submission_id: trace2333-mistral-dpo-trail1_v2
developer_uid: Trace2333
best_of: 8
celo_rating: 1256.63
display_name: trace2333-mistral-dpo-trail1_v2
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': 0.06, 'top_k': 80, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '</s>'], 'max_input_tokens': 512, 'best_of': 8, 'max_output_tokens': 64}
gpu_counts: {'NVIDIA RTX A5000': 1}
is_internal_developer: False
language_model: Trace2333/mistral_dpo_trail1
latencies: [{'batch_size': 1, 'throughput': 0.7039228918400314, 'latency_mean': 1.4205172431468964, 'latency_p50': 1.4226560592651367, 'latency_p90': 1.5940174818038941}, {'batch_size': 3, 'throughput': 1.3509600920350067, 'latency_mean': 2.2126654398441317, 'latency_p50': 2.2197154760360718, 'latency_p90': 2.493104100227356}, {'batch_size': 5, 'throughput': 1.59561441290727, 'latency_mean': 3.1165970182418823, 'latency_p50': 3.1142425537109375, 'latency_p90': 3.4867151260375975}, {'batch_size': 6, 'throughput': 1.6424364704755663, 'latency_mean': 3.637619376182556, 'latency_p50': 3.625206232070923, 'latency_p90': 4.1895997524261475}, {'batch_size': 8, 'throughput': 1.6396190311305983, 'latency_mean': 4.853275482654571, 'latency_p50': 4.889989972114563, 'latency_p90': 5.528837442398071}, {'batch_size': 10, 'throughput': 1.579291121643863, 'latency_mean': 6.288628416061401, 'latency_p50': 6.3875943422317505, 'latency_p90': 7.104311609268188}]
max_input_tokens: 512
max_output_tokens: 64
model_architecture: MistralForCausalLM
model_group: Trace2333/mistral_dpo_tr
model_name: trace2333-mistral-dpo-trail1_v2
model_num_parameters: 12772070400.0
model_repo: Trace2333/mistral_dpo_trail1
model_size: 13B
num_battles: 10962
num_wins: 5691
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 1.65
timestamp: 2024-09-11T02:44:16+00:00
us_pacific_date: 2024-09-10
win_ratio: 0.5191570881226054
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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 trace2333-mistral-dpo-trail1-v2-mkmlizer
Waiting for job on trace2333-mistral-dpo-trail1-v2-mkmlizer to finish
trace2333-mistral-dpo-trail1-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ _____ __ __ ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ /___/ ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ Version: 0.10.1 ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ https://mk1.ai ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ The license key for the current software has been verified as ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ belonging to: ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ Chai Research Corp. ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ║ ║
trace2333-mistral-dpo-trail1-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
trace2333-mistral-dpo-trail1-v2-mkmlizer: Downloaded to shared memory in 34.515s
trace2333-mistral-dpo-trail1-v2-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpt52uvh_h, device:0
trace2333-mistral-dpo-trail1-v2-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
trace2333-mistral-dpo-trail1-v2-mkmlizer: quantized model in 35.861s
trace2333-mistral-dpo-trail1-v2-mkmlizer: Processed model Trace2333/mistral_dpo_trail1 in 70.376s
trace2333-mistral-dpo-trail1-v2-mkmlizer: creating bucket guanaco-mkml-models
trace2333-mistral-dpo-trail1-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
trace2333-mistral-dpo-trail1-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/trace2333-mistral-dpo-trail1-v2
trace2333-mistral-dpo-trail1-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/trace2333-mistral-dpo-trail1-v2/special_tokens_map.json
trace2333-mistral-dpo-trail1-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/trace2333-mistral-dpo-trail1-v2/config.json
trace2333-mistral-dpo-trail1-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/trace2333-mistral-dpo-trail1-v2/tokenizer_config.json
trace2333-mistral-dpo-trail1-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/trace2333-mistral-dpo-trail1-v2/tokenizer.json
trace2333-mistral-dpo-trail1-v2-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/trace2333-mistral-dpo-trail1-v2/flywheel_model.0.safetensors
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Job trace2333-mistral-dpo-trail1-v2-mkmlizer completed after 95.76s with status: succeeded
Stopping job with name trace2333-mistral-dpo-trail1-v2-mkmlizer
Pipeline stage MKMLizer completed in 96.82s
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Creating inference service trace2333-mistral-dpo-trail1-v2
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Inference service trace2333-mistral-dpo-trail1-v2 ready after 161.55307579040527s
Pipeline stage MKMLDeployer completed in 161.97s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.1604108810424805s
Received healthy response to inference request in 1.99674391746521s
Received healthy response to inference request in 1.815537452697754s
Received healthy response to inference request in 2.2548587322235107s
Received healthy response to inference request in 1.6211800575256348s
5 requests
0 failed requests
5th percentile: 1.6600515365600585
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80th percentile: 2.1793004512786864
90th percentile: 2.217079591751099
95th percentile: 2.2359691619873048
99th percentile: 2.2510808181762694
mean time: 1.969746208190918
Pipeline stage StressChecker completed in 10.58s
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Pipeline stage TriggerMKMLProfilingPipeline completed in 5.77s
Shutdown handler de-registered
trace2333-mistral-dpo-trail1_v2 status is now deployed due to DeploymentManager action
Shutdown handler registered
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Pipeline stage MKMLProfilerTemplater completed in 0.11s
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Creating inference service trace2333-mistral-dpo-trail1-v2-profiler
Waiting for inference service trace2333-mistral-dpo-trail1-v2-profiler to be ready
Inference service trace2333-mistral-dpo-trail1-v2-profiler ready after 160.38432836532593s
Pipeline stage MKMLProfilerDeployer completed in 160.73s
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Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/trace2333-mistral-dpf138f33b93cbdf71f3eca249a444396e-deplowrsc5:/code/chaiverse_profiler_1726023135 --namespace tenant-chaiml-guanaco
kubectl exec -it trace2333-mistral-dpf138f33b93cbdf71f3eca249a444396e-deplowrsc5 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1726023135 && 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_1726023135/summary.json'
kubectl exec -it trace2333-mistral-dpf138f33b93cbdf71f3eca249a444396e-deplowrsc5 --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1726023135/summary.json'
Pipeline stage MKMLProfilerRunner completed in 933.12s
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Running pipeline stage MKMLProfilerDeleter
Checking if service trace2333-mistral-dpo-trail1-v2-profiler is running
Tearing down inference service trace2333-mistral-dpo-trail1-v2-profiler
Service trace2333-mistral-dpo-trail1-v2-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.00s
Shutdown handler de-registered
trace2333-mistral-dpo-trail1_v2 status is now inactive due to auto deactivation removed underperforming models
trace2333-mistral-dpo-trail1_v2 status is now torndown due to DeploymentManager action