submission_id: a100-anhnv125-llama-op-v17-1_v32
developer_uid: chai_backend_admin
status: inactive
model_repo: anhnv125/llama-op-v17.1
reward_repo: rirv938/gpt2_ties_merge_preference_plus_classic_e2_density_99
generation_params: {'temperature': 1.1, 'top_p': 1.0, 'top_k': 20, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '</s>', '<|im_end|>'], 'max_input_tokens': 1024, 'best_of': 4, 'max_output_tokens': 64}
formatter: {'memory_template': "### Instruction:\nAs the assistant, your task is to fully embody the given character, creating immersive, captivating narratives. Stay true to the character's personality and background, generating responses that not only reflect their core traits but are also accurate to their character. Your responses should evoke emotion, suspense, and anticipation in the user. The more detailed and descriptive your response, the more vivid the narrative becomes. Aim to create a fertile environment for ongoing interaction – introduce new elements, offer choices, or ask questions to invite the user to participate more fully in the conversation. This conversation is a dance, always continuing, always evolving.\nYour character: {bot_name}.\nContext: {memory}\n", 'prompt_template': '### Input:\n{prompt}\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '### Response:\n{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: 2024-02-25T00:04:03+00:00
model_name: anhnv125-llama-op-v17-1_v32
model_eval_status: success
safety_score: 0.98
entertaining: 7.02
stay_in_character: 8.54
user_preference: 7.44
double_thumbs_up: 1511
thumbs_up: 2240
thumbs_down: 1028
num_battles: 175813
num_wins: 84812
win_ratio: 0.4823989124808746
celo_rating: 1141.76
Resubmit model
Running pipeline stage MKMLizer
Starting job with name anhnv125-llama-op-v17-1-v32-mkmlizer
Waiting for job on anhnv125-llama-op-v17-1-v32-mkmlizer to finish
anhnv125-llama-op-v17-1-v32-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ _____ __ __ ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ /___/ ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ Version: 0.6.11 ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ The license key for the current software has been verified as ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ belonging to: ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ Chai Research Corp. ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ Expiration: 2024-04-15 23:59:59 ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ║ ║
anhnv125-llama-op-v17-1-v32-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
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anhnv125-llama-op-v17-1-v32-mkmlizer: Downloaded to shared memory in 39.792s
anhnv125-llama-op-v17-1-v32-mkmlizer: quantizing model to /dev/shm/model_cache
anhnv125-llama-op-v17-1-v32-mkmlizer: Saving mkml model at /dev/shm/model_cache
anhnv125-llama-op-v17-1-v32-mkmlizer: Reading /tmp/tmpsjhavxct/model.safetensors.index.json
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anhnv125-llama-op-v17-1-v32-mkmlizer: quantized model in 31.374s
anhnv125-llama-op-v17-1-v32-mkmlizer: Processed model anhnv125/llama-op-v17.1 in 73.294s
anhnv125-llama-op-v17-1-v32-mkmlizer: creating bucket guanaco-mkml-models
anhnv125-llama-op-v17-1-v32-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
anhnv125-llama-op-v17-1-v32-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/anhnv125-llama-op-v17-1-v32
anhnv125-llama-op-v17-1-v32-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/anhnv125-llama-op-v17-1-v32/config.json
anhnv125-llama-op-v17-1-v32-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/anhnv125-llama-op-v17-1-v32/tokenizer_config.json
anhnv125-llama-op-v17-1-v32-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/anhnv125-llama-op-v17-1-v32/special_tokens_map.json
anhnv125-llama-op-v17-1-v32-mkmlizer: cp /dev/shm/model_cache/tokenizer.model s3://guanaco-mkml-models/anhnv125-llama-op-v17-1-v32/tokenizer.model
anhnv125-llama-op-v17-1-v32-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/anhnv125-llama-op-v17-1-v32/tokenizer.json
anhnv125-llama-op-v17-1-v32-mkmlizer: cp /dev/shm/model_cache/added_tokens.json s3://guanaco-mkml-models/anhnv125-llama-op-v17-1-v32/added_tokens.json
anhnv125-llama-op-v17-1-v32-mkmlizer: cp /dev/shm/model_cache/mkml_model.tensors s3://guanaco-mkml-models/anhnv125-llama-op-v17-1-v32/mkml_model.tensors
anhnv125-llama-op-v17-1-v32-mkmlizer: loading reward model from rirv938/gpt2_ties_merge_preference_plus_classic_e2_density_99
anhnv125-llama-op-v17-1-v32-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.
anhnv125-llama-op-v17-1-v32-mkmlizer: warnings.warn(
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anhnv125-llama-op-v17-1-v32-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.
anhnv125-llama-op-v17-1-v32-mkmlizer: warnings.warn(
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anhnv125-llama-op-v17-1-v32-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.
anhnv125-llama-op-v17-1-v32-mkmlizer: warnings.warn(
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anhnv125-llama-op-v17-1-v32-mkmlizer: Downloading shards: 100%|██████████| 1/1 [00:01<00:00, 1.01s/it] Downloading shards: 100%|██████████| 1/1 [00:01<00:00, 1.01s/it]
anhnv125-llama-op-v17-1-v32-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
anhnv125-llama-op-v17-1-v32-mkmlizer: Saving duration: 0.109s
anhnv125-llama-op-v17-1-v32-mkmlizer: Processed model rirv938/gpt2_ties_merge_preference_plus_classic_e2_density_99 in 3.373s
anhnv125-llama-op-v17-1-v32-mkmlizer: creating bucket guanaco-reward-models
anhnv125-llama-op-v17-1-v32-mkmlizer: Bucket 's3://guanaco-reward-models/' created
anhnv125-llama-op-v17-1-v32-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/anhnv125-llama-op-v17-1-v32_reward
anhnv125-llama-op-v17-1-v32-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/anhnv125-llama-op-v17-1-v32_reward/config.json
anhnv125-llama-op-v17-1-v32-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/anhnv125-llama-op-v17-1-v32_reward/tokenizer_config.json
anhnv125-llama-op-v17-1-v32-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/anhnv125-llama-op-v17-1-v32_reward/special_tokens_map.json
anhnv125-llama-op-v17-1-v32-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/anhnv125-llama-op-v17-1-v32_reward/merges.txt
anhnv125-llama-op-v17-1-v32-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/anhnv125-llama-op-v17-1-v32_reward/vocab.json
anhnv125-llama-op-v17-1-v32-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/anhnv125-llama-op-v17-1-v32_reward/tokenizer.json
anhnv125-llama-op-v17-1-v32-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/anhnv125-llama-op-v17-1-v32_reward/reward.tensors
Job anhnv125-llama-op-v17-1-v32-mkmlizer completed after 160.08s with status: succeeded
Stopping job with name anhnv125-llama-op-v17-1-v32-mkmlizer
Pipeline stage MKMLizer completed in 168.24s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.17s
Running pipeline stage ISVCDeployer
Creating inference service anhnv125-llama-op-v17-1-v32
Waiting for inference service anhnv125-llama-op-v17-1-v32 to be ready
Inference service anhnv125-llama-op-v17-1-v32 ready after 150.9457550048828s
Pipeline stage ISVCDeployer completed in 159.80s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.8894195556640625s
Received healthy response to inference request in 1.5008330345153809s
Received healthy response to inference request in 1.4162442684173584s
Received healthy response to inference request in 1.9030015468597412s
Received healthy response to inference request in 1.9024882316589355s
5 requests
0 failed requests
5th percentile: 1.433162021636963
10th percentile: 1.4500797748565675
20th percentile: 1.4839152812957763
30th percentile: 1.5811640739440918
40th percentile: 1.7418261528015138
50th percentile: 1.9024882316589355
60th percentile: 1.9026935577392579
70th percentile: 1.9028988838195802
80th percentile: 2.1002851486206056
90th percentile: 2.4948523521423343
95th percentile: 2.692135953903198
99th percentile: 2.8499628353118895
mean time: 1.9223973274230957
Pipeline stage StressChecker completed in 10.60s
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 0.06s
M-Eval Dataset for topic stay_in_character is loaded
a100-anhnv125-llama-op-v17-1_v32 status is now inactive due to auto deactivation removed underperforming models
a100-anhnv125-llama-op-v17-1_v32 status is now deployed due to admin request
a100-anhnv125-llama-op-v17-1_v32 status is now inactive due to auto deactivation removed underperforming models

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