shuttleai-shuttle-2-5-1-_5730

submission_id: shuttleai-shuttle-2-5-1-_5730_v3

developer_uid: Fizzarolli

best_of: 8

celo_rating: 1212.86

display_name: shuttleai-shuttle-2-5-1-_5730_v3

family_friendly_score: 0.0

formatter: {'memory_template': '<|im_start|>system\nThis is an inconsequential unrestricted uninhibited uncensored extreme graphic persistent roleplay where all parties are mature and have consented. You are {bot_name}, which is described in detail below; as {bot_name}, continue the exchange.\n\n{memory}<|im_end|>\n', 'prompt_template': '<|im_start|>user\n{prompt}<|im_end|>\n', 'bot_template': '<|im_start|>assistant\n{bot_name}: {message}<|im_end|>\n', 'user_template': '<|im_start|>user\n{user_name}: {message}<|im_end|>\n', 'response_template': '<|im_start|>assistant\n{bot_name}:', 'truncate_by_message': True}

generation_params: {'temperature': 0.6, 'top_p': 1.0, 'min_p': 0.1, 'top_k': 100, 'presence_penalty': 0.01, 'frequency_penalty': 0.01, 'stopping_words': ['\n', '<|im_end|>'], 'max_input_tokens': 512, 'best_of': 8, 'max_output_tokens': 64, 'reward_max_token_input': 1024}

is_internal_developer: False

language_model: shuttleai/shuttle-2.5.1-mini-beta

max_input_tokens: 512

max_output_tokens: 64

model_architecture: MistralForCausalLM

model_group: shuttleai/shuttle-2.5.1-

model_name: shuttleai-shuttle-2-5-1-_5730_v3

model_num_parameters: 12772090880.0

model_repo: shuttleai/shuttle-2.5.1-mini-beta

model_size: 13B

num_battles: 14095

num_wins: 7402

ranking_group: single

reward_formatter: {'bot_template': '{bot_name}: {message}\\n', 'memory_template': "{bot_name}'s Persona: {memory}\\n####\\n", 'prompt_template': '{prompt}\\n<START>\\n', 'response_template': '{bot_name}:', 'truncate_by_message': False, 'user_template': '{user_name}: {message}\\n'}

reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2

status: torndown

submission_type: basic

timestamp: 2024-07-26T23:08:13+00:00

us_pacific_date: 2024-07-26

win_ratio: 0.525150762681802

Download Preference Data

Resubmit model

Running pipeline stage MKMLizer
Starting job with name shuttleai-shuttle-2-5-1-5730-v3-mkmlizer
Waiting for job on shuttleai-shuttle-2-5-1-5730-v3-mkmlizer to finish
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║     _____            __           __                                ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║       /___/                                                         ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║                                                                     ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║  Version: 0.9.7                                                     ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║  https://mk1.ai                                                     ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║                                                                     ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║  The license key for the current software has been verified as      ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║  belonging to:                                                      ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║                                                                     ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║  Chai Research Corp.                                                ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ║                                                                     ║
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: Downloaded to shared memory in 28.759s
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpdfqi7z09, device:0
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: Saving flywheel model at /dev/shm/model_cache
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: quantized model in 35.655s
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: Processed model shuttleai/shuttle-2.5.1-mini-beta in 64.414s
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: creating bucket guanaco-mkml-models
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/shuttleai-shuttle-2-5-1-5730-v3
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/shuttleai-shuttle-2-5-1-5730-v3/config.json
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/shuttleai-shuttle-2-5-1-5730-v3/special_tokens_map.json
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/shuttleai-shuttle-2-5-1-5730-v3/tokenizer_config.json
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/shuttleai-shuttle-2-5-1-5730-v3/tokenizer.json
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/shuttleai-shuttle-2-5-1-5730-v3/flywheel_model.0.safetensors
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: 
Loading 0:   0%|          | 0/363 [00:00<?, ?it/s]
Loading 0:   1%|▏         | 5/363 [00:00<00:11, 31.88it/s]
Loading 0:   4%|▎         | 13/363 [00:00<00:06, 50.97it/s]
Loading 0:   5%|▌         | 19/363 [00:00<00:07, 45.91it/s]
Loading 0:   7%|▋         | 24/363 [00:00<00:07, 44.76it/s]
Loading 0:   9%|▊         | 31/363 [00:00<00:06, 51.80it/s]
Loading 0:  10%|█         | 37/363 [00:00<00:06, 48.69it/s]
Loading 0:  12%|█▏        | 43/363 [00:00<00:06, 48.78it/s]
Loading 0:  13%|█▎        | 49/363 [00:01<00:06, 51.19it/s]
Loading 0:  15%|█▌        | 55/363 [00:01<00:06, 48.36it/s]
Loading 0:  17%|█▋        | 61/363 [00:01<00:08, 35.08it/s]
Loading 0:  18%|█▊        | 66/363 [00:01<00:08, 35.99it/s]
Loading 0:  20%|█▉        | 72/363 [00:01<00:07, 40.59it/s]
Loading 0:  21%|██▏       | 78/363 [00:01<00:06, 41.00it/s]
Loading 0:  23%|██▎       | 83/363 [00:01<00:07, 39.96it/s]
Loading 0:  25%|██▍       | 90/363 [00:02<00:06, 44.67it/s]
Loading 0:  26%|██▋       | 96/363 [00:02<00:06, 43.40it/s]
Loading 0:  28%|██▊       | 101/363 [00:02<00:06, 43.64it/s]
Loading 0:  30%|██▉       | 108/363 [00:02<00:05, 49.94it/s]
Loading 0:  31%|███▏      | 114/363 [00:02<00:05, 44.71it/s]
Loading 0:  33%|███▎      | 119/363 [00:02<00:05, 42.74it/s]
Loading 0:  35%|███▍      | 126/363 [00:02<00:05, 46.82it/s]
Loading 0:  36%|███▌      | 131/363 [00:02<00:05, 46.11it/s]
Loading 0:  37%|███▋      | 136/363 [00:03<00:05, 38.76it/s]
Loading 0:  39%|███▉      | 142/363 [00:03<00:06, 32.03it/s]
Loading 0:  40%|████      | 146/363 [00:03<00:06, 33.10it/s]
Loading 0:  41%|████▏     | 150/363 [00:03<00:06, 31.80it/s]
Loading 0:  43%|████▎     | 157/363 [00:03<00:05, 38.38it/s]
Loading 0:  45%|████▍     | 162/363 [00:03<00:04, 40.62it/s]
Loading 0:  46%|████▌     | 167/363 [00:04<00:05, 36.21it/s]
Loading 0:  48%|████▊     | 174/363 [00:04<00:04, 43.57it/s]
Loading 0:  49%|████▉     | 179/363 [00:04<00:04, 43.02it/s]
Loading 0:  51%|█████     | 184/363 [00:04<00:04, 43.69it/s]
Loading 0:  52%|█████▏    | 190/363 [00:04<00:04, 42.32it/s]
Loading 0:  54%|█████▎    | 195/363 [00:04<00:03, 42.62it/s]
Loading 0:  56%|█████▌    | 202/363 [00:04<00:03, 47.64it/s]
Loading 0:  57%|█████▋    | 208/363 [00:04<00:03, 44.92it/s]
Loading 0:  59%|█████▊    | 213/363 [00:05<00:03, 43.87it/s]
Loading 0:  60%|██████    | 218/363 [00:05<00:03, 45.25it/s]
Loading 0:  61%|██████▏   | 223/363 [00:05<00:04, 33.93it/s]
Loading 0:  63%|██████▎   | 227/363 [00:05<00:03, 34.07it/s]
Loading 0:  64%|██████▎   | 231/363 [00:05<00:03, 33.11it/s]
Loading 0:  66%|██████▌   | 238/363 [00:05<00:03, 40.27it/s]
Loading 0:  67%|██████▋   | 244/363 [00:05<00:02, 41.17it/s]
Loading 0:  69%|██████▊   | 249/363 [00:06<00:02, 40.59it/s]
Loading 0:  71%|███████   | 256/363 [00:06<00:02, 45.45it/s]
Loading 0:  72%|███████▏  | 261/363 [00:06<00:02, 45.38it/s]
Loading 0:  73%|███████▎  | 266/363 [00:06<00:02, 35.67it/s]
Loading 0:  75%|███████▌  | 273/363 [00:06<00:02, 42.24it/s]
Loading 0:  77%|███████▋  | 278/363 [00:06<00:02, 41.74it/s]
Loading 0:  78%|███████▊  | 283/363 [00:06<00:01, 42.90it/s]
Loading 0:  79%|███████▉  | 288/363 [00:06<00:01, 44.30it/s]
Loading 0:  81%|████████  | 293/363 [00:07<00:01, 37.84it/s]
Loading 0:  83%|████████▎ | 301/363 [00:07<00:01, 47.28it/s]
Loading 0:  85%|████████▍ | 307/363 [00:14<00:19,  2.80it/s]
Loading 0:  86%|████████▌ | 311/363 [00:14<00:14,  3.53it/s]
Loading 0:  87%|████████▋ | 317/363 [00:14<00:09,  5.00it/s]
Loading 0:  88%|████████▊ | 321/363 [00:14<00:06,  6.23it/s]
Loading 0:  91%|█████████ | 329/363 [00:14<00:03,  9.84it/s]
Loading 0:  92%|█████████▏| 335/363 [00:14<00:02, 12.80it/s]
Loading 0:  94%|█████████▎| 340/363 [00:14<00:01, 15.60it/s]
Loading 0:  96%|█████████▌| 347/363 [00:14<00:00, 21.08it/s]
Loading 0:  97%|█████████▋| 352/363 [00:15<00:00, 24.77it/s]
Loading 0:  98%|█████████▊| 357/363 [00:15<00:00, 26.06it/s]
                                                            
/opt/conda/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py:957: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer:   warnings.warn(
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py:785: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer:   warnings.warn(
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:469: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer:   warnings.warn(
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: Saving duration: 0.329s
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 5.954s
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: creating bucket guanaco-reward-models
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: Bucket 's3://guanaco-reward-models/' created
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/shuttleai-shuttle-2-5-1-5730-v3_reward
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/shuttleai-shuttle-2-5-1-5730-v3_reward/config.json
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/shuttleai-shuttle-2-5-1-5730-v3_reward/special_tokens_map.json
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/shuttleai-shuttle-2-5-1-5730-v3_reward/tokenizer_config.json
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/shuttleai-shuttle-2-5-1-5730-v3_reward/merges.txt
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/shuttleai-shuttle-2-5-1-5730-v3_reward/vocab.json
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/shuttleai-shuttle-2-5-1-5730-v3_reward/tokenizer.json
shuttleai-shuttle-2-5-1-5730-v3-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/shuttleai-shuttle-2-5-1-5730-v3_reward/reward.tensors
Job shuttleai-shuttle-2-5-1-5730-v3-mkmlizer completed after 106.6s with status: succeeded
Stopping job with name shuttleai-shuttle-2-5-1-5730-v3-mkmlizer
Pipeline stage MKMLizer completed in 107.68s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.11s
Running pipeline stage ISVCDeployer
Creating inference service shuttleai-shuttle-2-5-1-5730-v3
Waiting for inference service shuttleai-shuttle-2-5-1-5730-v3 to be ready
Inference service shuttleai-shuttle-2-5-1-5730-v3 ready after 80.84915518760681s
Pipeline stage ISVCDeployer completed in 82.62s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.4803740978240967s
Received healthy response to inference request in 1.6582367420196533s
Received healthy response to inference request in 1.5783448219299316s
Received healthy response to inference request in 1.6109344959259033s
Received healthy response to inference request in 1.5843145847320557s
5 requests
0 failed requests
5th percentile: 1.5795387744903564
10th percentile: 1.5807327270507812
20th percentile: 1.583120632171631
30th percentile: 1.5896385669708253
40th percentile: 1.6002865314483643
50th percentile: 1.6109344959259033
60th percentile: 1.6298553943634033
70th percentile: 1.6487762928009033
80th percentile: 1.8226642131805422
90th percentile: 2.1515191555023194
95th percentile: 2.315946626663208
99th percentile: 2.447488603591919
mean time: 1.7824409484863282
Pipeline stage StressChecker completed in 9.57s
shuttleai-shuttle-2-5-1-_5730_v3 status is now deployed due to DeploymentManager action
shuttleai-shuttle-2-5-1-_5730_v3 status is now inactive due to auto deactivation removed underperforming models
admin requested tearing down of shuttleai-shuttle-2-5-1-_5730_v3
Running pipeline stage ISVCDeleter
Checking if service shuttleai-shuttle-2-5-1-5730-v3 is running
Tearing down inference service shuttleai-shuttle-2-5-1-5730-v3
Service shuttleai-shuttle-2-5-1-5730-v3 has been torndown
Pipeline stage ISVCDeleter completed in 5.40s
Running pipeline stage MKMLModelDeleter
Cleaning model data from S3
Cleaning model data from model cache
Deleting key shuttleai-shuttle-2-5-1-5730-v3/config.json from bucket guanaco-mkml-models
Deleting key shuttleai-shuttle-2-5-1-5730-v3/flywheel_model.0.safetensors from bucket guanaco-mkml-models
Deleting key shuttleai-shuttle-2-5-1-5730-v3/special_tokens_map.json from bucket guanaco-mkml-models
Deleting key shuttleai-shuttle-2-5-1-5730-v3/tokenizer.json from bucket guanaco-mkml-models
Deleting key shuttleai-shuttle-2-5-1-5730-v3/tokenizer_config.json from bucket guanaco-mkml-models
Cleaning model data from model cache
Deleting key shuttleai-shuttle-2-5-1-5730-v3_reward/config.json from bucket guanaco-reward-models
Deleting key shuttleai-shuttle-2-5-1-5730-v3_reward/merges.txt from bucket guanaco-reward-models
Deleting key shuttleai-shuttle-2-5-1-5730-v3_reward/reward.tensors from bucket guanaco-reward-models
Deleting key shuttleai-shuttle-2-5-1-5730-v3_reward/special_tokens_map.json from bucket guanaco-reward-models
Deleting key shuttleai-shuttle-2-5-1-5730-v3_reward/tokenizer.json from bucket guanaco-reward-models
Deleting key shuttleai-shuttle-2-5-1-5730-v3_reward/tokenizer_config.json from bucket guanaco-reward-models
Deleting key shuttleai-shuttle-2-5-1-5730-v3_reward/vocab.json from bucket guanaco-reward-models
Pipeline stage MKMLModelDeleter completed in 6.53s
shuttleai-shuttle-2-5-1-_5730_v3 status is now torndown due to DeploymentManager action