submission_id: mistralai-mistral-7b-ins_6151_v5
developer_uid: chai_backend_admin
status: inactive
model_repo: mistralai/Mistral-7B-Instruct-v0.2
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 0.9, 'top_p': 1.0, 'top_k': 50, 'presence_penalty': 0.5, 'frequency_penalty': 0.5, 'stopping_words': ['\n', '</s>', '<|user|>', '###'], 'max_input_tokens': 512, 'best_of': 1, 'max_output_tokens': 64}
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}:'}
reward_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}:'}
timestamp: 2024-04-02T15:46:45+00:00
model_name: auto_submit_ricum_gurusulive
model_eval_status: success
safety_score: 0.98
entertaining: 6.64
stay_in_character: 8.44
user_preference: 7.12
double_thumbs_up: 232
thumbs_up: 403
thumbs_down: 252
num_battles: 25043
num_wins: 9788
win_ratio: 0.3908477418839596
celo_rating: 1076.85
Resubmit model
Running pipeline stage MKMLizer
Starting job with name mistralai-mistral-7b-ins-6151-v5-mkmlizer
Waiting for job on mistralai-mistral-7b-ins-6151-v5-mkmlizer to finish
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ _____ __ __ ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ /___/ ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ Version: 0.6.11 ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ The license key for the current software has been verified as ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ belonging to: ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ Chai Research Corp. ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ║ ║
mistralai-mistral-7b-ins-6151-v5-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
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mistralai-mistral-7b-ins-6151-v5-mkmlizer: Downloaded to shared memory in 17.456s
mistralai-mistral-7b-ins-6151-v5-mkmlizer: quantizing model to /dev/shm/model_cache
mistralai-mistral-7b-ins-6151-v5-mkmlizer: Saving mkml model at /dev/shm/model_cache
mistralai-mistral-7b-ins-6151-v5-mkmlizer: Reading /tmp/tmp1rjez2x6/model.safetensors.index.json
mistralai-mistral-7b-ins-6151-v5-mkmlizer: Profiling: 0%| | 0/291 [00:00<?, ?it/s] Profiling: 0%| | 1/291 [00:01<06:04, 1.26s/it] Profiling: 4%|▍ | 13/291 [00:01<00:21, 12.84it/s] Profiling: 9%|▉ | 27/291 [00:01<00:09, 28.72it/s] Profiling: 13%|█▎ | 38/291 [00:01<00:06, 40.49it/s] Profiling: 19%|█▊ | 54/291 [00:01<00:03, 61.03it/s] Profiling: 23%|██▎ | 66/291 [00:01<00:03, 71.25it/s] Profiling: 28%|██▊ | 81/291 [00:01<00:02, 88.19it/s] Profiling: 32%|███▏ | 94/291 [00:02<00:02, 95.26it/s] Profiling: 37%|███▋ | 107/291 [00:02<00:02, 64.54it/s] Profiling: 42%|████▏ | 121/291 [00:02<00:02, 76.22it/s] Profiling: 46%|████▋ | 135/291 [00:02<00:01, 88.76it/s] Profiling: 51%|█████ | 148/291 [00:02<00:01, 96.87it/s] Profiling: 56%|█████▌ | 163/291 [00:02<00:01, 109.34it/s] Profiling: 60%|██████ | 176/291 [00:02<00:01, 108.31it/s] Profiling: 66%|██████▋ | 193/291 [00:03<00:00, 118.74it/s] Profiling: 71%|███████ | 206/291 [00:04<00:03, 26.02it/s] Profiling: 74%|███████▍ | 216/291 [00:04<00:02, 31.39it/s] Profiling: 79%|███████▉ | 230/291 [00:04<00:01, 41.15it/s] Profiling: 84%|████████▍ | 244/291 [00:04<00:00, 52.59it/s] Profiling: 88%|████████▊ | 257/291 [00:04<00:00, 63.06it/s] Profiling: 93%|█████████▎| 271/291 [00:05<00:00, 75.89it/s] Profiling: 98%|█████████▊| 284/291 [00:05<00:00, 85.17it/s] Profiling: 100%|██████████| 291/291 [00:05<00:00, 53.84it/s]
mistralai-mistral-7b-ins-6151-v5-mkmlizer: quantized model in 15.637s
mistralai-mistral-7b-ins-6151-v5-mkmlizer: Processed model mistralai/Mistral-7B-Instruct-v0.2 in 34.010s
mistralai-mistral-7b-ins-6151-v5-mkmlizer: creating bucket guanaco-mkml-models
mistralai-mistral-7b-ins-6151-v5-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
mistralai-mistral-7b-ins-6151-v5-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/mistralai-mistral-7b-ins-6151-v5
mistralai-mistral-7b-ins-6151-v5-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/mistralai-mistral-7b-ins-6151-v5/config.json
mistralai-mistral-7b-ins-6151-v5-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/mistralai-mistral-7b-ins-6151-v5/tokenizer.model
mistralai-mistral-7b-ins-6151-v5-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/mistralai-mistral-7b-ins-6151-v5/tokenizer.json
mistralai-mistral-7b-ins-6151-v5-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/mistralai-mistral-7b-ins-6151-v5/tokenizer_config.json
mistralai-mistral-7b-ins-6151-v5-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/mistralai-mistral-7b-ins-6151-v5/special_tokens_map.json
mistralai-mistral-7b-ins-6151-v5-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
mistralai-mistral-7b-ins-6151-v5-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py:1067: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
mistralai-mistral-7b-ins-6151-v5-mkmlizer: warnings.warn(
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mistralai-mistral-7b-ins-6151-v5-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py:690: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
mistralai-mistral-7b-ins-6151-v5-mkmlizer: warnings.warn(
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mistralai-mistral-7b-ins-6151-v5-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:472: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
mistralai-mistral-7b-ins-6151-v5-mkmlizer: warnings.warn(
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mistralai-mistral-7b-ins-6151-v5-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
mistralai-mistral-7b-ins-6151-v5-mkmlizer: Bucket 's3://guanaco-reward-models/' created
mistralai-mistral-7b-ins-6151-v5-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/mistralai-mistral-7b-ins-6151-v5_reward
mistralai-mistral-7b-ins-6151-v5-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/mistralai-mistral-7b-ins-6151-v5_reward/config.json
mistralai-mistral-7b-ins-6151-v5-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/mistralai-mistral-7b-ins-6151-v5_reward/merges.txt
mistralai-mistral-7b-ins-6151-v5-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/mistralai-mistral-7b-ins-6151-v5_reward/tokenizer_config.json
mistralai-mistral-7b-ins-6151-v5-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/mistralai-mistral-7b-ins-6151-v5_reward/special_tokens_map.json
mistralai-mistral-7b-ins-6151-v5-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/mistralai-mistral-7b-ins-6151-v5_reward/vocab.json
mistralai-mistral-7b-ins-6151-v5-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/mistralai-mistral-7b-ins-6151-v5_reward/tokenizer.json
mistralai-mistral-7b-ins-6151-v5-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/mistralai-mistral-7b-ins-6151-v5_reward/reward.tensors
Job mistralai-mistral-7b-ins-6151-v5-mkmlizer completed after 64.05s with status: succeeded
Stopping job with name mistralai-mistral-7b-ins-6151-v5-mkmlizer
Pipeline stage MKMLizer completed in 68.03s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.09s
Running pipeline stage ISVCDeployer
Creating inference service mistralai-mistral-7b-ins-6151-v5
Waiting for inference service mistralai-mistral-7b-ins-6151-v5 to be ready
Inference service mistralai-mistral-7b-ins-6151-v5 ready after 50.32521367073059s
Pipeline stage ISVCDeployer completed in 57.38s
Running pipeline stage StressChecker
Received healthy response to inference request in 1.2144219875335693s
Received healthy response to inference request in 0.4904160499572754s
Received healthy response to inference request in 0.8338873386383057s
Received healthy response to inference request in 0.5188961029052734s
Received healthy response to inference request in 0.33692264556884766s
5 requests
0 failed requests
5th percentile: 0.3676213264465332
10th percentile: 0.39832000732421874
20th percentile: 0.4597173690795898
30th percentile: 0.496112060546875
40th percentile: 0.5075040817260742
50th percentile: 0.5188961029052734
60th percentile: 0.6448925971984862
70th percentile: 0.7708890914916992
80th percentile: 0.9099942684173584
90th percentile: 1.0622081279754638
95th percentile: 1.1383150577545165
99th percentile: 1.1992006015777588
mean time: 0.6789088249206543
Pipeline stage StressChecker completed in 4.27s
Running pipeline stage DaemonicModelEvalScorer
Pipeline stage DaemonicModelEvalScorer completed in 0.04s
Running M-Eval for topic stay_in_character
Running pipeline stage DaemonicSafetyScorer
M-Eval Dataset for topic stay_in_character is loaded
Pipeline stage DaemonicSafetyScorer completed in 0.08s
mistralai-mistral-7b-ins_6151_v5 status is now deployed due to DeploymentManager action
mistralai-mistral-7b-ins_6151_v5 status is now inactive due to auto deactivation removed underperforming models

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