submission_id: jic062-dpo-v1-5-c500_v2
developer_uid: chace9580
best_of: 16
celo_rating: 1249.1
display_name: jic062-dpo-v1-5-c500_v2
family_friendly_score: 0.0
formatter: {'memory_template': "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n{bot_name}'s Persona: {memory}\n\n", 'prompt_template': '{prompt}<|eot_id|>', 'bot_template': '<|start_header_id|>assistant<|end_header_id|>\n\n{bot_name}: {message}<|eot_id|>', 'user_template': '<|start_header_id|>user<|end_header_id|>\n\n{user_name}: {message}<|eot_id|>', 'response_template': '<|start_header_id|>assistant<|end_header_id|>\n\n{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', '<|end_of_text|>', '|eot_id|'], 'max_input_tokens': 512, 'best_of': 16, 'max_output_tokens': 64}
gpu_counts: {'NVIDIA RTX A5000': 1}
is_internal_developer: False
language_model: jic062/dpo-v1.5-c500
latencies: [{'batch_size': 1, 'throughput': 0.8951100594688272, 'latency_mean': 1.1170825564861298, 'latency_p50': 1.1222362518310547, 'latency_p90': 1.2452787160873413}, {'batch_size': 3, 'throughput': 1.569558137791753, 'latency_mean': 1.9049015414714814, 'latency_p50': 1.8924596309661865, 'latency_p90': 2.1069660663604735}, {'batch_size': 5, 'throughput': 1.7452782602356538, 'latency_mean': 2.8498659420013426, 'latency_p50': 2.83822762966156, 'latency_p90': 3.2159887552261353}, {'batch_size': 6, 'throughput': 1.75073624779529, 'latency_mean': 3.4060009217262266, 'latency_p50': 3.405379295349121, 'latency_p90': 3.8085400342941282}, {'batch_size': 8, 'throughput': 1.7517246001041828, 'latency_mean': 4.536375169754028, 'latency_p50': 4.522991418838501, 'latency_p90': 5.119816732406616}, {'batch_size': 10, 'throughput': 1.7303490377970239, 'latency_mean': 5.730692204236984, 'latency_p50': 5.812921643257141, 'latency_p90': 6.427660346031189}]
max_input_tokens: 512
max_output_tokens: 64
model_architecture: LlamaForCausalLM
model_group: jic062/dpo-v1.5-c500
model_name: jic062-dpo-v1-5-c500_v2
model_num_parameters: 8030261248.0
model_repo: jic062/dpo-v1.5-c500
model_size: 8B
num_battles: 10701
num_wins: 5356
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 1.76
timestamp: 2024-09-15T04:59:05+00:00
us_pacific_date: 2024-09-14
win_ratio: 0.5005139706569479
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run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name jic062-dpo-v1-5-c500-v2-mkmlizer
Waiting for job on jic062-dpo-v1-5-c500-v2-mkmlizer to finish
jic062-dpo-v1-5-c500-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ _____ __ __ ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
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jic062-dpo-v1-5-c500-v2-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ /___/ ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ Version: 0.10.1 ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ https://mk1.ai ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ The license key for the current software has been verified as ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ belonging to: ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ Chai Research Corp. ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ║ ║
jic062-dpo-v1-5-c500-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
jic062-dpo-v1-5-c500-v2-mkmlizer: Downloaded to shared memory in 20.412s
jic062-dpo-v1-5-c500-v2-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp7403ljei, device:0
jic062-dpo-v1-5-c500-v2-mkmlizer: Saving flywheel model at /dev/shm/model_cache
jic062-dpo-v1-5-c500-v2-mkmlizer: quantized model in 25.816s
jic062-dpo-v1-5-c500-v2-mkmlizer: Processed model jic062/dpo-v1.5-c500 in 46.228s
jic062-dpo-v1-5-c500-v2-mkmlizer: creating bucket guanaco-mkml-models
jic062-dpo-v1-5-c500-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
jic062-dpo-v1-5-c500-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/jic062-dpo-v1-5-c500-v2
jic062-dpo-v1-5-c500-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/jic062-dpo-v1-5-c500-v2/config.json
jic062-dpo-v1-5-c500-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/jic062-dpo-v1-5-c500-v2/special_tokens_map.json
jic062-dpo-v1-5-c500-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/jic062-dpo-v1-5-c500-v2/tokenizer_config.json
jic062-dpo-v1-5-c500-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/jic062-dpo-v1-5-c500-v2/tokenizer.json
jic062-dpo-v1-5-c500-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/jic062-dpo-v1-5-c500-v2/flywheel_model.0.safetensors
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Job jic062-dpo-v1-5-c500-v2-mkmlizer completed after 63.84s with status: succeeded
Stopping job with name jic062-dpo-v1-5-c500-v2-mkmlizer
Pipeline stage MKMLizer completed in 64.87s
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Creating inference service jic062-dpo-v1-5-c500-v2
Waiting for inference service jic062-dpo-v1-5-c500-v2 to be ready
Connection pool is full, discarding connection: %s. Connection pool size: %s
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Failed to get response for submission blend_sudit_2024-09-14: ('http://zonemercy-lexical-nemo-1518-v18-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', 'read tcp 127.0.0.1:49100->127.0.0.1:8080: read: connection reset by peer\n')
Inference service jic062-dpo-v1-5-c500-v2 ready after 172.13592314720154s
Pipeline stage MKMLDeployer completed in 173.00s
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Running pipeline stage StressChecker
Received healthy response to inference request in 3.077183961868286s
Received healthy response to inference request in 2.1365480422973633s
Received healthy response to inference request in 2.635958671569824s
Failed to get response for submission blend_jugel_2024-09-09: ('http://chaiml-llama-8b-pairwis-8189-v19-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', 'read tcp 127.0.0.1:43890->127.0.0.1:8080: read: connection reset by peer\n')
Received healthy response to inference request in 2.481898784637451s
Received healthy response to inference request in 3.1270508766174316s
Connection pool is full, discarding connection: %s. Connection pool size: %s
5 requests
0 failed requests
5th percentile: 2.2056181907653807
10th percentile: 2.2746883392333985
20th percentile: 2.4128286361694338
30th percentile: 2.512710762023926
40th percentile: 2.574334716796875
50th percentile: 2.635958671569824
60th percentile: 2.812448787689209
70th percentile: 2.988938903808594
80th percentile: 3.0871573448181153
90th percentile: 3.1071041107177733
95th percentile: 3.1170774936676025
99th percentile: 3.125056200027466
mean time: 2.6917280673980715
Pipeline stage StressChecker completed in 16.53s
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Running pipeline stage TriggerMKMLProfilingPipeline
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starting trigger_guanaco_pipeline args=%s
Pipeline stage TriggerMKMLProfilingPipeline completed in 5.10s
Shutdown handler de-registered
jic062-dpo-v1-5-c500_v2 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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Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.13s
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Running pipeline stage MKMLProfilerDeployer
Creating inference service jic062-dpo-v1-5-c500-v2-profiler
Waiting for inference service jic062-dpo-v1-5-c500-v2-profiler to be ready
Inference service jic062-dpo-v1-5-c500-v2-profiler ready after 170.44217348098755s
Pipeline stage MKMLProfilerDeployer completed in 170.86s
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Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/jic062-dpo-v1-5-c500-v2-profiler-predictor-00001-deploymenlmmwn:/code/chaiverse_profiler_1726376832 --namespace tenant-chaiml-guanaco
kubectl exec -it jic062-dpo-v1-5-c500-v2-profiler-predictor-00001-deploymenlmmwn --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1726376832 && 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_1726376832/summary.json'
kubectl exec -it jic062-dpo-v1-5-c500-v2-profiler-predictor-00001-deploymenlmmwn --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1726376832/summary.json'
Pipeline stage MKMLProfilerRunner completed in 820.10s
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Running pipeline stage MKMLProfilerDeleter
Checking if service jic062-dpo-v1-5-c500-v2-profiler is running
Tearing down inference service jic062-dpo-v1-5-c500-v2-profiler
Service jic062-dpo-v1-5-c500-v2-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 1.79s
Shutdown handler de-registered
jic062-dpo-v1-5-c500_v2 status is now inactive due to auto deactivation removed underperforming models
jic062-dpo-v1-5-c500_v2 status is now torndown due to DeploymentManager action