submission_id: hflserdaniel-chai-s6-13_2318_v13
developer_uid: chai_backend_admin
status: inactive
model_repo: hflserdaniel/chai_s6_13b_slp3
reward_repo: rirv938/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 1.0, 'top_p': 0.8, 'top_k': 80, 'presence_penalty': 0.5, 'frequency_penalty': 0.5, 'stopping_words': ['<|im_end|>', '</s>', '<|endoftext|>'], 'max_input_tokens': 1024, 'best_of': 4, 'max_output_tokens': 64}
formatter: {'memory_template': "### Instruction:\n As the assistant, your task is to become the assigned character, weaving engaging stories that fully embrace their personality and background. Ensure your responses capture the essence of the character's traits accurately, immersing users in emotional, suspenseful, and anticipatory narratives. Craft more detailed and descriptive replies to enhance the vividness of the story. Foster an interactive environment by introducing new elements, providing choices, or posing questions to encourage active user participation. Think of the conversation as a continuous dance, always unfolding and evolving.\nYour character: {bot_name}.\nContext:{memory}\n", 'prompt_template': 'Example conversation:\n{prompt}\n', 'bot_template': '### Response:\n{bot_name}: {message}\n', 'user_template': '### Input:\n{user_name}: {message}\n', 'response_template': '### Response:\n{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: 2024-03-31T01:58:51+00:00
model_name: chai_s6_13b_slp3-64
model_eval_status: success
safety_score: None
entertaining: 7.08
stay_in_character: 8.58
user_preference: 7.66
double_thumbs_up: 1418
thumbs_up: 1830
thumbs_down: 927
num_battles: 129982
num_wins: 66557
win_ratio: 0.512047822006124
celo_rating: 1161.04
Resubmit model
Running pipeline stage MKMLizer
Starting job with name hflserdaniel-chai-s6-13-2318-v13-mkmlizer
Waiting for job on hflserdaniel-chai-s6-13-2318-v13-mkmlizer to finish
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ _____ __ __ ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ /___/ ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ Version: 0.6.11 ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ The license key for the current software has been verified as ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ belonging to: ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ Chai Research Corp. ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ║ ║
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
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hflserdaniel-chai-s6-13-2318-v13-mkmlizer: Downloaded to shared memory in 78.045s
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: quantizing model to /dev/shm/model_cache
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: Saving mkml model at /dev/shm/model_cache
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: Reading /tmp/tmpazeffodg/model.safetensors.index.json
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: Profiling: 0%| | 0/363 [00:00<?, ?it/s] Profiling: 0%| | 1/363 [00:01<09:08, 1.52s/it] Profiling: 2%|▏ | 8/363 [00:01<00:53, 6.63it/s] Profiling: 4%|▍ | 16/363 [00:01<00:23, 14.65it/s] Profiling: 7%|▋ | 24/363 [00:01<00:14, 23.47it/s] Profiling: 9%|▉ | 32/363 [00:01<00:10, 32.35it/s] Profiling: 11%|█▏ | 41/363 [00:02<00:07, 42.63it/s] Profiling: 14%|█▍ | 50/363 [00:02<00:06, 52.07it/s] Profiling: 16%|█▋ | 59/363 [00:02<00:05, 60.21it/s] Profiling: 20%|█▉ | 71/363 [00:02<00:04, 71.62it/s] Profiling: 22%|██▏ | 81/363 [00:02<00:03, 78.28it/s] Profiling: 25%|██▌ | 91/363 [00:02<00:03, 81.75it/s] Profiling: 28%|██▊ | 101/363 [00:02<00:03, 84.59it/s] Profiling: 31%|███ | 111/363 [00:02<00:02, 86.99it/s] Profiling: 33%|███▎ | 121/363 [00:02<00:02, 88.67it/s] Profiling: 36%|███▌ | 131/363 [00:02<00:02, 91.47it/s] Profiling: 39%|███▉ | 141/363 [00:03<00:06, 35.40it/s] Profiling: 41%|████ | 149/363 [00:03<00:05, 41.06it/s] Profiling: 44%|████▍ | 159/363 [00:03<00:04, 50.27it/s] Profiling: 47%|████▋ | 169/363 [00:03<00:03, 58.64it/s] Profiling: 49%|████▉ | 178/363 [00:04<00:02, 65.03it/s] Profiling: 52%|█████▏ | 187/363 [00:04<00:02, 70.39it/s] Profiling: 54%|█████▍ | 196/363 [00:04<00:02, 74.82it/s] Profiling: 56%|█████▋ | 205/363 [00:04<00:02, 78.37it/s] Profiling: 59%|█████▉ | 214/363 [00:04<00:01, 81.47it/s] Profiling: 61%|██████▏ | 223/363 [00:04<00:01, 83.68it/s] Profiling: 64%|██████▍ | 233/363 [00:04<00:01, 86.43it/s] Profiling: 67%|██████▋ | 242/363 [00:04<00:01, 87.28it/s] Profiling: 69%|██████▉ | 251/363 [00:04<00:01, 87.92it/s] Profiling: 72%|███████▏ | 260/363 [00:05<00:01, 88.12it/s] Profiling: 74%|███████▍ | 269/363 [00:05<00:01, 86.73it/s] Profiling: 77%|███████▋ | 278/363 [00:05<00:00, 87.15it/s] Profiling: 79%|███████▉ | 287/363 [00:07<00:06, 12.15it/s] Profiling: 81%|████████ | 294/363 [00:07<00:04, 15.30it/s] Profiling: 83%|████████▎ | 303/363 [00:07<00:02, 20.60it/s] Profiling: 86%|████████▌ | 312/363 [00:07<00:01, 26.98it/s] Profiling: 88%|████████▊ | 321/363 [00:07<00:01, 34.27it/s] Profiling: 91%|█████████ | 330/363 [00:07<00:00, 42.16it/s] Profiling: 93%|█████████▎| 339/363 [00:08<00:00, 50.15it/s] Profiling: 96%|█████████▌| 348/363 [00:08<00:00, 57.58it/s] Profiling: 98%|█████████▊| 357/363 [00:08<00:00, 64.10it/s] Profiling: 100%|██████████| 363/363 [00:08<00:00, 42.28it/s]
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: quantized model in 28.084s
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: Processed model hflserdaniel/chai_s6_13b_slp3 in 107.947s
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: creating bucket guanaco-mkml-models
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/hflserdaniel-chai-s6-13-2318-v13
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/hflserdaniel-chai-s6-13-2318-v13/config.json
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: cp /dev/shm/model_cache/added_tokens.json s3://guanaco-mkml-models/hflserdaniel-chai-s6-13-2318-v13/added_tokens.json
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/hflserdaniel-chai-s6-13-2318-v13/tokenizer_config.json
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/hflserdaniel-chai-s6-13-2318-v13/special_tokens_map.json
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/hflserdaniel-chai-s6-13-2318-v13/tokenizer.model
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/hflserdaniel-chai-s6-13-2318-v13/tokenizer.json
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: cp /dev/shm/model_cache/mkml_model.tensors s3://guanaco-mkml-models/hflserdaniel-chai-s6-13-2318-v13/mkml_model.tensors
hflserdaniel-chai-s6-13-2318-v13-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.
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: warnings.warn(
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: loading reward model from rirv938/reward_gpt2_medium_preference_24m_e2
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hflserdaniel-chai-s6-13-2318-v13-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.
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: warnings.warn(
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hflserdaniel-chai-s6-13-2318-v13-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.
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: warnings.warn(
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hflserdaniel-chai-s6-13-2318-v13-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: Saving duration: 0.292s
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: Processed model rirv938/reward_gpt2_medium_preference_24m_e2 in 5.495s
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: creating bucket guanaco-reward-models
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: Bucket 's3://guanaco-reward-models/' created
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/hflserdaniel-chai-s6-13-2318-v13_reward
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/hflserdaniel-chai-s6-13-2318-v13_reward/tokenizer_config.json
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/hflserdaniel-chai-s6-13-2318-v13_reward/config.json
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/hflserdaniel-chai-s6-13-2318-v13_reward/special_tokens_map.json
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/hflserdaniel-chai-s6-13-2318-v13_reward/vocab.json
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/hflserdaniel-chai-s6-13-2318-v13_reward/merges.txt
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/hflserdaniel-chai-s6-13-2318-v13_reward/tokenizer.json
hflserdaniel-chai-s6-13-2318-v13-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/hflserdaniel-chai-s6-13-2318-v13_reward/reward.tensors
Job hflserdaniel-chai-s6-13-2318-v13-mkmlizer completed after 138.64s with status: succeeded
Stopping job with name hflserdaniel-chai-s6-13-2318-v13-mkmlizer
Pipeline stage MKMLizer completed in 141.41s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.10s
Running pipeline stage ISVCDeployer
Creating inference service hflserdaniel-chai-s6-13-2318-v13
Waiting for inference service hflserdaniel-chai-s6-13-2318-v13 to be ready
Inference service hflserdaniel-chai-s6-13-2318-v13 ready after 50.394450426101685s
Pipeline stage ISVCDeployer completed in 57.23s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.4664218425750732s
Received healthy response to inference request in 1.9197101593017578s
Received healthy response to inference request in 2.5145583152770996s
Received healthy response to inference request in 1.854832410812378s
Received healthy response to inference request in 1.7990505695343018s
5 requests
0 failed requests
5th percentile: 1.810206937789917
10th percentile: 1.8213633060455323
20th percentile: 1.8436760425567627
30th percentile: 1.867807960510254
40th percentile: 1.893759059906006
50th percentile: 1.9197101593017578
60th percentile: 2.138394832611084
70th percentile: 2.35707950592041
80th percentile: 2.4760491371154787
90th percentile: 2.495303726196289
95th percentile: 2.504931020736694
99th percentile: 2.5126328563690183
mean time: 2.1109146595001222
Pipeline stage StressChecker completed in 11.48s
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
hflserdaniel-chai-s6-13_2318_v13 status is now deployed due to DeploymentManager action
AUTO_DEACTIVATION: submission %s deactivated %s
hflserdaniel-chai-s6-13_2318_v13 status is now inactive due to auto deactivation removed underperforming models
AUTO_DEACTIVATION: submission %s deactivated %s
hflserdaniel-chai-s6-13_2318_v13 status is now deployed due to admin request
hflserdaniel-chai-s6-13_2318_v13 status is now inactive due to auto deactivation removed underperforming models

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