developer_uid: zonemercy
submission_id: mistralai-mistral-nem_93303_v237
model_name: tempv1-0
model_group: mistralai/Mistral-Nemo-I
status: torndown
timestamp: 2024-12-28T23:09:59+00:00
num_battles: 19543
num_wins: 8950
celo_rating: 1237.44
family_friendly_score: 0.5942000000000001
family_friendly_standard_error: 0.006944441806221721
submission_type: basic
model_repo: mistralai/Mistral-Nemo-Instruct-2407
model_architecture: MistralForCausalLM
model_num_parameters: 12772070400.0
best_of: 4
max_input_tokens: 1024
max_output_tokens: 64
reward_model: default
latencies: [{'batch_size': 1, 'throughput': 0.6345704483707675, 'latency_mean': 1.575805548429489, 'latency_p50': 1.5844717025756836, 'latency_p90': 1.731524610519409}, {'batch_size': 3, 'throughput': 1.2755019735084578, 'latency_mean': 2.3490710353851316, 'latency_p50': 2.346412777900696, 'latency_p90': 2.613575744628906}, {'batch_size': 5, 'throughput': 1.600939195390744, 'latency_mean': 3.105964094400406, 'latency_p50': 3.144216299057007, 'latency_p90': 3.507797694206238}, {'batch_size': 6, 'throughput': 1.706869704707631, 'latency_mean': 3.499805338382721, 'latency_p50': 3.511335849761963, 'latency_p90': 3.968419885635376}, {'batch_size': 8, 'throughput': 1.8603555260078823, 'latency_mean': 4.2703304600715635, 'latency_p50': 4.270780920982361, 'latency_p90': 4.799798750877381}, {'batch_size': 10, 'throughput': 1.9363442943644011, 'latency_mean': 5.122985293865204, 'latency_p50': 5.1744290590286255, 'latency_p90': 5.706695151329041}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: tempv1-0
is_internal_developer: True
language_model: mistralai/Mistral-Nemo-Instruct-2407
model_size: 13B
ranking_group: single
throughput_3p7s: 1.76
us_pacific_date: 2024-12-28
win_ratio: 0.4579644885636801
generation_params: {'temperature': 0.9, 'top_p': 1.0, 'min_p': 0.05, 'top_k': 80, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['User:', '<|eot_id|>', '<|im_end|>', 'Bot:', 'You:', '\n', '####', '</s>'], 'max_input_tokens': 1024, 'best_of': 4, 'max_output_tokens': 64}
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 mistralai-mistral-nem-93303-v237-mkmlizer
Waiting for job on mistralai-mistral-nem-93303-v237-mkmlizer to finish
Connection pool is full, discarding connection: %s. Connection pool size: %s
mistralai-mistral-nem-93303-v237-mkmlizer: Downloaded to shared memory in 61.201s
mistralai-mistral-nem-93303-v237-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpnzq_9djn, device:0
mistralai-mistral-nem-93303-v237-mkmlizer: Saving flywheel model at /dev/shm/model_cache
Retrying (%r) after connection broken by '%r': %s
mistralai-mistral-nem-93303-v237-mkmlizer: quantized model in 38.337s
mistralai-mistral-nem-93303-v237-mkmlizer: Processed model mistralai/Mistral-Nemo-Instruct-2407 in 99.539s
mistralai-mistral-nem-93303-v237-mkmlizer: creating bucket guanaco-mkml-models
mistralai-mistral-nem-93303-v237-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
mistralai-mistral-nem-93303-v237-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/mistralai-mistral-nem-93303-v237
mistralai-mistral-nem-93303-v237-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/mistralai-mistral-nem-93303-v237/config.json
mistralai-mistral-nem-93303-v237-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/mistralai-mistral-nem-93303-v237/tokenizer.json
mistralai-mistral-nem-93303-v237-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/mistralai-mistral-nem-93303-v237/flywheel_model.0.safetensors
mistralai-mistral-nem-93303-v237-mkmlizer: 
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Job mistralai-mistral-nem-93303-v237-mkmlizer completed after 143.75s with status: succeeded
Stopping job with name mistralai-mistral-nem-93303-v237-mkmlizer
Pipeline stage MKMLizer completed in 144.25s
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Running pipeline stage MKMLTemplater
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Running pipeline stage MKMLDeployer
Creating inference service mistralai-mistral-nem-93303-v237
Waiting for inference service mistralai-mistral-nem-93303-v237 to be ready
Inference service mistralai-mistral-nem-93303-v237 ready after 291.07004284858704s
Pipeline stage MKMLDeployer completed in 291.60s
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Running pipeline stage StressChecker
Received healthy response to inference request in 1.7224326133728027s
Received healthy response to inference request in 0.9028744697570801s
Received healthy response to inference request in 1.3113222122192383s
Received healthy response to inference request in 1.03737211227417s
Received healthy response to inference request in 0.4515843391418457s
5 requests
0 failed requests
5th percentile: 0.5418423652648926
10th percentile: 0.6321003913879395
20th percentile: 0.8126164436340332
30th percentile: 0.929773998260498
40th percentile: 0.983573055267334
50th percentile: 1.03737211227417
60th percentile: 1.1469521522521973
70th percentile: 1.2565321922302246
80th percentile: 1.3935442924499513
90th percentile: 1.557988452911377
95th percentile: 1.6402105331420898
99th percentile: 1.7059881973266602
mean time: 1.0851171493530274
Pipeline stage StressChecker completed in 6.91s
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Pipeline stage OfflineFamilyFriendlyScorer completed in 4611.52s
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