submission_id: jic062-dpo-v1-2-nemo-c500_v1
developer_uid: chace9580
alignment_samples: 10577
alignment_score: -1.6344180545289955
best_of: 8
celo_rating: 1155.75
display_name: jic062-dpo-v1-2-nemo-c500_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-v1.2-Nemo-c500
latencies: [{'batch_size': 1, 'throughput': 0.691243164979831, 'latency_mean': 1.4466006457805634, 'latency_p50': 1.4495887756347656, 'latency_p90': 1.6008866786956788}, {'batch_size': 3, 'throughput': 1.3317282778478805, 'latency_mean': 2.24319122672081, 'latency_p50': 2.2600873708724976, 'latency_p90': 2.4852947473526}, {'batch_size': 5, 'throughput': 1.5755177834451612, 'latency_mean': 3.1548821651935577, 'latency_p50': 3.192306876182556, 'latency_p90': 3.5483023881912232}, {'batch_size': 6, 'throughput': 1.6177754515659202, 'latency_mean': 3.687238829135895, 'latency_p50': 3.6781270503997803, 'latency_p90': 4.153065133094787}, {'batch_size': 8, 'throughput': 1.613034825735949, 'latency_mean': 4.923209717273712, 'latency_p50': 4.938737630844116, 'latency_p90': 5.638543725013733}, {'batch_size': 10, 'throughput': 1.5755705367320934, 'latency_mean': 6.304563139677048, 'latency_p50': 6.34716010093689, 'latency_p90': 7.336219143867493}]
max_input_tokens: 512
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: jic062/dpo-v1.2-Nemo-c50
model_name: jic062-dpo-v1-2-nemo-c500_v1
model_num_parameters: 12772070400.0
model_repo: jic062/dpo-v1.2-Nemo-c500
model_size: 13B
num_battles: 10576
num_wins: 3958
propriety_score: 0.7063081695966908
propriety_total_count: 967.0
ranking_group: single
status: inactive
submission_type: basic
throughput_3p7s: 1.63
timestamp: 2024-09-11T04:03:24+00:00
us_pacific_date: 2024-09-10
win_ratio: 0.37424357034795763
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 jic062-dpo-v1-2-nemo-c500-v1-mkmlizer
Waiting for job on jic062-dpo-v1-2-nemo-c500-v1-mkmlizer to finish
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
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jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: ║ ║
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: ║ Version: 0.10.1 ║
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: ║ https://mk1.ai ║
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jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: ║ Chai Research Corp. ║
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
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Retrying (%r) after connection broken by '%r': %s
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: Downloaded to shared memory in 51.414s
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp7b6kwwj0, device:0
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: quantized model in 35.985s
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: Processed model jic062/dpo-v1.2-Nemo-c500 in 87.399s
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: creating bucket guanaco-mkml-models
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/jic062-dpo-v1-2-nemo-c500-v1
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/jic062-dpo-v1-2-nemo-c500-v1/config.json
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/jic062-dpo-v1-2-nemo-c500-v1/special_tokens_map.json
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/jic062-dpo-v1-2-nemo-c500-v1/tokenizer_config.json
jic062-dpo-v1-2-nemo-c500-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/jic062-dpo-v1-2-nemo-c500-v1/tokenizer.json
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Job jic062-dpo-v1-2-nemo-c500-v1-mkmlizer completed after 116.39s with status: succeeded
Stopping job with name jic062-dpo-v1-2-nemo-c500-v1-mkmlizer
Pipeline stage MKMLizer completed in 119.92s
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Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.11s
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Running pipeline stage MKMLDeployer
Creating inference service jic062-dpo-v1-2-nemo-c500-v1
Waiting for inference service jic062-dpo-v1-2-nemo-c500-v1 to be ready
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Inference service jic062-dpo-v1-2-nemo-c500-v1 ready after 160.8551709651947s
Pipeline stage MKMLDeployer completed in 161.52s
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Running pipeline stage StressChecker
Received healthy response to inference request in 3.0664753913879395s
Received healthy response to inference request in 1.9238312244415283s
Received healthy response to inference request in 1.9242753982543945s
Received healthy response to inference request in 2.2193262577056885s
Received healthy response to inference request in 1.7061212062835693s
5 requests
0 failed requests
5th percentile: 1.7496632099151612
10th percentile: 1.7932052135467529
20th percentile: 1.8802892208099364
30th percentile: 1.9239200592041015
40th percentile: 1.924097728729248
50th percentile: 1.9242753982543945
60th percentile: 2.042295742034912
70th percentile: 2.1603160858154298
80th percentile: 2.388756084442139
90th percentile: 2.727615737915039
95th percentile: 2.897045564651489
99th percentile: 3.032589426040649
mean time: 2.168005895614624
Pipeline stage StressChecker completed in 11.58s
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Running pipeline stage TriggerMKMLProfilingPipeline
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starting trigger_guanaco_pipeline args=%s
Failed to get response for submission trace2333-mistral-dpo-trail2_v1: ('http://trace2333-mistral-dpo-trail2-v1-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', 'read tcp 127.0.0.1:53714->127.0.0.1:8080: read: connection reset by peer\n')
Pipeline stage TriggerMKMLProfilingPipeline completed in 5.22s
Shutdown handler de-registered
jic062-dpo-v1-2-nemo-c500_v1 status is now deployed due to DeploymentManager action
Shutdown handler registered
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Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLProfilerDeleter completed in 0.12s
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Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.12s
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Running pipeline stage MKMLProfilerDeployer
Creating inference service jic062-dpo-v1-2-nemo-c500-v1-profiler
Waiting for inference service jic062-dpo-v1-2-nemo-c500-v1-profiler to be ready
Inference service jic062-dpo-v1-2-nemo-c500-v1-profiler ready after 160.4437699317932s
Pipeline stage MKMLProfilerDeployer completed in 160.80s
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Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/jic062-dpo-v1-2-nemoc1e9510ded3fc4fbcc35b90dc82780d1-deplo8x74s:/code/chaiverse_profiler_1726027906 --namespace tenant-chaiml-guanaco
kubectl exec -it jic062-dpo-v1-2-nemoc1e9510ded3fc4fbcc35b90dc82780d1-deplo8x74s --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1726027906 && 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_1726027906/summary.json'
kubectl exec -it jic062-dpo-v1-2-nemoc1e9510ded3fc4fbcc35b90dc82780d1-deplo8x74s --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1726027906/summary.json'
Pipeline stage MKMLProfilerRunner completed in 946.36s
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Running pipeline stage MKMLProfilerDeleter
Checking if service jic062-dpo-v1-2-nemo-c500-v1-profiler is running
Tearing down inference service jic062-dpo-v1-2-nemo-c500-v1-profiler
Service jic062-dpo-v1-2-nemo-c500-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 1.72s
Shutdown handler de-registered
jic062-dpo-v1-2-nemo-c500_v1 status is now inactive due to auto deactivation removed underperforming models