submission_id: cgato-thespice-7b-ft-exp_6888_v3
developer_uid: c.gato
status: inactive
model_repo: cgato/TheSpice-7b-FT-ExperimentalOrca-LessOrca
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 512, 'best_of': 16, 'max_output_tokens': 64}
formatter: {'memory_template': "{bot_name} is having an engaging and entertaining chat with {user_name}. {bot_name}'s Personality: {memory}\n", 'prompt_template': '***\n{prompt}\n***\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '{bot_name}:'}
reward_formatter: {'memory_template': "{bot_name} is having an engaging and entertaining chat with {user_name}. {bot_name}'s Personality: {memory}\n", 'prompt_template': '***\n{prompt}\n***\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '{bot_name}:'}
timestamp: 2024-03-27T11:15:48+00:00
model_name: cgato-thespice-7b-ft-exp_6888_v3
model_eval_status: success
safety_score: 0.86
entertaining: 7.02
stay_in_character: 8.54
user_preference: 7.5
double_thumbs_up: 811
thumbs_up: 1114
thumbs_down: 491
num_battles: 112793
num_wins: 59038
win_ratio: 0.5234190064986303
celo_rating: 1174.35
Resubmit model
Running pipeline stage MKMLizer
Starting job with name cgato-thespice-7b-ft-exp-6888-v3-mkmlizer
Waiting for job on cgato-thespice-7b-ft-exp-6888-v3-mkmlizer to finish
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ _____ __ __ ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ /___/ ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ Version: 0.6.11 ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ The license key for the current software has been verified as ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ belonging to: ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ Chai Research Corp. ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ║ ║
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
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cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: Downloaded to shared memory in 15.644s
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: quantizing model to /dev/shm/model_cache
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: Saving mkml model at /dev/shm/model_cache
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: Reading /tmp/tmp5jzl9a4o/model.safetensors.index.json
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: Profiling: 0%| | 0/291 [00:00<?, ?it/s] Profiling: 0%| | 1/291 [00:01<06:15, 1.29s/it] Profiling: 4%|▍ | 12/291 [00:01<00:23, 11.63it/s] Profiling: 8%|▊ | 23/291 [00:01<00:11, 23.79it/s] Profiling: 12%|█▏ | 36/291 [00:01<00:06, 39.55it/s] Profiling: 16%|█▌ | 47/291 [00:01<00:04, 50.69it/s] Profiling: 22%|██▏ | 63/291 [00:01<00:03, 71.08it/s] Profiling: 26%|██▌ | 75/291 [00:01<00:02, 78.27it/s] Profiling: 31%|███ | 90/291 [00:02<00:02, 93.64it/s] Profiling: 35%|███▌ | 103/291 [00:02<00:03, 56.21it/s] Profiling: 40%|███▉ | 116/291 [00:02<00:02, 67.77it/s] Profiling: 45%|████▍ | 130/291 [00:02<00:02, 79.10it/s] Profiling: 49%|████▉ | 144/291 [00:02<00:01, 91.39it/s] Profiling: 54%|█████▍ | 157/291 [00:02<00:01, 99.17it/s] Profiling: 59%|█████▉ | 171/291 [00:03<00:01, 108.44it/s] Profiling: 63%|██████▎ | 184/291 [00:03<00:00, 112.73it/s] Profiling: 68%|██████▊ | 198/291 [00:03<00:00, 119.72it/s] Profiling: 73%|███████▎ | 211/291 [00:04<00:03, 23.41it/s] Profiling: 76%|███████▌ | 221/291 [00:04<00:02, 28.22it/s] Profiling: 81%|████████ | 235/291 [00:05<00:01, 38.13it/s] Profiling: 85%|████████▌ | 248/291 [00:05<00:00, 48.26it/s] Profiling: 90%|█████████ | 263/291 [00:05<00:00, 62.25it/s] Profiling: 95%|█████████▍| 276/291 [00:05<00:00, 71.08it/s] Profiling: 100%|██████████| 291/291 [00:05<00:00, 50.59it/s]
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: quantized model in 16.982s
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: Processed model cgato/TheSpice-7b-FT-ExperimentalOrca-LessOrca in 33.750s
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: creating bucket guanaco-mkml-models
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/cgato-thespice-7b-ft-exp-6888-v3
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/cgato-thespice-7b-ft-exp-6888-v3/config.json
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/cgato-thespice-7b-ft-exp-6888-v3/tokenizer_config.json
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/cgato-thespice-7b-ft-exp-6888-v3/special_tokens_map.json
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/cgato-thespice-7b-ft-exp-6888-v3/tokenizer.model
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/cgato-thespice-7b-ft-exp-6888-v3/tokenizer.json
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: cp /dev/shm/model_cache/mkml_model.tensors s3://guanaco-mkml-models/cgato-thespice-7b-ft-exp-6888-v3/mkml_model.tensors
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
cgato-thespice-7b-ft-exp-6888-v3-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.
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: warnings.warn(
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: config.json: 0%| | 0.00/1.05k [00:00<?, ?B/s] config.json: 100%|██████████| 1.05k/1.05k [00:00<00:00, 11.0MB/s]
cgato-thespice-7b-ft-exp-6888-v3-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.
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: warnings.warn(
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: tokenizer_config.json: 0%| | 0.00/234 [00:00<?, ?B/s] tokenizer_config.json: 100%|██████████| 234/234 [00:00<00:00, 1.99MB/s]
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: vocab.json: 0%| | 0.00/1.04M [00:00<?, ?B/s] vocab.json: 100%|██████████| 1.04M/1.04M [00:00<00:00, 40.0MB/s]
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: tokenizer.json: 0%| | 0.00/2.11M [00:00<?, ?B/s] tokenizer.json: 100%|██████████| 2.11M/2.11M [00:00<00:00, 33.7MB/s]
cgato-thespice-7b-ft-exp-6888-v3-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.
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: warnings.warn(
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: pytorch_model.bin: 0%| | 0.00/1.44G [00:00<?, ?B/s] pytorch_model.bin: 2%|▏ | 31.5M/1.44G [00:00<00:05, 264MB/s] pytorch_model.bin: 4%|▍ | 62.9M/1.44G [00:00<00:07, 175MB/s] pytorch_model.bin: 12%|█▏ | 168M/1.44G [00:00<00:03, 379MB/s] pytorch_model.bin: 18%|█▊ | 262M/1.44G [00:00<00:02, 521MB/s] pytorch_model.bin: 24%|██▍ | 346M/1.44G [00:00<00:01, 599MB/s] pytorch_model.bin: 29%|██▉ | 419M/1.44G [00:00<00:01, 542MB/s] pytorch_model.bin: 38%|███▊ | 556M/1.44G [00:01<00:01, 712MB/s] pytorch_model.bin: 49%|████▊ | 703M/1.44G [00:01<00:00, 885MB/s] pytorch_model.bin: 62%|██████▏ | 902M/1.44G [00:01<00:00, 1.16GB/s] pytorch_model.bin: 100%|█████████▉| 1.44G/1.44G [00:01<00:00, 1.07GB/s]
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: Saving duration: 0.268s
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 5.160s
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: creating bucket guanaco-reward-models
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: Bucket 's3://guanaco-reward-models/' created
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/cgato-thespice-7b-ft-exp-6888-v3_reward
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/cgato-thespice-7b-ft-exp-6888-v3_reward/special_tokens_map.json
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/cgato-thespice-7b-ft-exp-6888-v3_reward/tokenizer_config.json
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/cgato-thespice-7b-ft-exp-6888-v3_reward/config.json
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/cgato-thespice-7b-ft-exp-6888-v3_reward/merges.txt
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/cgato-thespice-7b-ft-exp-6888-v3_reward/vocab.json
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/cgato-thespice-7b-ft-exp-6888-v3_reward/tokenizer.json
cgato-thespice-7b-ft-exp-6888-v3-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/cgato-thespice-7b-ft-exp-6888-v3_reward/reward.tensors
Job cgato-thespice-7b-ft-exp-6888-v3-mkmlizer completed after 64.01s with status: succeeded
Stopping job with name cgato-thespice-7b-ft-exp-6888-v3-mkmlizer
Pipeline stage MKMLizer completed in 64.84s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.13s
Running pipeline stage ISVCDeployer
Creating inference service cgato-thespice-7b-ft-exp-6888-v3
Waiting for inference service cgato-thespice-7b-ft-exp-6888-v3 to be ready
Inference service cgato-thespice-7b-ft-exp-6888-v3 ready after 40.242870569229126s
Pipeline stage ISVCDeployer completed in 46.14s
Running pipeline stage StressChecker
Received healthy response to inference request in 1.7350854873657227s
Received healthy response to inference request in 1.2157742977142334s
Received healthy response to inference request in 1.2066893577575684s
Received healthy response to inference request in 1.2121641635894775s
Received healthy response to inference request in 1.199507474899292s
5 requests
0 failed requests
5th percentile: 1.2009438514709472
10th percentile: 1.2023802280426026
20th percentile: 1.2052529811859132
30th percentile: 1.20778431892395
40th percentile: 1.2099742412567138
50th percentile: 1.2121641635894775
60th percentile: 1.2136082172393798
70th percentile: 1.2150522708892821
80th percentile: 1.3196365356445314
90th percentile: 1.527361011505127
95th percentile: 1.6312232494354246
99th percentile: 1.714313039779663
mean time: 1.3138441562652587
Pipeline stage StressChecker completed in 7.45s
Running pipeline stage DaemonicModelEvalScorer
Pipeline stage DaemonicModelEvalScorer completed in 0.05s
Running M-Eval for topic stay_in_character
Running pipeline stage DaemonicSafetyScorer
M-Eval Dataset for topic stay_in_character is loaded
Pipeline stage DaemonicSafetyScorer completed in 0.15s
%s, retrying in %s seconds...
cgato-thespice-7b-ft-exp_6888_v3 status is now deployed due to DeploymentManager action
Running M-Eval for topic stay_in_character
M-Eval Dataset for topic stay_in_character is loaded
cgato-thespice-7b-ft-exp_6888_v3 status is now inactive due to auto deactivation removed underperforming models

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