submission_id: chaiml-phase2-winner-13b2_v272
developer_uid: chai_backend_admin
status: torndown
model_repo: ChaiML/phase2_winner_13b2
reward_repo: rirv938/gpt2_ties_merge_preference_plus_classic_e2_density_99
generation_params: {'temperature': 1.0733671330918084, 'top_p': 0.6971846333941389, 'min_p': 0.0, 'top_k': 50, 'presence_penalty': 0.0, 'frequency_penalty': 0.312882778758545, 'stopping_words': ['\n'], 'max_input_tokens': 512, 'best_of': 8, 'max_output_tokens': 96}
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}:', 'truncate_by_message': False}
reward_formatter: {'memory_template': 'Memory: {memory}\n', 'prompt_template': '{prompt}\n', 'bot_template': 'Bot: {message}\n', 'user_template': 'User: {message}\n', 'response_template': 'Bot:', 'truncate_by_message': False}
timestamp: 2024-03-31T01:28:09+00:00
model_name: chaiml-phase2-winner-96
model_eval_status: success
model_group: ChaiML/phase2_winner_13b
num_battles: 116
num_wins: 52
celo_rating: None
propriety_score: 0.0
propriety_total_count: 0.0
submission_type: basic
model_architecture: LlamaForCausalLM
model_num_parameters: 13015864320.0
best_of: 8
max_input_tokens: 512
max_output_tokens: 96
display_name: chaiml-phase2-winner-96
ineligible_reason: max_output_tokens!=64
language_model: ChaiML/phase2_winner_13b2
model_size: 13B
reward_model: rirv938/gpt2_ties_merge_preference_plus_classic_e2_density_99
us_pacific_date: 2024-03-30
win_ratio: 0.4482758620689655
preference_data_url: None
Resubmit model
Running pipeline stage MKMLizer
Starting job with name chaiml-phase2-winner-13b2-v272-mkmlizer
Waiting for job on chaiml-phase2-winner-13b2-v272-mkmlizer to finish
chaiml-phase2-winner-13b2-v272-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-phase2-winner-13b2-v272-mkmlizer: ║     _____            __           __                                ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║       /___/                                                         ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║                                                                     ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║  Version: 0.6.11                                                    ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║                                                                     ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║  The license key for the current software has been verified as      ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║  belonging to:                                                      ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║                                                                     ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║  Chai Research Corp.                                                ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║  Expiration: 2024-07-15 23:59:59                                    ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ║                                                                     ║
chaiml-phase2-winner-13b2-v272-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-phase2-winner-13b2-v272-mkmlizer: 
.gitattributes:   0%|          | 0.00/1.52k [00:00<?, ?B/s]
.gitattributes: 100%|██████████| 1.52k/1.52k [00:00<00:00, 19.0MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
README.md:   0%|          | 0.00/1.53k [00:00<?, ?B/s]
README.md: 100%|██████████| 1.53k/1.53k [00:00<00:00, 24.1MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
config.json:   0%|          | 0.00/651 [00:00<?, ?B/s]
config.json: 100%|██████████| 651/651 [00:00<00:00, 7.06MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
generation_config.json:   0%|          | 0.00/170 [00:00<?, ?B/s]
generation_config.json: 100%|██████████| 170/170 [00:00<00:00, 2.79MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
pytorch_model-00001-of-00003.bin:   0%|          | 0.00/9.95G [00:00<?, ?B/s]
pytorch_model-00001-of-00003.bin:   0%|          | 10.5M/9.95G [00:00<02:05, 79.3MB/s]
pytorch_model-00001-of-00003.bin:   0%|          | 21.0M/9.95G [00:00<02:17, 72.3MB/s]
pytorch_model-00001-of-00003.bin:   1%|          | 73.4M/9.95G [00:00<00:41, 237MB/s] 
pytorch_model-00001-of-00003.bin:   1%|▏         | 126M/9.95G [00:00<00:42, 233MB/s] 
pytorch_model-00001-of-00003.bin:   2%|▏         | 210M/9.95G [00:00<00:25, 385MB/s]
pytorch_model-00001-of-00003.bin:   3%|▎         | 273M/9.95G [00:00<00:22, 440MB/s]
pytorch_model-00001-of-00003.bin:   3%|▎         | 336M/9.95G [00:00<00:19, 488MB/s]
pytorch_model-00001-of-00003.bin:   4%|▍         | 440M/9.95G [00:01<00:15, 633MB/s]
pytorch_model-00001-of-00003.bin:   5%|▌         | 545M/9.95G [00:01<00:12, 739MB/s]
pytorch_model-00001-of-00003.bin:   7%|▋         | 661M/9.95G [00:01<00:15, 602MB/s]
pytorch_model-00001-of-00003.bin:   7%|▋         | 744M/9.95G [00:01<00:14, 642MB/s]
pytorch_model-00001-of-00003.bin:   9%|▉         | 881M/9.95G [00:01<00:11, 796MB/s]
pytorch_model-00001-of-00003.bin:  10%|▉         | 975M/9.95G [00:01<00:15, 590MB/s]
pytorch_model-00001-of-00003.bin:  11%|█         | 1.08G/9.95G [00:01<00:13, 660MB/s]
pytorch_model-00001-of-00003.bin:  12%|█▏        | 1.16G/9.95G [00:02<00:14, 588MB/s]
pytorch_model-00001-of-00003.bin:  13%|█▎        | 1.28G/9.95G [00:02<00:12, 680MB/s]
pytorch_model-00001-of-00003.bin:  14%|█▎        | 1.36G/9.95G [00:02<00:14, 595MB/s]
pytorch_model-00001-of-00003.bin:  15%|█▍        | 1.48G/9.95G [00:02<00:11, 707MB/s]
pytorch_model-00001-of-00003.bin:  16%|█▌        | 1.56G/9.95G [00:02<00:12, 686MB/s]
pytorch_model-00001-of-00003.bin:  17%|█▋        | 1.65G/9.95G [00:02<00:13, 604MB/s]
pytorch_model-00001-of-00003.bin:  18%|█▊        | 1.79G/9.95G [00:03<00:10, 752MB/s]
pytorch_model-00001-of-00003.bin:  20%|█▉        | 1.98G/9.95G [00:03<00:08, 996MB/s]
pytorch_model-00001-of-00003.bin:  21%|██        | 2.10G/9.95G [00:03<00:09, 800MB/s]
pytorch_model-00001-of-00003.bin:  22%|██▏       | 2.20G/9.95G [00:03<00:09, 842MB/s]
pytorch_model-00001-of-00003.bin:  23%|██▎       | 2.31G/9.95G [00:03<00:10, 759MB/s]
pytorch_model-00001-of-00003.bin:  24%|██▍       | 2.40G/9.95G [00:03<00:11, 685MB/s]
pytorch_model-00001-of-00003.bin:  26%|██▌       | 2.56G/9.95G [00:03<00:08, 872MB/s]
pytorch_model-00001-of-00003.bin:  27%|██▋       | 2.66G/9.95G [00:04<00:08, 888MB/s]
pytorch_model-00001-of-00003.bin:  28%|██▊       | 2.77G/9.95G [00:04<00:10, 654MB/s]
pytorch_model-00001-of-00003.bin:  29%|██▊       | 2.85G/9.95G [00:04<00:11, 630MB/s]
pytorch_model-00001-of-00003.bin:  30%|██▉       | 2.96G/9.95G [00:04<00:09, 715MB/s]
pytorch_model-00001-of-00003.bin:  31%|███       | 3.10G/9.95G [00:04<00:08, 825MB/s]
pytorch_model-00001-of-00003.bin:  32%|███▏      | 3.20G/9.95G [00:04<00:10, 668MB/s]
pytorch_model-00001-of-00003.bin:  33%|███▎      | 3.28G/9.95G [00:05<00:09, 674MB/s]
pytorch_model-00001-of-00003.bin:  34%|███▍      | 3.41G/9.95G [00:05<00:08, 800MB/s]
pytorch_model-00001-of-00003.bin:  35%|███▌      | 3.51G/9.95G [00:05<00:07, 843MB/s]
pytorch_model-00001-of-00003.bin:  36%|███▋      | 3.61G/9.95G [00:05<00:08, 749MB/s]
pytorch_model-00001-of-00003.bin:  37%|███▋      | 3.71G/9.95G [00:05<00:08, 772MB/s]
pytorch_model-00001-of-00003.bin:  38%|███▊      | 3.80G/9.95G [00:05<00:08, 699MB/s]
pytorch_model-00001-of-00003.bin:  39%|███▉      | 3.88G/9.95G [00:05<00:08, 727MB/s]
pytorch_model-00001-of-00003.bin:  40%|████      | 4.01G/9.95G [00:05<00:07, 838MB/s]
pytorch_model-00001-of-00003.bin:  41%|████      | 4.10G/9.95G [00:06<00:07, 736MB/s]
pytorch_model-00001-of-00003.bin:  42%|████▏     | 4.20G/9.95G [00:06<00:07, 789MB/s]
pytorch_model-00001-of-00003.bin:  44%|████▍     | 4.37G/9.95G [00:06<00:05, 1.01GB/s]
pytorch_model-00001-of-00003.bin:  45%|████▌     | 4.49G/9.95G [00:06<00:06, 829MB/s] 
pytorch_model-00001-of-00003.bin:  46%|████▌     | 4.58G/9.95G [00:06<00:07, 753MB/s]
pytorch_model-00001-of-00003.bin:  47%|████▋     | 4.67G/9.95G [00:06<00:07, 690MB/s]
pytorch_model-00001-of-00003.bin:  48%|████▊     | 4.77G/9.95G [00:06<00:06, 764MB/s]
pytorch_model-00001-of-00003.bin:  49%|████▉     | 4.90G/9.95G [00:06<00:05, 878MB/s]
pytorch_model-00001-of-00003.bin:  50%|█████     | 5.00G/9.95G [00:07<00:06, 822MB/s]
pytorch_model-00001-of-00003.bin:  51%|█████     | 5.10G/9.95G [00:07<00:07, 639MB/s]
pytorch_model-00001-of-00003.bin:  52%|█████▏    | 5.20G/9.95G [00:07<00:06, 719MB/s]
pytorch_model-00001-of-00003.bin:  53%|█████▎    | 5.28G/9.95G [00:07<00:07, 630MB/s]
pytorch_model-00001-of-00003.bin:  54%|█████▍    | 5.40G/9.95G [00:07<00:06, 674MB/s]
pytorch_model-00001-of-00003.bin:  55%|█████▌    | 5.51G/9.95G [00:07<00:05, 754MB/s]
pytorch_model-00001-of-00003.bin:  57%|█████▋    | 5.67G/9.95G [00:08<00:04, 963MB/s]
pytorch_model-00001-of-00003.bin:  58%|█████▊    | 5.79G/9.95G [00:08<00:04, 850MB/s]
pytorch_model-00001-of-00003.bin:  59%|█████▉    | 5.88G/9.95G [00:08<00:05, 788MB/s]
pytorch_model-00001-of-00003.bin:  61%|██████    | 6.05G/9.95G [00:08<00:03, 988MB/s]
pytorch_model-00001-of-00003.bin:  63%|██████▎   | 6.22G/9.95G [00:08<00:03, 1.15GB/s]
pytorch_model-00001-of-00003.bin:  65%|██████▌   | 6.49G/9.95G [00:08<00:02, 1.53GB/s]
pytorch_model-00001-of-00003.bin:  68%|██████▊   | 6.73G/9.95G [00:08<00:01, 1.76GB/s]
pytorch_model-00001-of-00003.bin:  70%|███████   | 6.99G/9.95G [00:08<00:01, 2.00GB/s]
pytorch_model-00001-of-00003.bin:  73%|███████▎  | 7.25G/9.95G [00:08<00:01, 2.12GB/s]
pytorch_model-00001-of-00003.bin:  75%|███████▌  | 7.48G/9.95G [00:09<00:01, 2.13GB/s]
pytorch_model-00001-of-00003.bin:  77%|███████▋  | 7.70G/9.95G [00:09<00:01, 2.09GB/s]
pytorch_model-00001-of-00003.bin:  80%|███████▉  | 7.92G/9.95G [00:09<00:01, 1.82GB/s]
pytorch_model-00001-of-00003.bin:  82%|████████▏ | 8.12G/9.95G [00:09<00:01, 1.14GB/s]
pytorch_model-00001-of-00003.bin:  83%|████████▎ | 8.27G/9.95G [00:09<00:01, 1.09GB/s]
pytorch_model-00001-of-00003.bin:  85%|████████▍ | 8.43G/9.95G [00:09<00:01, 1.17GB/s]
pytorch_model-00001-of-00003.bin:  86%|████████▌ | 8.58G/9.95G [00:10<00:01, 1.14GB/s]
pytorch_model-00001-of-00003.bin:  88%|████████▊ | 8.71G/9.95G [00:10<00:01, 888MB/s] 
pytorch_model-00001-of-00003.bin:  89%|████████▊ | 8.83G/9.95G [00:10<00:01, 906MB/s]
pytorch_model-00001-of-00003.bin:  90%|████████▉ | 8.94G/9.95G [00:10<00:01, 938MB/s]
pytorch_model-00001-of-00003.bin:  91%|█████████▏| 9.08G/9.95G [00:10<00:00, 1.02GB/s]
pytorch_model-00001-of-00003.bin:  94%|█████████▎| 9.31G/9.95G [00:10<00:00, 1.32GB/s]
pytorch_model-00001-of-00003.bin:  97%|█████████▋| 9.61G/9.95G [00:10<00:00, 1.68GB/s]
pytorch_model-00001-of-00003.bin:  99%|█████████▊| 9.80G/9.95G [00:10<00:00, 1.68GB/s]
pytorch_model-00001-of-00003.bin: 100%|█████████▉| 9.95G/9.95G [00:12<00:00, 816MB/s] 
chaiml-phase2-winner-13b2-v272-mkmlizer: 
pytorch_model-00002-of-00003.bin:   0%|          | 0.00/9.90G [00:00<?, ?B/s]
pytorch_model-00002-of-00003.bin:   0%|          | 10.5M/9.90G [00:00<02:47, 59.2MB/s]
pytorch_model-00002-of-00003.bin:   1%|          | 105M/9.90G [00:00<00:22, 444MB/s]  
pytorch_model-00002-of-00003.bin:   2%|▏         | 168M/9.90G [00:00<00:27, 358MB/s]
pytorch_model-00002-of-00003.bin:   2%|▏         | 241M/9.90G [00:00<00:23, 417MB/s]
pytorch_model-00002-of-00003.bin:   4%|▍         | 440M/9.90G [00:00<00:11, 828MB/s]
pytorch_model-00002-of-00003.bin:   6%|▌         | 556M/9.90G [00:00<00:10, 892MB/s]
pytorch_model-00002-of-00003.bin:   7%|▋         | 724M/9.90G [00:00<00:08, 1.10GB/s]
pytorch_model-00002-of-00003.bin:   9%|▊         | 849M/9.90G [00:01<00:08, 1.08GB/s]
pytorch_model-00002-of-00003.bin:  10%|▉         | 975M/9.90G [00:01<00:08, 1.11GB/s]
pytorch_model-00002-of-00003.bin:  12%|█▏        | 1.15G/9.90G [00:01<00:06, 1.27GB/s]
pytorch_model-00002-of-00003.bin:  13%|█▎        | 1.29G/9.90G [00:01<00:06, 1.27GB/s]
pytorch_model-00002-of-00003.bin:  14%|█▍        | 1.43G/9.90G [00:01<00:06, 1.23GB/s]
pytorch_model-00002-of-00003.bin:  16%|█▌        | 1.58G/9.90G [00:01<00:06, 1.33GB/s]
pytorch_model-00002-of-00003.bin:  17%|█▋        | 1.72G/9.90G [00:01<00:06, 1.28GB/s]
pytorch_model-00002-of-00003.bin:  19%|█▊        | 1.86G/9.90G [00:01<00:06, 1.16GB/s]
pytorch_model-00002-of-00003.bin:  21%|██▏       | 2.12G/9.90G [00:01<00:05, 1.54GB/s]
pytorch_model-00002-of-00003.bin:  23%|██▎       | 2.29G/9.90G [00:02<00:05, 1.44GB/s]
pytorch_model-00002-of-00003.bin:  25%|██▍       | 2.44G/9.90G [00:02<00:05, 1.28GB/s]
pytorch_model-00002-of-00003.bin:  26%|██▌       | 2.58G/9.90G [00:02<00:05, 1.26GB/s]
pytorch_model-00002-of-00003.bin:  27%|██▋       | 2.72G/9.90G [00:02<00:06, 1.10GB/s]
pytorch_model-00002-of-00003.bin:  30%|██▉       | 2.96G/9.90G [00:02<00:04, 1.39GB/s]
pytorch_model-00002-of-00003.bin:  32%|███▏      | 3.14G/9.90G [00:02<00:04, 1.47GB/s]
pytorch_model-00002-of-00003.bin:  33%|███▎      | 3.29G/9.90G [00:02<00:04, 1.48GB/s]
pytorch_model-00002-of-00003.bin:  35%|███▍      | 3.45G/9.90G [00:02<00:04, 1.38GB/s]
pytorch_model-00002-of-00003.bin:  37%|███▋      | 3.71G/9.90G [00:03<00:03, 1.66GB/s]
pytorch_model-00002-of-00003.bin:  40%|████      | 3.96G/9.90G [00:03<00:03, 1.86GB/s]
pytorch_model-00002-of-00003.bin:  43%|████▎     | 4.24G/9.90G [00:03<00:02, 2.06GB/s]
pytorch_model-00002-of-00003.bin:  45%|████▍     | 4.46G/9.90G [00:03<00:02, 2.00GB/s]
pytorch_model-00002-of-00003.bin:  47%|████▋     | 4.67G/9.90G [00:03<00:02, 1.79GB/s]
pytorch_model-00002-of-00003.bin:  50%|████▉     | 4.92G/9.90G [00:03<00:02, 1.95GB/s]
pytorch_model-00002-of-00003.bin:  52%|█████▏    | 5.13G/9.90G [00:03<00:02, 1.73GB/s]
pytorch_model-00002-of-00003.bin:  54%|█████▍    | 5.33G/9.90G [00:03<00:02, 1.73GB/s]
pytorch_model-00002-of-00003.bin:  56%|█████▌    | 5.52G/9.90G [00:04<00:02, 1.62GB/s]
pytorch_model-00002-of-00003.bin:  57%|█████▋    | 5.68G/9.90G [00:04<00:02, 1.59GB/s]
pytorch_model-00002-of-00003.bin:  59%|█████▉    | 5.85G/9.90G [00:04<00:02, 1.48GB/s]
pytorch_model-00002-of-00003.bin:  61%|██████    | 6.01G/9.90G [00:04<00:02, 1.46GB/s]
pytorch_model-00002-of-00003.bin:  62%|██████▏   | 6.17G/9.90G [00:04<00:03, 1.25GB/s]
pytorch_model-00002-of-00003.bin:  64%|██████▎   | 6.31G/9.90G [00:04<00:03, 1.20GB/s]
pytorch_model-00002-of-00003.bin:  65%|██████▌   | 6.48G/9.90G [00:04<00:02, 1.22GB/s]
pytorch_model-00002-of-00003.bin:  67%|██████▋   | 6.61G/9.90G [00:05<00:02, 1.20GB/s]
pytorch_model-00002-of-00003.bin:  69%|██████▉   | 6.82G/9.90G [00:05<00:02, 1.42GB/s]
pytorch_model-00002-of-00003.bin:  71%|███████▏  | 7.06G/9.90G [00:05<00:01, 1.67GB/s]
pytorch_model-00002-of-00003.bin:  73%|███████▎  | 7.26G/9.90G [00:05<00:01, 1.73GB/s]
pytorch_model-00002-of-00003.bin:  75%|███████▌  | 7.44G/9.90G [00:05<00:01, 1.65GB/s]
pytorch_model-00002-of-00003.bin:  78%|███████▊  | 7.70G/9.90G [00:05<00:01, 1.87GB/s]
pytorch_model-00002-of-00003.bin:  80%|███████▉  | 7.90G/9.90G [00:05<00:01, 1.82GB/s]
pytorch_model-00002-of-00003.bin:  82%|████████▏ | 8.08G/9.90G [00:05<00:01, 1.76GB/s]
pytorch_model-00002-of-00003.bin:  84%|████████▎ | 8.27G/9.90G [00:05<00:00, 1.75GB/s]
pytorch_model-00002-of-00003.bin:  85%|████████▌ | 8.45G/9.90G [00:05<00:00, 1.76GB/s]
pytorch_model-00002-of-00003.bin:  87%|████████▋ | 8.63G/9.90G [00:06<00:00, 1.74GB/s]
pytorch_model-00002-of-00003.bin:  90%|████████▉ | 8.90G/9.90G [00:06<00:00, 1.99GB/s]
pytorch_model-00002-of-00003.bin:  92%|█████████▏| 9.11G/9.90G [00:06<00:00, 1.99GB/s]
pytorch_model-00002-of-00003.bin:  94%|█████████▍| 9.32G/9.90G [00:06<00:00, 1.68GB/s]
pytorch_model-00002-of-00003.bin:  96%|█████████▌| 9.51G/9.90G [00:06<00:00, 1.62GB/s]
pytorch_model-00002-of-00003.bin:  98%|█████████▊| 9.68G/9.90G [00:06<00:00, 1.10GB/s]
pytorch_model-00002-of-00003.bin:  99%|█████████▉| 9.84G/9.90G [00:07<00:00, 1.17GB/s]
pytorch_model-00002-of-00003.bin: 100%|█████████▉| 9.90G/9.90G [00:07<00:00, 1.40GB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
pytorch_model-00003-of-00003.bin:   0%|          | 0.00/6.18G [00:00<?, ?B/s]
pytorch_model-00003-of-00003.bin:   0%|          | 10.5M/6.18G [00:00<01:35, 64.4MB/s]
pytorch_model-00003-of-00003.bin:   1%|          | 31.5M/6.18G [00:00<01:07, 91.6MB/s]
pytorch_model-00003-of-00003.bin:   1%|          | 52.4M/6.18G [00:00<00:52, 117MB/s] 
pytorch_model-00003-of-00003.bin:   2%|▏         | 126M/6.18G [00:00<00:20, 296MB/s] 
pytorch_model-00003-of-00003.bin:   3%|▎         | 210M/6.18G [00:00<00:13, 446MB/s]
pytorch_model-00003-of-00003.bin:   5%|▌         | 315M/6.18G [00:00<00:09, 617MB/s]
pytorch_model-00003-of-00003.bin:   8%|▊         | 472M/6.18G [00:00<00:06, 871MB/s]
pytorch_model-00003-of-00003.bin:   9%|▉         | 566M/6.18G [00:01<00:07, 771MB/s]
pytorch_model-00003-of-00003.bin:  11%|█         | 682M/6.18G [00:01<00:06, 853MB/s]
pytorch_model-00003-of-00003.bin:  13%|█▎        | 776M/6.18G [00:01<00:06, 853MB/s]
pytorch_model-00003-of-00003.bin:  14%|█▍        | 891M/6.18G [00:01<00:05, 908MB/s]
pytorch_model-00003-of-00003.bin:  16%|█▋        | 1.01G/6.18G [00:01<00:06, 835MB/s]
pytorch_model-00003-of-00003.bin:  18%|█▊        | 1.10G/6.18G [00:01<00:06, 810MB/s]
pytorch_model-00003-of-00003.bin:  19%|█▉        | 1.18G/6.18G [00:01<00:06, 797MB/s]
pytorch_model-00003-of-00003.bin:  22%|██▏       | 1.38G/6.18G [00:01<00:04, 1.10GB/s]
pytorch_model-00003-of-00003.bin:  26%|██▋       | 1.63G/6.18G [00:01<00:03, 1.45GB/s]
pytorch_model-00003-of-00003.bin:  29%|██▉       | 1.78G/6.18G [00:02<00:03, 1.13GB/s]
pytorch_model-00003-of-00003.bin:  31%|███       | 1.92G/6.18G [00:02<00:04, 972MB/s] 
pytorch_model-00003-of-00003.bin:  33%|███▎      | 2.03G/6.18G [00:02<00:04, 880MB/s]
pytorch_model-00003-of-00003.bin:  35%|███▍      | 2.14G/6.18G [00:02<00:05, 713MB/s]
pytorch_model-00003-of-00003.bin:  36%|███▌      | 2.22G/6.18G [00:02<00:05, 727MB/s]
pytorch_model-00003-of-00003.bin:  38%|███▊      | 2.36G/6.18G [00:03<00:04, 823MB/s]
pytorch_model-00003-of-00003.bin:  40%|███▉      | 2.45G/6.18G [00:03<00:04, 804MB/s]
pytorch_model-00003-of-00003.bin:  41%|████      | 2.55G/6.18G [00:03<00:04, 771MB/s]
pytorch_model-00003-of-00003.bin:  44%|████▍     | 2.73G/6.18G [00:03<00:03, 986MB/s]
pytorch_model-00003-of-00003.bin:  48%|████▊     | 2.95G/6.18G [00:03<00:02, 1.25GB/s]
pytorch_model-00003-of-00003.bin:  51%|█████     | 3.17G/6.18G [00:03<00:02, 1.48GB/s]
pytorch_model-00003-of-00003.bin:  55%|█████▌    | 3.43G/6.18G [00:03<00:01, 1.74GB/s]
pytorch_model-00003-of-00003.bin:  59%|█████▉    | 3.66G/6.18G [00:03<00:01, 1.86GB/s]
pytorch_model-00003-of-00003.bin:  62%|██████▏   | 3.86G/6.18G [00:03<00:01, 1.77GB/s]
pytorch_model-00003-of-00003.bin:  66%|██████▌   | 4.05G/6.18G [00:04<00:01, 1.64GB/s]
pytorch_model-00003-of-00003.bin:  68%|██████▊   | 4.23G/6.18G [00:04<00:01, 1.64GB/s]
pytorch_model-00003-of-00003.bin:  71%|███████▏  | 4.41G/6.18G [00:04<00:01, 1.68GB/s]
pytorch_model-00003-of-00003.bin:  74%|███████▍  | 4.59G/6.18G [00:04<00:00, 1.66GB/s]
pytorch_model-00003-of-00003.bin:  77%|███████▋  | 4.76G/6.18G [00:04<00:00, 1.60GB/s]
pytorch_model-00003-of-00003.bin:  80%|███████▉  | 4.93G/6.18G [00:04<00:00, 1.54GB/s]
pytorch_model-00003-of-00003.bin:  83%|████████▎ | 5.11G/6.18G [00:04<00:00, 1.59GB/s]
pytorch_model-00003-of-00003.bin:  85%|████████▌ | 5.27G/6.18G [00:04<00:00, 1.60GB/s]
pytorch_model-00003-of-00003.bin:  88%|████████▊ | 5.44G/6.18G [00:05<00:00, 1.37GB/s]
pytorch_model-00003-of-00003.bin:  90%|█████████ | 5.59G/6.18G [00:05<00:00, 1.39GB/s]
pytorch_model-00003-of-00003.bin:  93%|█████████▎| 5.77G/6.18G [00:05<00:00, 1.48GB/s]
pytorch_model-00003-of-00003.bin:  96%|█████████▋| 5.95G/6.18G [00:05<00:00, 1.56GB/s]
pytorch_model-00003-of-00003.bin:  99%|█████████▉| 6.12G/6.18G [00:05<00:00, 1.49GB/s]
pytorch_model-00003-of-00003.bin: 100%|█████████▉| 6.18G/6.18G [00:05<00:00, 1.08GB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
pytorch_model.bin.index.json:   0%|          | 0.00/33.4k [00:00<?, ?B/s]
pytorch_model.bin.index.json: 100%|██████████| 33.4k/33.4k [00:00<00:00, 24.6MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
special_tokens_map.json:   0%|          | 0.00/414 [00:00<?, ?B/s]
special_tokens_map.json: 100%|██████████| 414/414 [00:00<00:00, 4.76MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
tokenizer.json:   0%|          | 0.00/1.84M [00:00<?, ?B/s]
tokenizer.json: 100%|██████████| 1.84M/1.84M [00:00<00:00, 28.9MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
tokenizer.model:   0%|          | 0.00/500k [00:00<?, ?B/s]
tokenizer.model: 100%|██████████| 500k/500k [00:00<00:00, 14.5MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
tokenizer_config.json:   0%|          | 0.00/725 [00:00<?, ?B/s]
tokenizer_config.json: 100%|██████████| 725/725 [00:00<00:00, 9.87MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: Downloaded to shared memory in 26.886s
chaiml-phase2-winner-13b2-v272-mkmlizer: quantizing model to /dev/shm/model_cache
chaiml-phase2-winner-13b2-v272-mkmlizer: Saving mkml model at /dev/shm/model_cache
chaiml-phase2-winner-13b2-v272-mkmlizer: Reading /tmp/tmp3zy711hz/pytorch_model.bin.index.json
chaiml-phase2-winner-13b2-v272-mkmlizer: 
Profiling:   0%|          | 0/363 [00:00<?, ?it/s]
Profiling:   0%|          | 1/363 [00:03<20:45,  3.44s/it]
Profiling:  38%|███▊      | 139/363 [00:05<00:07, 32.00it/s]
Profiling:  77%|███████▋  | 278/363 [00:06<00:01, 55.65it/s]
Profiling: 100%|██████████| 363/363 [00:08<00:00, 54.97it/s]
Profiling: 100%|██████████| 363/363 [00:08<00:00, 44.49it/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: quantized model in 26.907s
chaiml-phase2-winner-13b2-v272-mkmlizer: Processed model ChaiML/phase2_winner_13b2 in 55.593s
chaiml-phase2-winner-13b2-v272-mkmlizer: creating bucket guanaco-mkml-models
chaiml-phase2-winner-13b2-v272-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-phase2-winner-13b2-v272-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-phase2-winner-13b2-v272
chaiml-phase2-winner-13b2-v272-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-phase2-winner-13b2-v272/tokenizer_config.json
chaiml-phase2-winner-13b2-v272-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-phase2-winner-13b2-v272/config.json
chaiml-phase2-winner-13b2-v272-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/chaiml-phase2-winner-13b2-v272/tokenizer.model
chaiml-phase2-winner-13b2-v272-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-phase2-winner-13b2-v272/special_tokens_map.json
chaiml-phase2-winner-13b2-v272-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-phase2-winner-13b2-v272/tokenizer.json
chaiml-phase2-winner-13b2-v272-mkmlizer: cp /dev/shm/model_cache/mkml_model.tensors s3://guanaco-mkml-models/chaiml-phase2-winner-13b2-v272/mkml_model.tensors
chaiml-phase2-winner-13b2-v272-mkmlizer: loading reward model from rirv938/gpt2_ties_merge_preference_plus_classic_e2_density_99
chaiml-phase2-winner-13b2-v272-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.
chaiml-phase2-winner-13b2-v272-mkmlizer:   warnings.warn(
chaiml-phase2-winner-13b2-v272-mkmlizer: 
config.json:   0%|          | 0.00/983 [00:00<?, ?B/s]
config.json: 100%|██████████| 983/983 [00:00<00:00, 11.2MB/s]
chaiml-phase2-winner-13b2-v272-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.
chaiml-phase2-winner-13b2-v272-mkmlizer:   warnings.warn(
chaiml-phase2-winner-13b2-v272-mkmlizer: 
tokenizer_config.json:   0%|          | 0.00/445 [00:00<?, ?B/s]
tokenizer_config.json: 100%|██████████| 445/445 [00:00<00:00, 5.93MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
vocab.json:   0%|          | 0.00/798k [00:00<?, ?B/s]
vocab.json: 100%|██████████| 798k/798k [00:00<00:00, 36.4MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
merges.txt:   0%|          | 0.00/456k [00:00<?, ?B/s]
merges.txt: 100%|██████████| 456k/456k [00:00<00:00, 6.67MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
tokenizer.json:   0%|          | 0.00/2.11M [00:00<?, ?B/s]
tokenizer.json: 100%|██████████| 2.11M/2.11M [00:00<00:00, 26.3MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
special_tokens_map.json:   0%|          | 0.00/441 [00:00<?, ?B/s]
special_tokens_map.json: 100%|██████████| 441/441 [00:00<00:00, 3.27MB/s]
chaiml-phase2-winner-13b2-v272-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.
chaiml-phase2-winner-13b2-v272-mkmlizer:   warnings.warn(
chaiml-phase2-winner-13b2-v272-mkmlizer: 
model.safetensors.index.json:   0%|          | 0.00/10.5k [00:00<?, ?B/s]
model.safetensors.index.json: 100%|██████████| 10.5k/10.5k [00:00<00:00, 96.0MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
Downloading shards:   0%|          | 0/1 [00:00<?, ?it/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
model-00001-of-00001.safetensors:   0%|          | 0.00/249M [00:00<?, ?B/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
model-00001-of-00001.safetensors:   4%|▍         | 10.5M/249M [00:00<00:02, 87.1MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
model-00001-of-00001.safetensors:  58%|█████▊    | 144M/249M [00:00<00:00, 761MB/s]  
chaiml-phase2-winner-13b2-v272-mkmlizer: 
model-00001-of-00001.safetensors:  96%|█████████▌| 238M/249M [00:00<00:00, 820MB/s]
model-00001-of-00001.safetensors: 100%|█████████▉| 249M/249M [00:05<00:00, 49.0MB/s]
chaiml-phase2-winner-13b2-v272-mkmlizer: 
Downloading shards: 100%|██████████| 1/1 [00:05<00:00,  5.36s/it]
Downloading shards: 100%|██████████| 1/1 [00:05<00:00,  5.36s/it]
chaiml-phase2-winner-13b2-v272-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
chaiml-phase2-winner-13b2-v272-mkmlizer: Saving duration: 0.095s
chaiml-phase2-winner-13b2-v272-mkmlizer: Processed model rirv938/gpt2_ties_merge_preference_plus_classic_e2_density_99 in 7.198s
chaiml-phase2-winner-13b2-v272-mkmlizer: creating bucket guanaco-reward-models
chaiml-phase2-winner-13b2-v272-mkmlizer: Bucket 's3://guanaco-reward-models/' created
chaiml-phase2-winner-13b2-v272-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/chaiml-phase2-winner-13b2-v272_reward
chaiml-phase2-winner-13b2-v272-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/chaiml-phase2-winner-13b2-v272_reward/config.json
chaiml-phase2-winner-13b2-v272-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/chaiml-phase2-winner-13b2-v272_reward/tokenizer_config.json
Job chaiml-phase2-winner-13b2-v272-mkmlizer completed after 85.13s with status: succeeded
Stopping job with name chaiml-phase2-winner-13b2-v272-mkmlizer
Pipeline stage MKMLizer completed in 89.85s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.14s
Running pipeline stage ISVCDeployer
Creating inference service chaiml-phase2-winner-13b2-v272
Waiting for inference service chaiml-phase2-winner-13b2-v272 to be ready
Inference service chaiml-phase2-winner-13b2-v272 ready after 40.29353356361389s
Pipeline stage ISVCDeployer completed in 49.19s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.5845861434936523s
Received healthy response to inference request in 2.0698764324188232s
Received healthy response to inference request in 2.0561838150024414s
Received healthy response to inference request in 1.8198425769805908s
Received healthy response to inference request in 2.197105646133423s
5 requests
0 failed requests
5th percentile: 1.867110824584961
10th percentile: 1.914379072189331
20th percentile: 2.008915567398071
30th percentile: 2.0589223384857176
40th percentile: 2.0643993854522704
50th percentile: 2.0698764324188232
60th percentile: 2.120768117904663
70th percentile: 2.171659803390503
80th percentile: 2.274601745605469
90th percentile: 2.4295939445495605
95th percentile: 2.507090044021606
99th percentile: 2.5690869235992433
mean time: 2.145518922805786
Pipeline stage StressChecker completed in 11.54s
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
chaiml-phase2-winner-13b2_v272 status is now deployed due to DeploymentManager action
chaiml-phase2-winner-13b2_v272 status is now inactive due to admin request
admin requested tearing down of chaiml-phase2-winner-13b2_v272
Running pipeline stage ISVCDeleter
Checking if service chaiml-phase2-winner-13b2-v272 is running
Tearing down inference service chaiml-phase2-winner-13b2-v272
Toredown service chaiml-phase2-winner-13b2-v272
Pipeline stage ISVCDeleter completed in 7.50s
Running pipeline stage MKMLModelDeleter
Cleaning model data from S3
Cleaning model data from model cache
Deleting key chaiml-phase2-winner-13b2-v272/config.json from bucket guanaco-mkml-models
Deleting key chaiml-phase2-winner-13b2-v272/mkml_model.tensors from bucket guanaco-mkml-models
Deleting key chaiml-phase2-winner-13b2-v272/special_tokens_map.json from bucket guanaco-mkml-models
Deleting key chaiml-phase2-winner-13b2-v272/tokenizer.json from bucket guanaco-mkml-models
Deleting key chaiml-phase2-winner-13b2-v272/tokenizer.model from bucket guanaco-mkml-models
Deleting key chaiml-phase2-winner-13b2-v272/tokenizer_config.json from bucket guanaco-mkml-models
Cleaning model data from model cache
Deleting key chaiml-phase2-winner-13b2-v272_reward/config.json from bucket guanaco-reward-models
Deleting key chaiml-phase2-winner-13b2-v272_reward/merges.txt from bucket guanaco-reward-models
Deleting key chaiml-phase2-winner-13b2-v272_reward/reward.tensors from bucket guanaco-reward-models
Deleting key chaiml-phase2-winner-13b2-v272_reward/special_tokens_map.json from bucket guanaco-reward-models
Deleting key chaiml-phase2-winner-13b2-v272_reward/tokenizer.json from bucket guanaco-reward-models
Deleting key chaiml-phase2-winner-13b2-v272_reward/tokenizer_config.json from bucket guanaco-reward-models
Deleting key chaiml-phase2-winner-13b2-v272_reward/vocab.json from bucket guanaco-reward-models
Pipeline stage MKMLModelDeleter completed in 3.85s
chaiml-phase2-winner-13b2_v272 status is now torndown due to DeploymentManager action

Usage Metrics

Latency Metrics