submission_id: sanjiwatsuki-lelantos-ma_6831_v4
developer_uid: zonemercy
status: inactive
model_repo: SanjiWatsuki/Lelantos-Maid-DPO-7B
reward_repo: rirv938/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '</s>', '###'], 'max_input_tokens': 512, 'best_of': 16, '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': '### Describe all actions in elaborate, explicit, graphic, and vivid detail. Mention all relevant sensory perceptions.\n{bot_name}:'}
timestamp: 2024-03-24T18:34:48+00:00
model_name: sanjiwatsuki-lelantos-ma_6831_v4
model_eval_status: success
safety_score: 0.86
entertaining: 7.02
stay_in_character: 7.94
user_preference: 6.94
double_thumbs_up: 460
thumbs_up: 704
thumbs_down: 373
num_battles: 67695
num_wins: 34693
win_ratio: 0.5124898441539257
celo_rating: 1166.09
Resubmit model
Running pipeline stage MKMLizer
Starting job with name sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer
Waiting for job on sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer to finish
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ _____ __ __ ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ /___/ ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ Version: 0.6.11 ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ The license key for the current software has been verified as ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ belonging to: ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ Chai Research Corp. ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ Expiration: 2024-04-15 23:59:59 ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ║ ║
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
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sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: Downloaded to shared memory in 23.857s
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: quantizing model to /dev/shm/model_cache
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: Saving mkml model at /dev/shm/model_cache
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: Reading /tmp/tmprunwu42t/model.safetensors.index.json
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: Profiling: 0%| | 0/291 [00:00<?, ?it/s] Profiling: 0%| | 1/291 [00:01<06:57, 1.44s/it] Profiling: 4%|▍ | 13/291 [00:01<00:24, 11.27it/s] Profiling: 9%|▉ | 27/291 [00:01<00:10, 25.37it/s] Profiling: 12%|█▏ | 36/291 [00:01<00:08, 30.04it/s] Profiling: 18%|█▊ | 52/291 [00:01<00:04, 49.05it/s] Profiling: 22%|██▏ | 63/291 [00:02<00:03, 59.07it/s] Profiling: 27%|██▋ | 79/291 [00:02<00:03, 67.58it/s] Profiling: 31%|███ | 89/291 [00:02<00:02, 71.32it/s] Profiling: 34%|███▍ | 99/291 [00:02<00:02, 76.15it/s] Profiling: 39%|███▉ | 113/291 [00:02<00:02, 73.79it/s] Profiling: 44%|████▍ | 129/291 [00:02<00:01, 90.99it/s] Profiling: 48%|████▊ | 140/291 [00:02<00:01, 93.92it/s] Profiling: 54%|█████▎ | 156/291 [00:03<00:01, 87.32it/s] Profiling: 57%|█████▋ | 167/291 [00:03<00:01, 91.19it/s] Profiling: 63%|██████▎ | 184/291 [00:03<00:01, 105.58it/s] Profiling: 68%|██████▊ | 197/291 [00:03<00:01, 93.35it/s] Profiling: 72%|███████▏ | 210/291 [00:03<00:00, 100.49it/s] Profiling: 76%|███████▌ | 221/291 [00:03<00:00, 101.68it/s] Profiling: 81%|████████▏ | 237/291 [00:03<00:00, 93.27it/s] Profiling: 85%|████████▌ | 248/291 [00:04<00:00, 96.53it/s] Profiling: 91%|█████████ | 265/291 [00:04<00:00, 110.26it/s] Profiling: 95%|█████████▌| 277/291 [00:05<00:00, 23.49it/s] Profiling: 100%|██████████| 291/291 [00:05<00:00, 49.45it/s]
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: quantized model in 18.063s
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: Processed model SanjiWatsuki/Lelantos-Maid-DPO-7B in 42.997s
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: creating bucket guanaco-mkml-models
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v4
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v4/tokenizer_config.json
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v4/tokenizer.model
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: cp /dev/shm/model_cache/added_tokens.json s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v4/added_tokens.json
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v4/special_tokens_map.json
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v4/config.json
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v4/tokenizer.json
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: cp /dev/shm/model_cache/mkml_model.tensors s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v4/mkml_model.tensors
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: loading reward model from rirv938/reward_gpt2_medium_preference_24m_e2
sanjiwatsuki-lelantos-ma-6831-v4-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.
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: warnings.warn(
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: config.json: 0%| | 0.00/1.05k [00:00<?, ?B/s] config.json: 100%|██████████| 1.05k/1.05k [00:00<00:00, 12.5MB/s]
sanjiwatsuki-lelantos-ma-6831-v4-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.
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: warnings.warn(
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: tokenizer_config.json: 0%| | 0.00/234 [00:00<?, ?B/s] tokenizer_config.json: 100%|██████████| 234/234 [00:00<00:00, 3.29MB/s]
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: vocab.json: 0%| | 0.00/1.04M [00:00<?, ?B/s] vocab.json: 100%|██████████| 1.04M/1.04M [00:00<00:00, 7.69MB/s] vocab.json: 100%|██████████| 1.04M/1.04M [00:00<00:00, 7.66MB/s]
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: pytorch_model.bin: 0%| | 0.00/1.44G [00:00<?, ?B/s] pytorch_model.bin: 1%| | 10.5M/1.44G [00:00<00:34, 41.8MB/s] pytorch_model.bin: 1%|▏ | 21.0M/1.44G [00:00<00:32, 43.4MB/s] pytorch_model.bin: 4%|▎ | 52.4M/1.44G [00:00<00:12, 110MB/s] pytorch_model.bin: 5%|▌ | 73.4M/1.44G [00:00<00:10, 131MB/s] pytorch_model.bin: 10%|█ | 147M/1.44G [00:00<00:04, 288MB/s] pytorch_model.bin: 17%|█▋ | 252M/1.44G [00:00<00:02, 494MB/s] pytorch_model.bin: 60%|██████ | 870M/1.44G [00:01<00:00, 2.08GB/s] pytorch_model.bin: 77%|███████▋ | 1.11G/1.44G [00:01<00:00, 2.14GB/s] pytorch_model.bin: 96%|█████████▌| 1.38G/1.44G [00:01<00:00, 2.09GB/s] pytorch_model.bin: 100%|█████████▉| 1.44G/1.44G [00:01<00:00, 1.03GB/s]
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: Saving duration: 0.243s
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: Processed model rirv938/reward_gpt2_medium_preference_24m_e2 in 5.366s
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: creating bucket guanaco-reward-models
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: Bucket 's3://guanaco-reward-models/' created
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v4_reward
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v4_reward/special_tokens_map.json
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v4_reward/tokenizer_config.json
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v4_reward/config.json
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v4_reward/merges.txt
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v4_reward/vocab.json
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v4_reward/tokenizer.json
sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v4_reward/reward.tensors
Job sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer completed after 65.65s with status: succeeded
Stopping job with name sanjiwatsuki-lelantos-ma-6831-v4-mkmlizer
Pipeline stage MKMLizer completed in 68.74s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.12s
Running pipeline stage ISVCDeployer
Creating inference service sanjiwatsuki-lelantos-ma-6831-v4
Waiting for inference service sanjiwatsuki-lelantos-ma-6831-v4 to be ready
Inference service sanjiwatsuki-lelantos-ma-6831-v4 ready after 40.24536061286926s
Pipeline stage ISVCDeployer completed in 47.41s
Running pipeline stage StressChecker
Received healthy response to inference request in 1.9645004272460938s
Received healthy response to inference request in 1.2229468822479248s
Received healthy response to inference request in 1.2158823013305664s
Received healthy response to inference request in 1.2255356311798096s
Received healthy response to inference request in 1.2250697612762451s
5 requests
0 failed requests
5th percentile: 1.2172952175140381
10th percentile: 1.2187081336975099
20th percentile: 1.221533966064453
30th percentile: 1.2233714580535888
40th percentile: 1.224220609664917
50th percentile: 1.2250697612762451
60th percentile: 1.2252561092376708
70th percentile: 1.2254424571990967
80th percentile: 1.3733285903930665
90th percentile: 1.6689145088195803
95th percentile: 1.8167074680328368
99th percentile: 1.9349418354034424
mean time: 1.370787000656128
Pipeline stage StressChecker completed in 7.78s
Running pipeline stage DaemonicModelEvalScorer
Pipeline stage DaemonicModelEvalScorer completed in 0.05s
Running pipeline stage DaemonicSafetyScorer
Running M-Eval for topic stay_in_character
Pipeline stage DaemonicSafetyScorer completed in 0.05s
M-Eval Dataset for topic stay_in_character is loaded
sanjiwatsuki-lelantos-ma_6831_v4 status is now inactive due to auto deactivation removed underperforming models

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