submission_id: rica40325-feedback-dpo-10_v1
developer_uid: rica40325
best_of: 16
celo_rating: 1246.24
display_name: rica40325-feedback-dpo-10_v1
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': 0.0, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 512, 'best_of': 16, 'max_output_tokens': 64}
gpu_counts: {'NVIDIA RTX A5000': 1}
is_internal_developer: False
language_model: rica40325/feedback_dpo_10
latencies: [{'batch_size': 1, 'throughput': 0.9080466297942528, 'latency_mean': 1.1011741650104523, 'latency_p50': 1.0970619916915894, 'latency_p90': 1.2331916093826294}, {'batch_size': 4, 'throughput': 1.8020918944441071, 'latency_mean': 2.2083158576488495, 'latency_p50': 2.2249221801757812, 'latency_p90': 2.497475790977478}, {'batch_size': 5, 'throughput': 1.8920687394237459, 'latency_mean': 2.6320382416248322, 'latency_p50': 2.6272183656692505, 'latency_p90': 2.9436498880386353}, {'batch_size': 8, 'throughput': 1.995185325523204, 'latency_mean': 3.9849071562290193, 'latency_p50': 3.995392680168152, 'latency_p90': 4.425540804862976}, {'batch_size': 10, 'throughput': 2.03370185454978, 'latency_mean': 4.871041784286499, 'latency_p50': 4.8917152881622314, 'latency_p90': 5.527490234375}, {'batch_size': 12, 'throughput': 2.044101515141591, 'latency_mean': 5.799888514280319, 'latency_p50': 5.8356733322143555, 'latency_p90': 6.694674730300903}, {'batch_size': 15, 'throughput': 2.044176073207742, 'latency_mean': 7.201027916669846, 'latency_p50': 7.320666313171387, 'latency_p90': 8.040846729278565}]
max_input_tokens: 512
max_output_tokens: 64
model_architecture: LlamaForCausalLM
model_group: rica40325/feedback_dpo_1
model_name: rica40325-feedback-dpo-10_v1
model_num_parameters: 8030261248.0
model_repo: rica40325/feedback_dpo_10
model_size: 8B
num_battles: 10823
num_wins: 5486
ranking_group: single
status: torndown
submission_type: basic
throughput_3p7s: 1.99
timestamp: 2024-09-11T05:35:28+00:00
us_pacific_date: 2024-09-10
win_ratio: 0.5068834888663032
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 rica40325-feedback-dpo-10-v1-mkmlizer
Waiting for job on rica40325-feedback-dpo-10-v1-mkmlizer to finish
rica40325-feedback-dpo-10-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
rica40325-feedback-dpo-10-v1-mkmlizer: ║ _____ __ __ ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ /___/ ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ Version: 0.10.1 ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ https://mk1.ai ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ The license key for the current software has been verified as ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ belonging to: ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ Chai Research Corp. ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
rica40325-feedback-dpo-10-v1-mkmlizer: ║ ║
rica40325-feedback-dpo-10-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
rica40325-feedback-dpo-10-v1-mkmlizer: Downloaded to shared memory in 65.283s
rica40325-feedback-dpo-10-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpy3i6v6sc, device:0
rica40325-feedback-dpo-10-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
rica40325-feedback-dpo-10-v1-mkmlizer: quantized model in 28.859s
rica40325-feedback-dpo-10-v1-mkmlizer: Processed model rica40325/feedback_dpo_10 in 94.142s
rica40325-feedback-dpo-10-v1-mkmlizer: creating bucket guanaco-mkml-models
rica40325-feedback-dpo-10-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
rica40325-feedback-dpo-10-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/rica40325-feedback-dpo-10-v1
rica40325-feedback-dpo-10-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/rica40325-feedback-dpo-10-v1/tokenizer_config.json
rica40325-feedback-dpo-10-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/rica40325-feedback-dpo-10-v1/special_tokens_map.json
rica40325-feedback-dpo-10-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/rica40325-feedback-dpo-10-v1/config.json
rica40325-feedback-dpo-10-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/rica40325-feedback-dpo-10-v1/tokenizer.json
rica40325-feedback-dpo-10-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/rica40325-feedback-dpo-10-v1/flywheel_model.0.safetensors
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Job rica40325-feedback-dpo-10-v1-mkmlizer completed after 116.0s with status: succeeded
Stopping job with name rica40325-feedback-dpo-10-v1-mkmlizer
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Inference service rica40325-feedback-dpo-10-v1 ready after 181.048011302948s
Pipeline stage MKMLDeployer completed in 181.89s
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Received healthy response to inference request in 3.098379135131836s
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Received healthy response to inference request in 1.6015589237213135s
Received healthy response to inference request in 2.106792449951172s
Received healthy response to inference request in 3.180720090866089s
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mean time: 2.355544424057007
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Inference service rica40325-feedback-dpo-10-v1-profiler ready after 160.4634392261505s
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/rica40325-feedback-d2a9c7c11f461e5176522e57826919efd-deplonffsp:/code/chaiverse_profiler_1726033454 --namespace tenant-chaiml-guanaco
kubectl exec -it rica40325-feedback-d2a9c7c11f461e5176522e57826919efd-deplonffsp --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1726033454 && 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_1726033454/summary.json'
kubectl exec -it rica40325-feedback-d2a9c7c11f461e5176522e57826919efd-deplonffsp --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1726033454/summary.json'
Pipeline stage MKMLProfilerRunner completed in 837.60s
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rica40325-feedback-dpo-10_v1 status is now torndown due to DeploymentManager action