submission_id: jic062-dpo-v1-3-nemo_v1
developer_uid: chace9580
alignment_samples: 10660
alignment_score: 0.13874507633519248
best_of: 8
celo_rating: 1232.58
display_name: jic062-dpo-v1-3-nemo_v1
formatter: {'memory_template': '[INST]system\n{memory}[/INST]\n', 'prompt_template': '[INST]user\n{prompt}[/INST]\n', 'bot_template': '[INST]assistant\n{bot_name}: {message}[/INST]\n', 'user_template': '[INST]user\n{user_name}: {message}[/INST]\n', 'response_template': '[INST]assistant\n{bot_name}:', 'truncate_by_message': False}
generation_params: {'temperature': 0.75, 'top_p': 1.0, 'min_p': 0.1, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '\n\n', '\nYou:', '[/INST]', '<|im_end|>', '</s>'], 'max_input_tokens': 512, 'best_of': 8, 'max_output_tokens': 64}
gpu_counts: {'NVIDIA RTX A5000': 1}
is_internal_developer: False
language_model: jic062/dpo-v1.3-Nemo
latencies: [{'batch_size': 1, 'throughput': 0.6944579316369992, 'latency_mean': 1.439909384250641, 'latency_p50': 1.444454550743103, 'latency_p90': 1.5938768148422242}, {'batch_size': 3, 'throughput': 1.3482498252565518, 'latency_mean': 2.2174251639842986, 'latency_p50': 2.221012830734253, 'latency_p90': 2.4668855905532836}, {'batch_size': 5, 'throughput': 1.5882380540319903, 'latency_mean': 3.137662442922592, 'latency_p50': 3.1381150484085083, 'latency_p90': 3.537899708747864}, {'batch_size': 6, 'throughput': 1.6459884148748556, 'latency_mean': 3.6246847784519196, 'latency_p50': 3.6564189195632935, 'latency_p90': 4.060385847091675}, {'batch_size': 8, 'throughput': 1.6309501161163789, 'latency_mean': 4.868891962766647, 'latency_p50': 4.86676025390625, 'latency_p90': 5.493939638137817}, {'batch_size': 10, 'throughput': 1.5700528605857258, 'latency_mean': 6.322702369689941, 'latency_p50': 6.314559102058411, 'latency_p90': 7.201911211013794}]
max_input_tokens: 512
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: jic062/dpo-v1.3-Nemo
model_name: jic062-dpo-v1-3-nemo_v1
model_num_parameters: 12772070400.0
model_repo: jic062/dpo-v1.3-Nemo
model_size: 13B
num_battles: 10660
num_wins: 5157
propriety_score: 0.7102085620197585
propriety_total_count: 911.0
ranking_group: single
status: inactive
submission_type: basic
throughput_3p7s: 1.65
timestamp: 2024-09-12T02:56:38+00:00
us_pacific_date: 2024-09-11
win_ratio: 0.48377110694183867
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run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name jic062-dpo-v1-3-nemo-v1-mkmlizer
Waiting for job on jic062-dpo-v1-3-nemo-v1-mkmlizer to finish
jic062-dpo-v1-3-nemo-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ _____ __ __ ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ /___/ ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ Version: 0.10.1 ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ https://mk1.ai ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ The license key for the current software has been verified as ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ belonging to: ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ Chai Research Corp. ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ║ ║
jic062-dpo-v1-3-nemo-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
jic062-dpo-v1-3-nemo-v1-mkmlizer: Downloaded to shared memory in 44.879s
jic062-dpo-v1-3-nemo-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpfw935wu_, device:0
jic062-dpo-v1-3-nemo-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
jic062-dpo-v1-3-nemo-v1-mkmlizer: quantized model in 35.328s
jic062-dpo-v1-3-nemo-v1-mkmlizer: Processed model jic062/dpo-v1.3-Nemo in 80.207s
jic062-dpo-v1-3-nemo-v1-mkmlizer: creating bucket guanaco-mkml-models
jic062-dpo-v1-3-nemo-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
jic062-dpo-v1-3-nemo-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/jic062-dpo-v1-3-nemo-v1
jic062-dpo-v1-3-nemo-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/jic062-dpo-v1-3-nemo-v1/special_tokens_map.json
jic062-dpo-v1-3-nemo-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/jic062-dpo-v1-3-nemo-v1/config.json
jic062-dpo-v1-3-nemo-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/jic062-dpo-v1-3-nemo-v1/tokenizer_config.json
jic062-dpo-v1-3-nemo-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/jic062-dpo-v1-3-nemo-v1/tokenizer.json
jic062-dpo-v1-3-nemo-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/jic062-dpo-v1-3-nemo-v1/flywheel_model.0.safetensors
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Job jic062-dpo-v1-3-nemo-v1-mkmlizer completed after 104.33s with status: succeeded
Stopping job with name jic062-dpo-v1-3-nemo-v1-mkmlizer
Pipeline stage MKMLizer completed in 105.22s
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Creating inference service jic062-dpo-v1-3-nemo-v1
Waiting for inference service jic062-dpo-v1-3-nemo-v1 to be ready
Inference service jic062-dpo-v1-3-nemo-v1 ready after 170.70582389831543s
Pipeline stage MKMLDeployer completed in 171.06s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.6443676948547363s
Received healthy response to inference request in 15.152331590652466s
Received healthy response to inference request in 1.609349012374878s
Received healthy response to inference request in 1.7557957172393799s
Received healthy response to inference request in 2.187499761581421s
5 requests
0 failed requests
5th percentile: 1.6386383533477784
10th percentile: 1.6679276943206787
20th percentile: 1.7265063762664794
30th percentile: 1.842136526107788
40th percentile: 2.0148181438446047
50th percentile: 2.187499761581421
60th percentile: 2.370246934890747
70th percentile: 2.5529941082000733
80th percentile: 5.145960474014284
90th percentile: 10.149146032333375
95th percentile: 12.650738811492918
99th percentile: 14.652013034820556
mean time: 4.669868755340576
Pipeline stage StressChecker completed in 23.94s
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Pipeline stage TriggerMKMLProfilingPipeline completed in 4.37s
Shutdown handler de-registered
jic062-dpo-v1-3-nemo_v1 status is now deployed due to DeploymentManager action
Shutdown handler registered
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Skipping teardown as no inference service was successfully deployed
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Pipeline stage MKMLProfilerTemplater completed in 0.11s
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Running pipeline stage MKMLProfilerDeployer
Creating inference service jic062-dpo-v1-3-nemo-v1-profiler
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Inference service jic062-dpo-v1-3-nemo-v1-profiler ready after 170.42863082885742s
Pipeline stage MKMLProfilerDeployer completed in 170.89s
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Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/jic062-dpo-v1-3-nemo-v1-profiler-predictor-00001-deploymen7x7lc:/code/chaiverse_profiler_1726110326 --namespace tenant-chaiml-guanaco
kubectl exec -it jic062-dpo-v1-3-nemo-v1-profiler-predictor-00001-deploymen7x7lc --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1726110326 && python profiles.py profile --best_of_n 8 --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_1726110326/summary.json'
kubectl exec -it jic062-dpo-v1-3-nemo-v1-profiler-predictor-00001-deploymen7x7lc --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1726110326/summary.json'
Pipeline stage MKMLProfilerRunner completed in 938.96s
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Running pipeline stage MKMLProfilerDeleter
Checking if service jic062-dpo-v1-3-nemo-v1-profiler is running
Tearing down inference service jic062-dpo-v1-3-nemo-v1-profiler
Service jic062-dpo-v1-3-nemo-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.00s
Shutdown handler de-registered
jic062-dpo-v1-3-nemo_v1 status is now inactive due to auto deactivation removed underperforming models