04, 31.77it/s] Loading 0: 57%|█████▋ | 165/291 [00:05<00:03, 34.63it/s] Loading 0: 58%|█████▊ | 169/291 [00:05<00:03, 33.25it/s] Loading 0: 60%|█████▉ | 174/291 [00:05<00:03, 35.37it/s] Loading 0: 61%|██████ | 178/291 [00:05<00:03, 33.00it/s] Loading 0: 63%|██████▎ | 183/291 [00:05<00:02, 36.33it/s] Loading 0: 64%|██████▍ | 187/291 [00:06<00:03, 26.40it/s] Loading 0: 66%|██████▌ | 191/291 [00:06<00:03, 27.31it/s] Loading 0: 67%|██████▋ | 195/291 [00:06<00:03, 26.29it/s] Loading 0: 68%|██████▊ | 199/291 [00:06<00:03, 28.97it/s] Loading 0: 70%|██████▉ | 203/291 [00:06<00:03, 26.68it/s] Loading 0: 72%|███████▏ | 210/291 [00:06<00:02, 33.43it/s] Loading 0: 74%|███████▎ | 214/291 [00:07<00:02, 31.72it/s] Loading 0: 75%|███████▌ | 219/291 [00:07<00:02, 34.48it/s] Loading 0: 77%|███████▋ | 223/291 [00:07<00:02, 33.21it/s] Loading 0: 78%|███████▊ | 227/291 [00:07<00:01, 33.78it/s] Loading 0: 79%|███████▉ | 231/291 [00:07<00:01, 34.13it/s] Loading 0: 81%|████████ | 235/291 [00:07<00:02, 25.34it/s] Loading 0: 82%|████████▏ | 239/291 [00:07<00:02, 24.62it/s] Loading 0: 85%|████████▍ | 246/291 [00:08<00:01, 32.14it/s] Loading 0: 86%|████████▌ | 250/291 [00:08<00:01, 31.93it/s] Loading 0: 88%|████████▊ | 255/291 [00:08<00:01, 34.64it/s] Loading 0: 89%|████████▉ | 259/291 [00:08<00:00, 33.15it/s] Loading 0: 91%|█████████ | 264/291 [00:08<00:00, 35.68it/s] Loading 0: 92%|█████████▏| 268/291 [00:08<00:00, 33.68it/s] Loading 0: 94%|█████████▍| 273/291 [00:08<00:00, 36.60it/s] Loading 0: 95%|█████████▌| 277/291 [00:08<00:00, 35.07it/s] Loading 0: 97%|█████████▋| 281/291 [00:09<00:00, 35.18it/s] Loading 0: 98%|█████████▊| 286/291 [00:14<00:01, 2.59it/s] Loading 0: 99%|█████████▉| 289/291 [00:14<00:00, 3.23it/s]
Job rica40325-feedback-7000-v1-mkmlizer completed after 115.37s with status: succeeded
Stopping job with name rica40325-feedback-7000-v1-mkmlizer
Pipeline stage MKMLizer completed in 117.52s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.09s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service rica40325-feedback-7000-v1
Waiting for inference service rica40325-feedback-7000-v1 to be ready
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Inference service rica40325-feedback-7000-v1 ready after 150.45408129692078s
Pipeline stage MKMLDeployer completed in 151.64s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.8933119773864746s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Received healthy response to inference request in 1.4530465602874756s
Received healthy response to inference request in 1.8085644245147705s
Received healthy response to inference request in 2.890165328979492s
Received healthy response to inference request in 2.2777271270751953s
5 requests
0 failed requests
5th percentile: 1.5241501331329346
10th percentile: 1.5952537059783936
20th percentile: 1.7374608516693115
30th percentile: 1.9023969650268555
40th percentile: 2.0900620460510253
50th percentile: 2.2777271270751953
60th percentile: 2.5227024078369142
70th percentile: 2.7676776885986327
80th percentile: 2.8907946586608886
90th percentile: 2.892053318023682
95th percentile: 2.892682647705078
99th percentile: 2.8931861114501953
mean time: 2.2645630836486816
Pipeline stage StressChecker completed in 12.35s
run pipeline stage %s
Running pipeline stage TriggerMKMLProfilingPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
Pipeline stage TriggerMKMLProfilingPipeline completed in 8.48s
Shutdown handler de-registered
rica40325-feedback-7000_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 0.11s
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 rica40325-feedback-7000-v1-profiler
Waiting for inference service rica40325-feedback-7000-v1-profiler to be ready
Inference service rica40325-feedback-7000-v1-profiler ready after 150.36044073104858s
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/rica40325-feedback-7000-v1-profiler-predictor-00001-deploy52bh2:/code/chaiverse_profiler_1725874358 --namespace tenant-chaiml-guanaco
kubectl exec -it rica40325-feedback-7000-v1-profiler-predictor-00001-deploy52bh2 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1725874358 && python profiles.py profile --best_of_n 16 --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 512 --output_tokens 64 --summary /code/chaiverse_profiler_1725874358/summary.json'
kubectl exec -it rica40325-feedback-7000-v1-profiler-predictor-00001-deploy52bh2 --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1725874358/summary.json'
Pipeline stage MKMLProfilerRunner completed in 826.23s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service rica40325-feedback-7000-v1-profiler is running
Tearing down inference service rica40325-feedback-7000-v1-profiler
Service rica40325-feedback-7000-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 1.65s
Shutdown handler de-registered
rica40325-feedback-7000_v1 status is now inactive due to auto deactivation removed underperforming models
rica40325-feedback-7000_v1 status is now torndown due to DeploymentManager action