developer_uid: rirv938
submission_id: rirv938-mistral-12b-dpo_40445_v1
model_name: rirv938-mistral-12b-dpo_40445_v1
model_group: rirv938/mistral_12b_dpo_
status: inactive
timestamp: 2025-02-25T00:41:43+00:00
num_battles: 6088
num_wins: 2413
celo_rating: 1153.38
family_friendly_score: 0.6178
family_friendly_standard_error: 0.0068720180442137955
submission_type: basic
model_repo: rirv938/mistral_12b_dpo_40k_2374_32_output_tokens_v2
model_architecture: MistralForCausalLM
model_num_parameters: 12772070400.0
best_of: 8
max_input_tokens: 768
max_output_tokens: 32
latencies: [{'batch_size': 1, 'throughput': 1.1075952147775872, 'latency_mean': 0.9027814126014709, 'latency_p50': 0.8866157531738281, 'latency_p90': 1.0807397365570068}, {'batch_size': 4, 'throughput': 1.9663730279868932, 'latency_mean': 2.0212822163105013, 'latency_p50': 2.009194850921631, 'latency_p90': 2.4712863206863402}, {'batch_size': 5, 'throughput': 2.1281641506856497, 'latency_mean': 2.34111358165741, 'latency_p50': 2.3706717491149902, 'latency_p90': 2.7575277805328366}, {'batch_size': 8, 'throughput': 2.258710485626249, 'latency_mean': 3.519281189441681, 'latency_p50': 3.542559027671814, 'latency_p90': 4.122386264801025}, {'batch_size': 10, 'throughput': 2.344026644185612, 'latency_mean': 4.250989453792572, 'latency_p50': 4.284047961235046, 'latency_p90': 5.00990924835205}, {'batch_size': 12, 'throughput': 2.3291719062641785, 'latency_mean': 5.097202563285828, 'latency_p50': 5.1052796840667725, 'latency_p90': 6.167601895332337}, {'batch_size': 15, 'throughput': 2.3582971307218292, 'latency_mean': 6.273592038154602, 'latency_p50': 6.227359414100647, 'latency_p90': 7.262431597709655}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: rirv938-mistral-12b-dpo_40445_v1
ineligible_reason: max_output_tokens!=64
is_internal_developer: True
language_model: rirv938/mistral_12b_dpo_40k_2374_32_output_tokens_v2
model_size: 13B
ranking_group: single
throughput_3p7s: 2.3
us_pacific_date: 2025-02-24
win_ratio: 0.39635348226018396
generation_params: {'temperature': 0.9, 'top_p': 0.9, 'min_p': 0.6, 'top_k': 80, 'presence_penalty': 0.5, 'frequency_penalty': 0.5, 'stopping_words': ['\n', '</s>', '###', 'You:'], 'max_input_tokens': 768, 'best_of': 8, 'max_output_tokens': 32}
formatter: {'memory_template': '', 'prompt_template': '', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '{bot_name}:', 'truncate_by_message': False}
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 rirv938-mistral-12b-dpo-40445-v1-mkmlizer
Waiting for job on rirv938-mistral-12b-dpo-40445-v1-mkmlizer to finish
rirv938-mistral-12b-dpo-40445-v1-mkmlizer: Downloaded to shared memory in 103.221s
rirv938-mistral-12b-dpo-40445-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpk7s90ps1, device:0
rirv938-mistral-12b-dpo-40445-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
rirv938-mistral-12b-dpo-40445-v1-mkmlizer: quantized model in 42.398s
rirv938-mistral-12b-dpo-40445-v1-mkmlizer: Processed model rirv938/mistral_12b_dpo_40k_2374_32_output_tokens_v2 in 145.620s
rirv938-mistral-12b-dpo-40445-v1-mkmlizer: creating bucket guanaco-mkml-models
rirv938-mistral-12b-dpo-40445-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
rirv938-mistral-12b-dpo-40445-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/rirv938-mistral-12b-dpo-40445-v1
rirv938-mistral-12b-dpo-40445-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/rirv938-mistral-12b-dpo-40445-v1/config.json
rirv938-mistral-12b-dpo-40445-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/rirv938-mistral-12b-dpo-40445-v1/special_tokens_map.json
rirv938-mistral-12b-dpo-40445-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/rirv938-mistral-12b-dpo-40445-v1/tokenizer_config.json
rirv938-mistral-12b-dpo-40445-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/rirv938-mistral-12b-dpo-40445-v1/tokenizer.json
rirv938-mistral-12b-dpo-40445-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/rirv938-mistral-12b-dpo-40445-v1/flywheel_model.0.safetensors
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Job rirv938-mistral-12b-dpo-40445-v1-mkmlizer completed after 174.71s with status: succeeded
Stopping job with name rirv938-mistral-12b-dpo-40445-v1-mkmlizer
Pipeline stage MKMLizer completed in 175.19s
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Pipeline stage MKMLTemplater completed in 0.16s
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Creating inference service rirv938-mistral-12b-dpo-40445-v1
Waiting for inference service rirv938-mistral-12b-dpo-40445-v1 to be ready
Inference service rirv938-mistral-12b-dpo-40445-v1 ready after 250.84439945220947s
Pipeline stage MKMLDeployer completed in 251.34s
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Running pipeline stage StressChecker
Received healthy response to inference request in 1.344329595565796s
Received healthy response to inference request in 1.0117359161376953s
Received healthy response to inference request in 0.8385906219482422s
Received healthy response to inference request in 0.8165242671966553s
Received healthy response to inference request in 0.7312521934509277s
5 requests
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5th percentile: 0.7483066082000732
10th percentile: 0.7653610229492187
20th percentile: 0.7994698524475098
30th percentile: 0.8209375381469727
40th percentile: 0.8297640800476074
50th percentile: 0.8385906219482422
60th percentile: 0.9078487396240235
70th percentile: 0.9771068572998046
80th percentile: 1.0782546520233154
90th percentile: 1.2112921237945558
95th percentile: 1.2778108596801758
99th percentile: 1.3310258483886719
mean time: 0.9484865188598632
Pipeline stage StressChecker completed in 6.02s
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Pipeline stage TriggerMKMLProfilingPipeline completed in 0.72s
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Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
Pipeline stage OfflineFamilyFriendlyScorer completed in 1766.73s
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rirv938-mistral-12b-dpo_40445_v1 status is now inactive due to auto deactivation removed underperforming models
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