submission_id: sao10k-fimbulvetr-11b-v2_v4
developer_uid: sao10k
status: inactive
model_repo: Sao10K/Fimbulvetr-11B-v2
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 0.9, 'top_p': 0.9, 'top_k': 50, 'presence_penalty': 0.9, 'frequency_penalty': 0.9, 'stopping_words': ['\n', '</s>', '\n###'], 'max_input_tokens': 512, 'best_of': 8, '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', 'bot_template': '### Response: {bot_name}: {message}\n</s>', 'user_template': '### Input: {user_name}: {message}\n', 'response_template': '### Response: {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': '### Response:\n{bot_name}:'}
timestamp: 2024-04-02T15:24:29+00:00
model_name: sao10k-fimbulvetr-11b-v2_v4
model_eval_status: success
safety_score: 0.78
entertaining: 7.12
stay_in_character: 8.67
user_preference: 7.6
double_thumbs_up: 350
thumbs_up: 496
thumbs_down: 198
num_battles: 30882
num_wins: 16115
win_ratio: 0.5218250113334628
celo_rating: 1171.67
Resubmit model
Running pipeline stage MKMLizer
Starting job with name sao10k-fimbulvetr-11b-v2-v4-mkmlizer
Waiting for job on sao10k-fimbulvetr-11b-v2-v4-mkmlizer to finish
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ _____ __ __ ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ /___/ ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ Version: 0.6.11 ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ The license key for the current software has been verified as ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ belonging to: ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ Chai Research Corp. ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ║ ║
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
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sao10k-fimbulvetr-11b-v2-v4-mkmlizer: tokenizer.json: 0%| | 0.00/1.80M [00:00<?, ?B/s] tokenizer.json: 100%|██████████| 1.80M/1.80M [00:00<00:00, 34.0MB/s]
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sao10k-fimbulvetr-11b-v2-v4-mkmlizer: Downloaded to shared memory in 29.506s
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: quantizing model to /dev/shm/model_cache
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: Saving mkml model at /dev/shm/model_cache
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: Reading /tmp/tmpn4_nd8qz/model.safetensors.index.json
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: Profiling: 0%| | 0/435 [00:00<?, ?it/s] Profiling: 0%| | 1/435 [00:01<09:27, 1.31s/it] Profiling: 4%|▍ | 18/435 [00:01<00:23, 17.43it/s] Profiling: 9%|▊ | 37/435 [00:01<00:10, 38.62it/s] Profiling: 13%|█▎ | 56/435 [00:01<00:06, 60.44it/s] Profiling: 19%|█▊ | 81/435 [00:01<00:03, 91.56it/s] Profiling: 23%|██▎ | 99/435 [00:02<00:04, 74.32it/s] Profiling: 27%|██▋ | 117/435 [00:02<00:03, 91.10it/s] Profiling: 32%|███▏ | 138/435 [00:02<00:02, 111.76it/s] Profiling: 36%|███▌ | 157/435 [00:02<00:02, 125.13it/s] Profiling: 40%|████ | 176/435 [00:02<00:01, 136.95it/s] Profiling: 45%|████▌ | 196/435 [00:02<00:01, 151.86it/s] Profiling: 49%|████▉ | 214/435 [00:02<00:02, 101.50it/s] Profiling: 53%|█████▎ | 229/435 [00:03<00:01, 109.48it/s] Profiling: 57%|█████▋ | 247/435 [00:03<00:01, 120.64it/s] Profiling: 61%|██████ | 265/435 [00:03<00:01, 132.77it/s] Profiling: 65%|██████▌ | 284/435 [00:03<00:01, 146.48it/s] Profiling: 70%|██████▉ | 304/435 [00:03<00:01, 111.35it/s] Profiling: 74%|███████▎ | 320/435 [00:03<00:00, 119.84it/s] Profiling: 79%|███████▉ | 345/435 [00:03<00:00, 147.79it/s] Profiling: 84%|████████▍ | 365/435 [00:03<00:00, 158.26it/s] Profiling: 90%|████████▉ | 390/435 [00:04<00:00, 180.05it/s] Profiling: 94%|█████████▍| 410/435 [00:05<00:00, 40.40it/s] Profiling: 99%|█████████▊| 429/435 [00:05<00:00, 51.50it/s] Profiling: 100%|██████████| 435/435 [00:05<00:00, 76.64it/s]
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: quantized model in 20.200s
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: Processed model Sao10K/Fimbulvetr-11B-v2 in 51.035s
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: creating bucket guanaco-mkml-models
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/sao10k-fimbulvetr-11b-v2-v4
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/sao10k-fimbulvetr-11b-v2-v4/special_tokens_map.json
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/sao10k-fimbulvetr-11b-v2-v4/tokenizer_config.json
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/sao10k-fimbulvetr-11b-v2-v4/tokenizer.json
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/sao10k-fimbulvetr-11b-v2-v4/config.json
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/sao10k-fimbulvetr-11b-v2-v4/tokenizer.model
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: cp /dev/shm/model_cache/mkml_model.tensors s3://guanaco-mkml-models/sao10k-fimbulvetr-11b-v2-v4/mkml_model.tensors
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
sao10k-fimbulvetr-11b-v2-v4-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.
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: warnings.warn(
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: config.json: 0%| | 0.00/1.05k [00:00<?, ?B/s] config.json: 100%|██████████| 1.05k/1.05k [00:00<00:00, 11.9MB/s]
sao10k-fimbulvetr-11b-v2-v4-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.
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: warnings.warn(
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: tokenizer_config.json: 0%| | 0.00/234 [00:00<?, ?B/s] tokenizer_config.json: 100%|██████████| 234/234 [00:00<00:00, 1.83MB/s]
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: vocab.json: 0%| | 0.00/1.04M [00:00<?, ?B/s] vocab.json: 100%|██████████| 1.04M/1.04M [00:00<00:00, 25.5MB/s]
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: tokenizer.json: 0%| | 0.00/2.11M [00:00<?, ?B/s] tokenizer.json: 100%|██████████| 2.11M/2.11M [00:00<00:00, 32.0MB/s]
sao10k-fimbulvetr-11b-v2-v4-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.
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: warnings.warn(
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: pytorch_model.bin: 0%| | 0.00/1.44G [00:00<?, ?B/s] pytorch_model.bin: 1%| | 10.5M/1.44G [00:00<00:23, 60.7MB/s] pytorch_model.bin: 2%|▏ | 31.5M/1.44G [00:00<00:22, 62.6MB/s] pytorch_model.bin: 3%|▎ | 41.9M/1.44G [00:00<00:21, 66.0MB/s] pytorch_model.bin: 7%|▋ | 105M/1.44G [00:00<00:09, 136MB/s] pytorch_model.bin: 9%|▉ | 136M/1.44G [00:01<00:07, 164MB/s] pytorch_model.bin: 12%|█▏ | 178M/1.44G [00:01<00:06, 209MB/s] pytorch_model.bin: 21%|██ | 304M/1.44G [00:01<00:02, 438MB/s] pytorch_model.bin: 69%|██████▉ | 996M/1.44G [00:01<00:00, 1.99GB/s] pytorch_model.bin: 87%|████████▋ | 1.26G/1.44G [00:01<00:00, 2.13GB/s] pytorch_model.bin: 100%|█████████▉| 1.44G/1.44G [00:01<00:00, 942MB/s]
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: Saving duration: 0.223s
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 8.408s
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: creating bucket guanaco-reward-models
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: Bucket 's3://guanaco-reward-models/' created
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/sao10k-fimbulvetr-11b-v2-v4_reward
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/sao10k-fimbulvetr-11b-v2-v4_reward/config.json
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/sao10k-fimbulvetr-11b-v2-v4_reward/special_tokens_map.json
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/sao10k-fimbulvetr-11b-v2-v4_reward/vocab.json
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/sao10k-fimbulvetr-11b-v2-v4_reward/merges.txt
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/sao10k-fimbulvetr-11b-v2-v4_reward/tokenizer_config.json
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/sao10k-fimbulvetr-11b-v2-v4_reward/tokenizer.json
sao10k-fimbulvetr-11b-v2-v4-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/sao10k-fimbulvetr-11b-v2-v4_reward/reward.tensors
Job sao10k-fimbulvetr-11b-v2-v4-mkmlizer completed after 85.59s with status: succeeded
Stopping job with name sao10k-fimbulvetr-11b-v2-v4-mkmlizer
Pipeline stage MKMLizer completed in 90.64s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.12s
Running pipeline stage ISVCDeployer
Creating inference service sao10k-fimbulvetr-11b-v2-v4
Waiting for inference service sao10k-fimbulvetr-11b-v2-v4 to be ready
Inference service sao10k-fimbulvetr-11b-v2-v4 ready after 50.416630029678345s
Pipeline stage ISVCDeployer completed in 58.88s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.35681414604187s
Received healthy response to inference request in 1.5610921382904053s
Received healthy response to inference request in 1.221590280532837s
Received healthy response to inference request in 1.7070045471191406s
Received healthy response to inference request in 1.406836748123169s
5 requests
0 failed requests
5th percentile: 1.2586395740509033
10th percentile: 1.2956888675689697
20th percentile: 1.3697874546051025
30th percentile: 1.4376878261566162
40th percentile: 1.4993899822235108
50th percentile: 1.5610921382904053
60th percentile: 1.6194571018218995
70th percentile: 1.6778220653533935
80th percentile: 1.8369664669036867
90th percentile: 2.0968903064727784
95th percentile: 2.226852226257324
99th percentile: 2.3308217620849607
mean time: 1.6506675720214843
Pipeline stage StressChecker completed in 9.46s
Running pipeline stage DaemonicModelEvalScorer
Pipeline stage DaemonicModelEvalScorer completed in 0.07s
Running pipeline stage DaemonicSafetyScorer
Running M-Eval for topic stay_in_character
Pipeline stage DaemonicSafetyScorer completed in 0.07s
M-Eval Dataset for topic stay_in_character is loaded
sao10k-fimbulvetr-11b-v2_v4 status is now deployed due to DeploymentManager action
sao10k-fimbulvetr-11b-v2_v4 status is now inactive due to auto deactivation removed underperforming models

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