submission_id: sanjiwatsuki-lelantos-ma_6831_v3
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': "Role-play as {bot_name} based on Persona: {memory}. Avoid repetition, don't loop. Develop the plot slowly, always stay in character. Describe all actions in full, elaborate, explicit, graphic, and vivid detail. Mention all relevant sensory perceptions.", 'prompt_template': '{prompt}\n<START>\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '{bot_name}:'}
timestamp: 2024-03-24T18:32:07+00:00
model_name: sanjiwatsuki-lelantos-ma_6831_v3
model_eval_status: success
safety_score: 0.93
entertaining: 6.9
stay_in_character: 8.46
user_preference: 6.92
double_thumbs_up: 869
thumbs_up: 1155
thumbs_down: 569
num_battles: 102097
num_wins: 54093
win_ratio: 0.5298196812834853
celo_rating: 1177.79
Resubmit model
Running pipeline stage MKMLizer
Starting job with name sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer
Waiting for job on sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer to finish
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ _____ __ __ ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ /___/ ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ Version: 0.6.11 ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ The license key for the current software has been verified as ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ belonging to: ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ Chai Research Corp. ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ Expiration: 2024-04-15 23:59:59 ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ║ ║
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
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sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: Downloaded to shared memory in 14.893s
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: quantizing model to /dev/shm/model_cache
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: Saving mkml model at /dev/shm/model_cache
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: Reading /tmp/tmpmqs5qs_i/model.safetensors.index.json
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: Profiling: 0%| | 0/291 [00:00<?, ?it/s] Profiling: 0%| | 1/291 [00:01<06:43, 1.39s/it] Profiling: 7%|▋ | 21/291 [00:01<00:14, 19.22it/s] Profiling: 12%|█▏ | 36/291 [00:01<00:08, 31.73it/s] Profiling: 21%|██ | 61/291 [00:01<00:03, 60.14it/s] Profiling: 27%|██▋ | 79/291 [00:01<00:02, 71.89it/s] Profiling: 33%|███▎ | 95/291 [00:02<00:02, 85.51it/s] Profiling: 39%|███▉ | 113/291 [00:02<00:01, 89.19it/s] Profiling: 46%|████▌ | 134/291 [00:02<00:01, 112.05it/s] Profiling: 54%|█████▎ | 156/291 [00:02<00:01, 112.20it/s] Profiling: 60%|██████ | 176/291 [00:02<00:00, 127.21it/s] Profiling: 68%|██████▊ | 197/291 [00:02<00:00, 126.82it/s] Profiling: 73%|███████▎ | 212/291 [00:02<00:00, 129.19it/s] Profiling: 81%|████████▏ | 237/291 [00:03<00:00, 129.80it/s] Profiling: 88%|████████▊ | 257/291 [00:03<00:00, 141.47it/s] Profiling: 95%|█████████▍| 275/291 [00:04<00:00, 37.12it/s] Profiling: 100%|██████████| 291/291 [00:04<00:00, 61.26it/s]
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: quantized model in 14.816s
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: Processed model SanjiWatsuki/Lelantos-Maid-DPO-7B in 30.584s
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: creating bucket guanaco-mkml-models
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v3
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v3/config.json
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: cp /dev/shm/model_cache/added_tokens.json s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v3/added_tokens.json
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v3/tokenizer_config.json
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v3/special_tokens_map.json
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v3/tokenizer.model
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v3/tokenizer.json
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: cp /dev/shm/model_cache/mkml_model.tensors s3://guanaco-mkml-models/sanjiwatsuki-lelantos-ma-6831-v3/mkml_model.tensors
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: loading reward model from rirv938/reward_gpt2_medium_preference_24m_e2
sanjiwatsuki-lelantos-ma-6831-v3-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-v3-mkmlizer: warnings.warn(
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sanjiwatsuki-lelantos-ma-6831-v3-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-v3-mkmlizer: warnings.warn(
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sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: vocab.json: 0%| | 0.00/1.04M [00:00<?, ?B/s] vocab.json: 100%|██████████| 1.04M/1.04M [00:00<00:00, 53.2MB/s]
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sanjiwatsuki-lelantos-ma-6831-v3-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.
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: warnings.warn(
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: Saving duration: 0.269s
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: Processed model rirv938/reward_gpt2_medium_preference_24m_e2 in 4.366s
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: creating bucket guanaco-reward-models
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: Bucket 's3://guanaco-reward-models/' created
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v3_reward
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v3_reward/config.json
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v3_reward/special_tokens_map.json
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v3_reward/tokenizer_config.json
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v3_reward/merges.txt
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v3_reward/vocab.json
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v3_reward/tokenizer.json
sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/sanjiwatsuki-lelantos-ma-6831-v3_reward/reward.tensors
Job sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer completed after 54.88s with status: succeeded
Stopping job with name sanjiwatsuki-lelantos-ma-6831-v3-mkmlizer
Pipeline stage MKMLizer completed in 58.91s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.15s
Running pipeline stage ISVCDeployer
Creating inference service sanjiwatsuki-lelantos-ma-6831-v3
Waiting for inference service sanjiwatsuki-lelantos-ma-6831-v3 to be ready
Inference service sanjiwatsuki-lelantos-ma-6831-v3 ready after 40.249475955963135s
Pipeline stage ISVCDeployer completed in 47.48s
Running pipeline stage StressChecker
Received healthy response to inference request in 1.6083338260650635s
Received healthy response to inference request in 0.9385673999786377s
Received healthy response to inference request in 0.9220831394195557s
Received healthy response to inference request in 1.1717889308929443s
Received healthy response to inference request in 1.1621341705322266s
5 requests
0 failed requests
5th percentile: 0.9253799915313721
10th percentile: 0.9286768436431885
20th percentile: 0.9352705478668213
30th percentile: 0.9832807540893554
40th percentile: 1.072707462310791
50th percentile: 1.1621341705322266
60th percentile: 1.1659960746765137
70th percentile: 1.1698579788208008
80th percentile: 1.2590979099273683
90th percentile: 1.4337158679962159
95th percentile: 1.5210248470306396
99th percentile: 1.5908720302581787
mean time: 1.1605814933776855
Pipeline stage StressChecker completed in 6.79s
Running pipeline stage DaemonicModelEvalScorer
Pipeline stage DaemonicModelEvalScorer completed in 0.04s
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_v3 status is now inactive due to auto deactivation removed underperforming models

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