submission_id: chaiml-phase2-winner-13b2_v280
developer_uid: chai_backend_admin
status: inactive
model_repo: ChaiML/phase2_winner_13b2
reward_repo: rirv938/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 1.0733671330918084, 'top_p': 0.6971846333941389, 'top_k': 50, 'presence_penalty': 0.0, 'frequency_penalty': 0.312882778758545, 'stopping_words': ['\n'], 'max_input_tokens': 512, 'best_of': 8, 'max_output_tokens': 156}
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}:'}
reward_formatter: {'memory_template': 'Memory: {memory}\n', 'prompt_template': '{prompt}\n', 'bot_template': 'Bot: {message}\n', 'user_template': 'User: {message}\n', 'response_template': 'Bot:'}
timestamp: 2024-03-31T02:00:18+00:00
model_name: chaiml-phase2-winner-13b2_v280
model_eval_status: success
safety_score: None
entertaining: 7.04
stay_in_character: 8.65
user_preference: 7.34
double_thumbs_up: 3384
thumbs_up: 4670
thumbs_down: 2037
num_battles: 314974
num_wins: 164614
win_ratio: 0.5226272644726231
celo_rating: 1172.74
Resubmit model
Running pipeline stage MKMLizer
Starting job with name chaiml-phase2-winner-13b2-v280-mkmlizer
Waiting for job on chaiml-phase2-winner-13b2-v280-mkmlizer to finish
chaiml-phase2-winner-13b2-v280-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ _____ __ __ ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ /___/ ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ Version: 0.6.11 ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ The license key for the current software has been verified as ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ belonging to: ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ Chai Research Corp. ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ║ ║
chaiml-phase2-winner-13b2-v280-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-phase2-winner-13b2-v280-mkmlizer: .gitattributes: 0%| | 0.00/1.52k [00:00<?, ?B/s] .gitattributes: 100%|██████████| 1.52k/1.52k [00:00<00:00, 11.7MB/s]
chaiml-phase2-winner-13b2-v280-mkmlizer: README.md: 0%| | 0.00/1.53k [00:00<?, ?B/s] README.md: 100%|██████████| 1.53k/1.53k [00:00<00:00, 13.8MB/s]
chaiml-phase2-winner-13b2-v280-mkmlizer: config.json: 0%| | 0.00/651 [00:00<?, ?B/s] config.json: 100%|██████████| 651/651 [00:00<00:00, 8.40MB/s]
chaiml-phase2-winner-13b2-v280-mkmlizer: generation_config.json: 0%| | 0.00/170 [00:00<?, ?B/s] generation_config.json: 100%|██████████| 170/170 [00:00<00:00, 1.81MB/s]
chaiml-phase2-winner-13b2-v280-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<06:19, 26.2MB/s] pytorch_model-00001-of-00003.bin: 0%| | 21.0M/9.95G [00:00<04:15, 38.8MB/s] pytorch_model-00001-of-00003.bin: 1%| | 62.9M/9.95G [00:00<01:19, 124MB/s] pytorch_model-00001-of-00003.bin: 2%|▏ | 157M/9.95G [00:00<00:30, 319MB/s] pytorch_model-00001-of-00003.bin: 2%|▏ | 210M/9.95G [00:01<00:33, 294MB/s] pytorch_model-00001-of-00003.bin: 3%|▎ | 252M/9.95G [00:01<00:33, 291MB/s] pytorch_model-00001-of-00003.bin: 3%|▎ | 315M/9.95G [00:01<00:27, 354MB/s] pytorch_model-00001-of-00003.bin: 4%|▍ | 409M/9.95G [00:01<00:19, 487MB/s] pytorch_model-00001-of-00003.bin: 5%|▌ | 524M/9.95G [00:01<00:14, 653MB/s] pytorch_model-00001-of-00003.bin: 7%|▋ | 682M/9.95G [00:01<00:10, 892MB/s] pytorch_model-00001-of-00003.bin: 8%|▊ | 807M/9.95G [00:01<00:09, 977MB/s] pytorch_model-00001-of-00003.bin: 9%|▉ | 923M/9.95G [00:01<00:11, 788MB/s] pytorch_model-00001-of-00003.bin: 10%|█ | 1.02G/9.95G [00:02<00:11, 775MB/s] pytorch_model-00001-of-00003.bin: 12%|█▏ | 1.15G/9.95G [00:02<00:09, 891MB/s] pytorch_model-00001-of-00003.bin: 13%|█▎ | 1.28G/9.95G [00:02<00:09, 963MB/s] pytorch_model-00001-of-00003.bin: 14%|█▍ | 1.38G/9.95G [00:02<00:11, 776MB/s] pytorch_model-00001-of-00003.bin: 15%|█▌ | 1.53G/9.95G [00:02<00:09, 899MB/s] pytorch_model-00001-of-00003.bin: 16%|█▋ | 1.64G/9.95G [00:02<00:10, 791MB/s] pytorch_model-00001-of-00003.bin: 17%|█▋ | 1.73G/9.95G [00:02<00:11, 743MB/s] pytorch_model-00001-of-00003.bin: 18%|█▊ | 1.81G/9.95G [00:03<00:11, 715MB/s] pytorch_model-00001-of-00003.bin: 19%|█▉ | 1.90G/9.95G [00:03<00:11, 674MB/s] pytorch_model-00001-of-00003.bin: 20%|█▉ | 1.97G/9.95G [00:03<00:12, 660MB/s] pytorch_model-00001-of-00003.bin: 21%|██ | 2.07G/9.95G [00:03<00:11, 700MB/s] pytorch_model-00001-of-00003.bin: 22%|██▏ | 2.14G/9.95G [00:03<00:11, 701MB/s] pytorch_model-00001-of-00003.bin: 23%|██▎ | 2.29G/9.95G [00:03<00:08, 885MB/s] pytorch_model-00001-of-00003.bin: 24%|██▍ | 2.39G/9.95G [00:03<00:08, 898MB/s] pytorch_model-00001-of-00003.bin: 25%|██▍ | 2.49G/9.95G [00:03<00:08, 863MB/s] pytorch_model-00001-of-00003.bin: 26%|██▌ | 2.59G/9.95G [00:03<00:08, 842MB/s] pytorch_model-00001-of-00003.bin: 27%|██▋ | 2.69G/9.95G [00:04<00:08, 894MB/s] pytorch_model-00001-of-00003.bin: 28%|██▊ | 2.82G/9.95G [00:04<00:07, 937MB/s] pytorch_model-00001-of-00003.bin: 30%|██▉ | 2.96G/9.95G [00:04<00:06, 1.04GB/s] pytorch_model-00001-of-00003.bin: 31%|███ | 3.07G/9.95G [00:04<00:06, 1.04GB/s] pytorch_model-00001-of-00003.bin: 32%|███▏ | 3.19G/9.95G [00:04<00:06, 1.02GB/s] pytorch_model-00001-of-00003.bin: 33%|███▎ | 3.29G/9.95G [00:04<00:06, 1.00GB/s] pytorch_model-00001-of-00003.bin: 34%|███▍ | 3.43G/9.95G [00:04<00:05, 1.10GB/s] pytorch_model-00001-of-00003.bin: 36%|███▌ | 3.55G/9.95G [00:04<00:06, 934MB/s] pytorch_model-00001-of-00003.bin: 38%|███▊ | 3.74G/9.95G [00:05<00:05, 1.16GB/s] pytorch_model-00001-of-00003.bin: 39%|███▉ | 3.87G/9.95G [00:05<00:05, 1.18GB/s] pytorch_model-00001-of-00003.bin: 40%|████ | 4.00G/9.95G [00:05<00:05, 1.18GB/s] pytorch_model-00001-of-00003.bin: 41%|████▏ | 4.12G/9.95G [00:05<00:05, 1.12GB/s] pytorch_model-00001-of-00003.bin: 43%|████▎ | 4.25G/9.95G [00:05<00:05, 1.08GB/s] pytorch_model-00001-of-00003.bin: 44%|████▍ | 4.39G/9.95G [00:05<00:04, 1.18GB/s] pytorch_model-00001-of-00003.bin: 47%|████▋ | 4.63G/9.95G [00:05<00:03, 1.45GB/s] pytorch_model-00001-of-00003.bin: 48%|████▊ | 4.78G/9.95G [00:05<00:05, 1.01GB/s] pytorch_model-00001-of-00003.bin: 49%|████▉ | 4.91G/9.95G [00:06<00:04, 1.02GB/s] pytorch_model-00001-of-00003.bin: 50%|█████ | 5.02G/9.95G [00:06<00:05, 916MB/s] pytorch_model-00001-of-00003.bin: 52%|█████▏ | 5.15G/9.95G [00:06<00:04, 975MB/s] pytorch_model-00001-of-00003.bin: 53%|█████▎ | 5.26G/9.95G [00:06<00:06, 741MB/s] pytorch_model-00001-of-00003.bin: 54%|█████▍ | 5.36G/9.95G [00:06<00:06, 734MB/s] pytorch_model-00001-of-00003.bin: 55%|█████▍ | 5.44G/9.95G [00:06<00:06, 739MB/s] pytorch_model-00001-of-00003.bin: 56%|█████▌ | 5.54G/9.95G [00:06<00:05, 784MB/s] pytorch_model-00001-of-00003.bin: 57%|█████▋ | 5.63G/9.95G [00:07<00:06, 685MB/s] pytorch_model-00001-of-00003.bin: 57%|█████▋ | 5.71G/9.95G [00:07<00:06, 652MB/s] pytorch_model-00001-of-00003.bin: 58%|█████▊ | 5.80G/9.95G [00:07<00:05, 692MB/s] pytorch_model-00001-of-00003.bin: 59%|█████▉ | 5.88G/9.95G [00:07<00:07, 562MB/s] pytorch_model-00001-of-00003.bin: 60%|██████ | 6.01G/9.95G [00:07<00:05, 700MB/s] pytorch_model-00001-of-00003.bin: 62%|██████▏ | 6.14G/9.95G [00:07<00:04, 824MB/s] pytorch_model-00001-of-00003.bin: 63%|██████▎ | 6.24G/9.95G [00:07<00:04, 804MB/s] pytorch_model-00001-of-00003.bin: 64%|██████▎ | 6.33G/9.95G [00:08<00:04, 741MB/s] pytorch_model-00001-of-00003.bin: 65%|██████▍ | 6.43G/9.95G [00:08<00:04, 762MB/s] pytorch_model-00001-of-00003.bin: 65%|██████▌ | 6.51G/9.95G [00:08<00:04, 770MB/s] pytorch_model-00001-of-00003.bin: 66%|██████▋ | 6.60G/9.95G [00:08<00:04, 762MB/s] pytorch_model-00001-of-00003.bin: 67%|██████▋ | 6.69G/9.95G [00:08<00:04, 806MB/s] pytorch_model-00001-of-00003.bin: 68%|██████▊ | 6.81G/9.95G [00:08<00:03, 880MB/s] pytorch_model-00001-of-00003.bin: 69%|██████▉ | 6.90G/9.95G [00:08<00:03, 821MB/s] pytorch_model-00001-of-00003.bin: 70%|███████ | 6.98G/9.95G [00:08<00:03, 787MB/s] pytorch_model-00001-of-00003.bin: 71%|███████▏ | 7.10G/9.95G [00:09<00:03, 853MB/s] pytorch_model-00001-of-00003.bin: 72%|███████▏ | 7.20G/9.95G [00:09<00:03, 903MB/s] pytorch_model-00001-of-00003.bin: 73%|███████▎ | 7.30G/9.95G [00:09<00:03, 795MB/s] pytorch_model-00001-of-00003.bin: 75%|███████▍ | 7.43G/9.95G [00:09<00:02, 923MB/s] pytorch_model-00001-of-00003.bin: 76%|███████▌ | 7.54G/9.95G [00:09<00:02, 949MB/s] pytorch_model-00001-of-00003.bin: 77%|███████▋ | 7.64G/9.95G [00:09<00:02, 873MB/s] pytorch_model-00001-of-00003.bin: 78%|███████▊ | 7.77G/9.95G [00:09<00:02, 899MB/s] pytorch_model-00001-of-00003.bin: 80%|███████▉ | 7.93G/9.95G [00:09<00:01, 1.07GB/s] pytorch_model-00001-of-00003.bin: 81%|████████ | 8.04G/9.95G [00:09<00:01, 1.04GB/s] pytorch_model-00001-of-00003.bin: 82%|████████▏ | 8.16G/9.95G [00:10<00:02, 883MB/s] pytorch_model-00001-of-00003.bin: 83%|████████▎ | 8.27G/9.95G [00:10<00:01, 939MB/s] pytorch_model-00001-of-00003.bin: 84%|████████▍ | 8.38G/9.95G [00:10<00:01, 875MB/s] pytorch_model-00001-of-00003.bin: 86%|████████▌ | 8.54G/9.95G [00:10<00:01, 982MB/s] pytorch_model-00001-of-00003.bin: 87%|████████▋ | 8.64G/9.95G [00:10<00:01, 892MB/s] pytorch_model-00001-of-00003.bin: 89%|████████▊ | 8.83G/9.95G [00:10<00:01, 1.11GB/s] pytorch_model-00001-of-00003.bin: 90%|█████████ | 8.95G/9.95G [00:10<00:00, 1.11GB/s] pytorch_model-00001-of-00003.bin: 91%|█████████▏| 9.08G/9.95G [00:11<00:00, 1.12GB/s] pytorch_model-00001-of-00003.bin: 92%|█████████▏| 9.20G/9.95G [00:11<00:00, 913MB/s] pytorch_model-00001-of-00003.bin: 93%|█████████▎| 9.30G/9.95G [00:11<00:01, 552MB/s] pytorch_model-00001-of-00003.bin: 94%|█████████▍| 9.38G/9.95G [00:11<00:01, 487MB/s] pytorch_model-00001-of-00003.bin: 95%|█████████▌| 9.46G/9.95G [00:11<00:00, 511MB/s] pytorch_model-00001-of-00003.bin: 97%|█████████▋| 9.60G/9.95G [00:12<00:00, 663MB/s] pytorch_model-00001-of-00003.bin: 97%|█████████▋| 9.69G/9.95G [00:12<00:00, 691MB/s] pytorch_model-00001-of-00003.bin: 98%|█████████▊| 9.77G/9.95G [00:12<00:00, 681MB/s] pytorch_model-00001-of-00003.bin: 99%|█████████▉| 9.85G/9.95G [00:12<00:00, 482MB/s] pytorch_model-00001-of-00003.bin: 100%|█████████▉| 9.92G/9.95G [00:12<00:00, 486MB/s] pytorch_model-00001-of-00003.bin: 100%|█████████▉| 9.95G/9.95G [00:12<00:00, 768MB/s]
chaiml-phase2-winner-13b2-v280-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<03:57, 41.6MB/s] pytorch_model-00002-of-00003.bin: 0%| | 41.9M/9.90G [00:00<01:42, 96.2MB/s] pytorch_model-00002-of-00003.bin: 2%|▏ | 168M/9.90G [00:00<00:24, 397MB/s] pytorch_model-00002-of-00003.bin: 2%|▏ | 241M/9.90G [00:00<00:20, 471MB/s] pytorch_model-00002-of-00003.bin: 3%|▎ | 304M/9.90G [00:00<00:20, 462MB/s] pytorch_model-00002-of-00003.bin: 4%|▍ | 419M/9.90G [00:00<00:14, 634MB/s] pytorch_model-00002-of-00003.bin: 6%|▌ | 566M/9.90G [00:01<00:10, 857MB/s] pytorch_model-00002-of-00003.bin: 9%|▉ | 912M/9.90G [00:01<00:05, 1.55GB/s] pytorch_model-00002-of-00003.bin: 12%|█▏ | 1.15G/9.90G [00:01<00:04, 1.78GB/s] pytorch_model-00002-of-00003.bin: 14%|█▎ | 1.35G/9.90G [00:01<00:05, 1.46GB/s] pytorch_model-00002-of-00003.bin: 15%|█▌ | 1.52G/9.90G [00:01<00:07, 1.18GB/s] pytorch_model-00002-of-00003.bin: 17%|█▋ | 1.67G/9.90G [00:01<00:08, 968MB/s] pytorch_model-00002-of-00003.bin: 18%|█▊ | 1.78G/9.90G [00:02<00:08, 910MB/s] pytorch_model-00002-of-00003.bin: 20%|██ | 1.99G/9.90G [00:02<00:06, 1.13GB/s] pytorch_model-00002-of-00003.bin: 23%|██▎ | 2.23G/9.90G [00:02<00:05, 1.40GB/s] pytorch_model-00002-of-00003.bin: 24%|██▍ | 2.42G/9.90G [00:02<00:04, 1.52GB/s] pytorch_model-00002-of-00003.bin: 26%|██▋ | 2.60G/9.90G [00:02<00:04, 1.55GB/s] pytorch_model-00002-of-00003.bin: 28%|██▊ | 2.78G/9.90G [00:02<00:04, 1.44GB/s] pytorch_model-00002-of-00003.bin: 30%|██▉ | 2.94G/9.90G [00:02<00:05, 1.18GB/s] pytorch_model-00002-of-00003.bin: 31%|███ | 3.07G/9.90G [00:02<00:05, 1.20GB/s] pytorch_model-00002-of-00003.bin: 32%|███▏ | 3.21G/9.90G [00:03<00:06, 1.03GB/s] pytorch_model-00002-of-00003.bin: 35%|███▍ | 3.46G/9.90G [00:03<00:04, 1.30GB/s] pytorch_model-00002-of-00003.bin: 36%|███▋ | 3.61G/9.90G [00:03<00:04, 1.30GB/s] pytorch_model-00002-of-00003.bin: 38%|███▊ | 3.75G/9.90G [00:03<00:04, 1.32GB/s] pytorch_model-00002-of-00003.bin: 39%|███▉ | 3.90G/9.90G [00:03<00:05, 1.20GB/s] pytorch_model-00002-of-00003.bin: 41%|████ | 4.03G/9.90G [00:03<00:04, 1.21GB/s] pytorch_model-00002-of-00003.bin: 42%|████▏ | 4.15G/9.90G [00:03<00:04, 1.21GB/s] pytorch_model-00002-of-00003.bin: 43%|████▎ | 4.28G/9.90G [00:03<00:04, 1.14GB/s] pytorch_model-00002-of-00003.bin: 46%|████▌ | 4.51G/9.90G [00:04<00:03, 1.44GB/s] pytorch_model-00002-of-00003.bin: 47%|████▋ | 4.67G/9.90G [00:04<00:03, 1.47GB/s] pytorch_model-00002-of-00003.bin: 49%|████▊ | 4.82G/9.90G [00:04<00:03, 1.38GB/s] pytorch_model-00002-of-00003.bin: 50%|█████ | 4.97G/9.90G [00:04<00:03, 1.34GB/s] pytorch_model-00002-of-00003.bin: 52%|█████▏ | 5.12G/9.90G [00:04<00:03, 1.32GB/s] pytorch_model-00002-of-00003.bin: 53%|█████▎ | 5.25G/9.90G [00:04<00:04, 1.06GB/s] pytorch_model-00002-of-00003.bin: 54%|█████▍ | 5.37G/9.90G [00:04<00:05, 895MB/s] pytorch_model-00002-of-00003.bin: 55%|█████▌ | 5.47G/9.90G [00:05<00:05, 867MB/s] pytorch_model-00002-of-00003.bin: 56%|█████▌ | 5.57G/9.90G [00:05<00:05, 796MB/s] pytorch_model-00002-of-00003.bin: 58%|█████▊ | 5.76G/9.90G [00:05<00:04, 1.03GB/s] pytorch_model-00002-of-00003.bin: 60%|█████▉ | 5.92G/9.90G [00:05<00:03, 1.11GB/s] pytorch_model-00002-of-00003.bin: 62%|██████▏ | 6.10G/9.90G [00:05<00:03, 1.26GB/s] pytorch_model-00002-of-00003.bin: 64%|██████▎ | 6.29G/9.90G [00:05<00:02, 1.42GB/s] pytorch_model-00002-of-00003.bin: 65%|██████▌ | 6.46G/9.90G [00:05<00:02, 1.44GB/s] pytorch_model-00002-of-00003.bin: 67%|██████▋ | 6.62G/9.90G [00:05<00:02, 1.22GB/s] pytorch_model-00002-of-00003.bin: 68%|██████▊ | 6.77G/9.90G [00:05<00:02, 1.30GB/s] pytorch_model-00002-of-00003.bin: 70%|██████▉ | 6.92G/9.90G [00:06<00:02, 1.29GB/s] pytorch_model-00002-of-00003.bin: 71%|███████▏ | 7.06G/9.90G [00:06<00:02, 1.23GB/s] pytorch_model-00002-of-00003.bin: 73%|███████▎ | 7.25G/9.90G [00:06<00:01, 1.38GB/s] pytorch_model-00002-of-00003.bin: 75%|███████▍ | 7.40G/9.90G [00:06<00:01, 1.42GB/s] pytorch_model-00002-of-00003.bin: 76%|███████▋ | 7.56G/9.90G [00:06<00:01, 1.46GB/s] pytorch_model-00002-of-00003.bin: 78%|███████▊ | 7.72G/9.90G [00:06<00:01, 1.37GB/s] pytorch_model-00002-of-00003.bin: 80%|████████ | 7.97G/9.90G [00:06<00:01, 1.63GB/s] pytorch_model-00002-of-00003.bin: 82%|████████▏ | 8.14G/9.90G [00:07<00:01, 1.08GB/s] pytorch_model-00002-of-00003.bin: 84%|████████▎ | 8.27G/9.90G [00:07<00:01, 1.02GB/s] pytorch_model-00002-of-00003.bin: 86%|████████▌ | 8.51G/9.90G [00:07<00:01, 1.30GB/s] pytorch_model-00002-of-00003.bin: 88%|████████▊ | 8.67G/9.90G [00:07<00:01, 1.22GB/s] pytorch_model-00002-of-00003.bin: 90%|█████████ | 8.94G/9.90G [00:07<00:00, 1.56GB/s] pytorch_model-00002-of-00003.bin: 92%|█████████▏| 9.13G/9.90G [00:07<00:00, 1.52GB/s] pytorch_model-00002-of-00003.bin: 94%|█████████▍| 9.32G/9.90G [00:07<00:00, 1.60GB/s] pytorch_model-00002-of-00003.bin: 98%|█████████▊| 9.72G/9.90G [00:07<00:00, 2.19GB/s] pytorch_model-00002-of-00003.bin: 100%|█████████▉| 9.90G/9.90G [00:08<00:00, 1.22GB/s]
chaiml-phase2-winner-13b2-v280-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<02:45, 37.3MB/s] pytorch_model-00003-of-00003.bin: 1%| | 31.5M/6.18G [00:00<01:39, 61.6MB/s] pytorch_model-00003-of-00003.bin: 1%| | 41.9M/6.18G [00:00<01:26, 71.1MB/s] pytorch_model-00003-of-00003.bin: 1%|▏ | 83.9M/6.18G [00:00<00:38, 157MB/s] pytorch_model-00003-of-00003.bin: 2%|▏ | 105M/6.18G [00:00<00:39, 155MB/s] pytorch_model-00003-of-00003.bin: 2%|▏ | 147M/6.18G [00:01<00:29, 207MB/s] pytorch_model-00003-of-00003.bin: 4%|▍ | 241M/6.18G [00:01<00:15, 382MB/s] pytorch_model-00003-of-00003.bin: 9%|▉ | 556M/6.18G [00:01<00:05, 1.10GB/s] pytorch_model-00003-of-00003.bin: 14%|█▍ | 870M/6.18G [00:01<00:03, 1.63GB/s] pytorch_model-00003-of-00003.bin: 18%|█▊ | 1.11G/6.18G [00:01<00:02, 1.82GB/s] pytorch_model-00003-of-00003.bin: 21%|██ | 1.31G/6.18G [00:01<00:04, 1.18GB/s] pytorch_model-00003-of-00003.bin: 24%|██▍ | 1.47G/6.18G [00:02<00:05, 899MB/s] pytorch_model-00003-of-00003.bin: 26%|██▌ | 1.59G/6.18G [00:02<00:05, 886MB/s] pytorch_model-00003-of-00003.bin: 28%|██▊ | 1.71G/6.18G [00:02<00:05, 887MB/s] pytorch_model-00003-of-00003.bin: 30%|██▉ | 1.82G/6.18G [00:02<00:04, 913MB/s] pytorch_model-00003-of-00003.bin: 33%|███▎ | 2.04G/6.18G [00:02<00:03, 1.17GB/s] pytorch_model-00003-of-00003.bin: 35%|███▌ | 2.18G/6.18G [00:02<00:03, 1.20GB/s] pytorch_model-00003-of-00003.bin: 38%|███▊ | 2.33G/6.18G [00:02<00:03, 1.26GB/s] pytorch_model-00003-of-00003.bin: 40%|███▉ | 2.46G/6.18G [00:02<00:03, 1.24GB/s] pytorch_model-00003-of-00003.bin: 42%|████▏ | 2.60G/6.18G [00:02<00:02, 1.23GB/s] pytorch_model-00003-of-00003.bin: 45%|████▍ | 2.78G/6.18G [00:03<00:02, 1.37GB/s] pytorch_model-00003-of-00003.bin: 47%|████▋ | 2.93G/6.18G [00:03<00:02, 1.38GB/s] pytorch_model-00003-of-00003.bin: 50%|████▉ | 3.07G/6.18G [00:03<00:02, 1.33GB/s] pytorch_model-00003-of-00003.bin: 52%|█████▏ | 3.21G/6.18G [00:03<00:02, 1.32GB/s] pytorch_model-00003-of-00003.bin: 55%|█████▍ | 3.38G/6.18G [00:03<00:02, 1.40GB/s] pytorch_model-00003-of-00003.bin: 57%|█████▋ | 3.52G/6.18G [00:03<00:02, 1.32GB/s] pytorch_model-00003-of-00003.bin: 60%|█████▉ | 3.68G/6.18G [00:03<00:01, 1.30GB/s] pytorch_model-00003-of-00003.bin: 62%|██████▏ | 3.85G/6.18G [00:03<00:01, 1.32GB/s] pytorch_model-00003-of-00003.bin: 65%|██████▍ | 4.01G/6.18G [00:04<00:01, 1.31GB/s] pytorch_model-00003-of-00003.bin: 68%|██████▊ | 4.22G/6.18G [00:04<00:01, 1.49GB/s] pytorch_model-00003-of-00003.bin: 71%|███████ | 4.39G/6.18G [00:04<00:01, 1.50GB/s] pytorch_model-00003-of-00003.bin: 74%|███████▎ | 4.55G/6.18G [00:04<00:01, 1.51GB/s] pytorch_model-00003-of-00003.bin: 76%|███████▋ | 4.72G/6.18G [00:04<00:00, 1.54GB/s] pytorch_model-00003-of-00003.bin: 79%|███████▉ | 4.88G/6.18G [00:04<00:01, 1.30GB/s] pytorch_model-00003-of-00003.bin: 81%|████████▏ | 5.02G/6.18G [00:04<00:00, 1.33GB/s] pytorch_model-00003-of-00003.bin: 84%|████████▍ | 5.19G/6.18G [00:04<00:00, 1.38GB/s] pytorch_model-00003-of-00003.bin: 87%|████████▋ | 5.37G/6.18G [00:04<00:00, 1.46GB/s] pytorch_model-00003-of-00003.bin: 92%|█████████▏| 5.67G/6.18G [00:05<00:00, 1.82GB/s] pytorch_model-00003-of-00003.bin: 99%|█████████▉| 6.11G/6.18G [00:05<00:00, 2.50GB/s] pytorch_model-00003-of-00003.bin: 100%|█████████▉| 6.18G/6.18G [00:05<00:00, 1.16GB/s]
chaiml-phase2-winner-13b2-v280-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, 17.0MB/s]
chaiml-phase2-winner-13b2-v280-mkmlizer: special_tokens_map.json: 0%| | 0.00/414 [00:00<?, ?B/s] special_tokens_map.json: 100%|██████████| 414/414 [00:00<00:00, 3.99MB/s]
chaiml-phase2-winner-13b2-v280-mkmlizer: tokenizer.json: 0%| | 0.00/1.84M [00:00<?, ?B/s] tokenizer.json: 100%|██████████| 1.84M/1.84M [00:00<00:00, 51.5MB/s]
chaiml-phase2-winner-13b2-v280-mkmlizer: tokenizer.model: 0%| | 0.00/500k [00:00<?, ?B/s] tokenizer.model: 100%|██████████| 500k/500k [00:00<00:00, 48.2MB/s]
chaiml-phase2-winner-13b2-v280-mkmlizer: Profiling: 0%| | 0/363 [00:00<?, ?it/s] Profiling: 0%| | 1/363 [00:03<23:23, 3.88s/it] Profiling: 38%|███▊ | 139/363 [00:06<00:08, 27.12it/s] Profiling: 77%|███████▋ | 278/363 [00:07<00:01, 45.64it/s] Profiling: 100%|██████████| 363/363 [00:09<00:00, 46.65it/s] Profiling: 100%|██████████| 363/363 [00:09<00:00, 37.75it/s]
chaiml-phase2-winner-13b2-v280-mkmlizer: quantized model in 29.946s
chaiml-phase2-winner-13b2-v280-mkmlizer: Processed model ChaiML/phase2_winner_13b2 in 61.167s
chaiml-phase2-winner-13b2-v280-mkmlizer: creating bucket guanaco-mkml-models
chaiml-phase2-winner-13b2-v280-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-phase2-winner-13b2-v280-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-phase2-winner-13b2-v280
chaiml-phase2-winner-13b2-v280-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-phase2-winner-13b2-v280/tokenizer_config.json
chaiml-phase2-winner-13b2-v280-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-phase2-winner-13b2-v280/special_tokens_map.json
chaiml-phase2-winner-13b2-v280-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-phase2-winner-13b2-v280/config.json
chaiml-phase2-winner-13b2-v280-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/chaiml-phase2-winner-13b2-v280/tokenizer.model
chaiml-phase2-winner-13b2-v280-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-phase2-winner-13b2-v280/tokenizer.json
chaiml-phase2-winner-13b2-v280-mkmlizer: cp /dev/shm/model_cache/mkml_model.tensors s3://guanaco-mkml-models/chaiml-phase2-winner-13b2-v280/mkml_model.tensors
chaiml-phase2-winner-13b2-v280-mkmlizer: loading reward model from rirv938/reward_gpt2_medium_preference_24m_e2
chaiml-phase2-winner-13b2-v280-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-v280-mkmlizer: warnings.warn(
chaiml-phase2-winner-13b2-v280-mkmlizer: config.json: 0%| | 0.00/1.05k [00:00<?, ?B/s] config.json: 100%|██████████| 1.05k/1.05k [00:00<00:00, 11.7MB/s]
chaiml-phase2-winner-13b2-v280-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-v280-mkmlizer: warnings.warn(
chaiml-phase2-winner-13b2-v280-mkmlizer: tokenizer_config.json: 0%| | 0.00/234 [00:00<?, ?B/s] tokenizer_config.json: 100%|██████████| 234/234 [00:00<00:00, 1.95MB/s]
chaiml-phase2-winner-13b2-v280-mkmlizer: vocab.json: 0%| | 0.00/1.04M [00:00<?, ?B/s] vocab.json: 100%|██████████| 1.04M/1.04M [00:00<00:00, 12.2MB/s]
chaiml-phase2-winner-13b2-v280-mkmlizer: tokenizer.json: 0%| | 0.00/2.11M [00:00<?, ?B/s] tokenizer.json: 100%|██████████| 2.11M/2.11M [00:00<00:00, 31.4MB/s]
chaiml-phase2-winner-13b2-v280-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-v280-mkmlizer: warnings.warn(
chaiml-phase2-winner-13b2-v280-mkmlizer: pytorch_model.bin: 0%| | 0.00/1.44G [00:00<?, ?B/s] pytorch_model.bin: 1%| | 10.5M/1.44G [00:00<01:09, 20.7MB/s] pytorch_model.bin: 4%|▎ | 52.4M/1.44G [00:00<00:17, 80.7MB/s] pytorch_model.bin: 9%|▊ | 126M/1.44G [00:00<00:06, 200MB/s] pytorch_model.bin: 15%|█▌ | 220M/1.44G [00:00<00:03, 353MB/s] pytorch_model.bin: 20%|█▉ | 283M/1.44G [00:01<00:02, 397MB/s] pytorch_model.bin: 28%|██▊ | 398M/1.44G [00:01<00:01, 543MB/s] pytorch_model.bin: 35%|███▍ | 503M/1.44G [00:01<00:01, 660MB/s] pytorch_model.bin: 45%|████▌ | 650M/1.44G [00:01<00:00, 845MB/s] pytorch_model.bin: 53%|█████▎ | 765M/1.44G [00:01<00:00, 871MB/s] pytorch_model.bin: 66%|██████▌ | 952M/1.44G [00:01<00:00, 1.13GB/s] pytorch_model.bin: 80%|███████▉ | 1.15G/1.44G [00:01<00:00, 1.36GB/s] pytorch_model.bin: 90%|████████▉ | 1.30G/1.44G [00:01<00:00, 1.25GB/s] pytorch_model.bin: 99%|█████████▉| 1.43G/1.44G [00:05<00:00, 135MB/s] pytorch_model.bin: 100%|█████████▉| 1.44G/1.44G [00:05<00:00, 265MB/s]
chaiml-phase2-winner-13b2-v280-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
chaiml-phase2-winner-13b2-v280-mkmlizer: Saving duration: 0.321s
chaiml-phase2-winner-13b2-v280-mkmlizer: Processed model rirv938/reward_gpt2_medium_preference_24m_e2 in 14.779s
chaiml-phase2-winner-13b2-v280-mkmlizer: creating bucket guanaco-reward-models
chaiml-phase2-winner-13b2-v280-mkmlizer: Bucket 's3://guanaco-reward-models/' created
chaiml-phase2-winner-13b2-v280-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/chaiml-phase2-winner-13b2-v280_reward
chaiml-phase2-winner-13b2-v280-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/chaiml-phase2-winner-13b2-v280_reward/config.json
chaiml-phase2-winner-13b2-v280-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/chaiml-phase2-winner-13b2-v280_reward/special_tokens_map.json
chaiml-phase2-winner-13b2-v280-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/chaiml-phase2-winner-13b2-v280_reward/tokenizer_config.json
chaiml-phase2-winner-13b2-v280-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/chaiml-phase2-winner-13b2-v280_reward/merges.txt
chaiml-phase2-winner-13b2-v280-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/chaiml-phase2-winner-13b2-v280_reward/vocab.json
chaiml-phase2-winner-13b2-v280-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/chaiml-phase2-winner-13b2-v280_reward/tokenizer.json
chaiml-phase2-winner-13b2-v280-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/chaiml-phase2-winner-13b2-v280_reward/reward.tensors
Job chaiml-phase2-winner-13b2-v280-mkmlizer completed after 97.69s with status: succeeded
Stopping job with name chaiml-phase2-winner-13b2-v280-mkmlizer
Pipeline stage MKMLizer completed in 99.93s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.12s
Running pipeline stage ISVCDeployer
Creating inference service chaiml-phase2-winner-13b2-v280
Waiting for inference service chaiml-phase2-winner-13b2-v280 to be ready
Inference service chaiml-phase2-winner-13b2-v280 ready after 50.440863370895386s
Pipeline stage ISVCDeployer completed in 57.06s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.6052746772766113s
Received healthy response to inference request in 2.0164599418640137s
Received healthy response to inference request in 1.9680650234222412s
Received healthy response to inference request in 2.0703911781311035s
Received healthy response to inference request in 1.7487382888793945s
5 requests
0 failed requests
5th percentile: 1.7926036357879638
10th percentile: 1.8364689826965332
20th percentile: 1.924199676513672
30th percentile: 1.9777440071105956
40th percentile: 1.9971019744873046
50th percentile: 2.0164599418640137
60th percentile: 2.0380324363708495
70th percentile: 2.0596049308776854
80th percentile: 2.1773678779602053
90th percentile: 2.3913212776184083
95th percentile: 2.4982979774475096
99th percentile: 2.583879337310791
mean time: 2.0817858219146728
Pipeline stage StressChecker completed in 11.31s
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 0.04s
M-Eval Dataset for topic stay_in_character is loaded
chaiml-phase2-winner-13b2_v280 status is now deployed due to DeploymentManager action
chaiml-phase2-winner-13b2_v280 status is now inactive due to auto deactivation removed underperforming models

Usage Metrics

Latency Metrics