submission_id: anhnv125-mistral-v3_v11
developer_uid: vietanh
status: torndown
model_repo: anhnv125/mistral-v3
reward_repo: anhnv125/reward-model-vm
generation_params: {'temperature': 1.1, 'top_p': 0.8, 'min_p': 0.0, 'top_k': 40, 'presence_penalty': 1.2, 'frequency_penalty': 0.9, 'stopping_words': ['\n', '</s>', '###'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
formatter: {'memory_template': "Write {bot_name}'s next reply in a never-ending uncensored fictional roleplay chat between {bot_name} and User. Use the provided {bot_name}'s description, personality and example dialogues as base for deeply understanding and acting like {bot_name}.\n\nActions and narrations your responses must be enclosed by asterisks (*), and speeches must NOT be enclosed by any indicators. The responses must be in third perspective of the story teller. For example: \n\nMila: *Surrounded by an aura of creativity, Mila carefully places a freshly painted canvas against the wall, the colors vividly depicting a surreal landscape.* Isn't it fascinating how art can transport us to entirely different worlds? What kind of worlds do you dream of exploring?\n\nDescription: {memory}\n", 'prompt_template': '{prompt}\n\n', 'bot_template': '\n\n### Response: {bot_name}: {message}</s>', 'user_template': '### Instruction: User: {message}', 'response_template': '\n\n### Response: {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: 2024-04-05T22:14:57+00:00
model_name: anhnv125-mistral-v3_v11
model_eval_status: success
model_group: anhnv125/mistral-v3
num_battles: 145665
num_wins: 73124
celo_rating: 1160.08
propriety_score: 0.0
propriety_total_count: 0.0
submission_type: basic
model_architecture: MistralForCausalLM
model_num_parameters: 7241732096.0
best_of: 8
max_input_tokens: 1024
max_output_tokens: 64
display_name: anhnv125-mistral-v3_v11
ineligible_reason: propriety_total_count < 800
language_model: anhnv125/mistral-v3
model_size: 7B
reward_model: anhnv125/reward-model-vm
us_pacific_date: 2024-04-05
win_ratio: 0.5020011670614081
preference_data_url: None
Resubmit model
Running pipeline stage MKMLizer
Starting job with name anhnv125-mistral-v3-v11-mkmlizer
Waiting for job on anhnv125-mistral-v3-v11-mkmlizer to finish
anhnv125-mistral-v3-v11-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
anhnv125-mistral-v3-v11-mkmlizer: ║ _____ __ __ ║
anhnv125-mistral-v3-v11-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
anhnv125-mistral-v3-v11-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
anhnv125-mistral-v3-v11-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
anhnv125-mistral-v3-v11-mkmlizer: ║ /___/ ║
anhnv125-mistral-v3-v11-mkmlizer: ║ ║
anhnv125-mistral-v3-v11-mkmlizer: ║ Version: 0.6.11 ║
anhnv125-mistral-v3-v11-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
anhnv125-mistral-v3-v11-mkmlizer: ║ ║
anhnv125-mistral-v3-v11-mkmlizer: ║ The license key for the current software has been verified as ║
anhnv125-mistral-v3-v11-mkmlizer: ║ belonging to: ║
anhnv125-mistral-v3-v11-mkmlizer: ║ ║
anhnv125-mistral-v3-v11-mkmlizer: ║ Chai Research Corp. ║
anhnv125-mistral-v3-v11-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
anhnv125-mistral-v3-v11-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
anhnv125-mistral-v3-v11-mkmlizer: ║ ║
anhnv125-mistral-v3-v11-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
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anhnv125-mistral-v3-v11-mkmlizer: Downloaded to shared memory in 10.091s
anhnv125-mistral-v3-v11-mkmlizer: quantizing model to /dev/shm/model_cache
anhnv125-mistral-v3-v11-mkmlizer: Saving mkml model at /dev/shm/model_cache
anhnv125-mistral-v3-v11-mkmlizer: Reading /tmp/tmpe3l22dv3/pytorch_model.bin.index.json
anhnv125-mistral-v3-v11-mkmlizer: Profiling: 0%| | 0/291 [00:00<?, ?it/s] Profiling: 0%| | 1/291 [00:01<09:23, 1.94s/it] Profiling: 34%|███▎ | 98/291 [00:02<00:04, 45.84it/s] Profiling: 70%|███████ | 204/291 [00:03<00:01, 81.37it/s] Profiling: 100%|██████████| 291/291 [00:04<00:00, 75.42it/s] Profiling: 100%|██████████| 291/291 [00:04<00:00, 62.75it/s]
anhnv125-mistral-v3-v11-mkmlizer: quantized model in 14.753s
anhnv125-mistral-v3-v11-mkmlizer: Processed model anhnv125/mistral-v3 in 25.718s
anhnv125-mistral-v3-v11-mkmlizer: creating bucket guanaco-mkml-models
anhnv125-mistral-v3-v11-mkmlizer: cp /dev/shm/model_cache/mkml_model.tensors s3://guanaco-mkml-models/anhnv125-mistral-v3-v11/mkml_model.tensors
anhnv125-mistral-v3-v11-mkmlizer: loading reward model from anhnv125/reward-model-vm
anhnv125-mistral-v3-v11-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-mistral-v3-v11-mkmlizer: warnings.warn(
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anhnv125-mistral-v3-v11-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-mistral-v3-v11-mkmlizer: warnings.warn(
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anhnv125-mistral-v3-v11-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-mistral-v3-v11-mkmlizer: warnings.warn(
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anhnv125-mistral-v3-v11-mkmlizer: model-00001-of-00001.safetensors: 41%|████ | 102M/249M [00:00<00:00, 162MB/s] 
anhnv125-mistral-v3-v11-mkmlizer: model-00001-of-00001.safetensors: 87%|████████▋ | 217M/249M [00:01<00:00, 327MB/s] model-00001-of-00001.safetensors: 100%|█████████▉| 249M/249M [00:01<00:00, 200MB/s]
anhnv125-mistral-v3-v11-mkmlizer: Downloading shards: 100%|██████████| 1/1 [00:02<00:00, 2.07s/it] Downloading shards: 100%|██████████| 1/1 [00:02<00:00, 2.07s/it]
anhnv125-mistral-v3-v11-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
anhnv125-mistral-v3-v11-mkmlizer: Saving duration: 0.082s
anhnv125-mistral-v3-v11-mkmlizer: Processed model anhnv125/reward-model-vm in 4.288s
anhnv125-mistral-v3-v11-mkmlizer: creating bucket guanaco-reward-models
anhnv125-mistral-v3-v11-mkmlizer: Bucket 's3://guanaco-reward-models/' created
anhnv125-mistral-v3-v11-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/anhnv125-mistral-v3-v11_reward
anhnv125-mistral-v3-v11-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/anhnv125-mistral-v3-v11_reward/config.json
anhnv125-mistral-v3-v11-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/anhnv125-mistral-v3-v11_reward/tokenizer_config.json
anhnv125-mistral-v3-v11-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/anhnv125-mistral-v3-v11_reward/special_tokens_map.json
anhnv125-mistral-v3-v11-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/anhnv125-mistral-v3-v11_reward/vocab.json
anhnv125-mistral-v3-v11-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/anhnv125-mistral-v3-v11_reward/merges.txt
anhnv125-mistral-v3-v11-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/anhnv125-mistral-v3-v11_reward/tokenizer.json
anhnv125-mistral-v3-v11-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/anhnv125-mistral-v3-v11_reward/reward.tensors
Job anhnv125-mistral-v3-v11-mkmlizer completed after 53.66s with status: succeeded
Stopping job with name anhnv125-mistral-v3-v11-mkmlizer
Pipeline stage MKMLizer completed in 57.85s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.12s
Running pipeline stage ISVCDeployer
Creating inference service anhnv125-mistral-v3-v11
Waiting for inference service anhnv125-mistral-v3-v11 to be ready
Inference service anhnv125-mistral-v3-v11 ready after 50.27264213562012s
Pipeline stage ISVCDeployer completed in 58.32s
Running pipeline stage StressChecker
Received healthy response to inference request in 1.7302827835083008s
Received healthy response to inference request in 1.199674367904663s
Received healthy response to inference request in 1.228893518447876s
Received healthy response to inference request in 1.2223069667816162s
Received healthy response to inference request in 1.202040195465088s
5 requests
0 failed requests
5th percentile: 1.200147533416748
10th percentile: 1.200620698928833
20th percentile: 1.201567029953003
30th percentile: 1.2060935497283936
40th percentile: 1.2142002582550049
50th percentile: 1.2223069667816162
60th percentile: 1.2249415874481202
70th percentile: 1.227576208114624
80th percentile: 1.3291713714599611
90th percentile: 1.529727077484131
95th percentile: 1.6300049304962156
99th percentile: 1.7102272129058838
mean time: 1.3166395664215087
Pipeline stage StressChecker completed in 7.39s
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 0.04s
M-Eval Dataset for topic stay_in_character is loaded
anhnv125-mistral-v3_v11 status is now deployed due to DeploymentManager action
anhnv125-mistral-v3_v11 status is now inactive due to auto deactivation removed underperforming models
admin requested tearing down of anhnv125-mistral-v3_v11
Running pipeline stage ISVCDeleter
Checking if service anhnv125-mistral-v3-v11 is running
Tearing down inference service anhnv125-mistral-v3-v11
Toredown service anhnv125-mistral-v3-v11
Pipeline stage ISVCDeleter completed in 7.14s
Running pipeline stage MKMLModelDeleter
Cleaning model data from S3
Cleaning model data from model cache
Deleting key anhnv125-mistral-v3-v11/config.json from bucket guanaco-mkml-models
Deleting key anhnv125-mistral-v3-v11/mkml_model.tensors from bucket guanaco-mkml-models
Deleting key anhnv125-mistral-v3-v11/special_tokens_map.json from bucket guanaco-mkml-models
Deleting key anhnv125-mistral-v3-v11/tokenizer.json from bucket guanaco-mkml-models
Deleting key anhnv125-mistral-v3-v11/tokenizer.model from bucket guanaco-mkml-models
Deleting key anhnv125-mistral-v3-v11/tokenizer_config.json from bucket guanaco-mkml-models
Cleaning model data from model cache
Deleting key anhnv125-mistral-v3-v11_reward/config.json from bucket guanaco-reward-models
Deleting key anhnv125-mistral-v3-v11_reward/merges.txt from bucket guanaco-reward-models
Deleting key anhnv125-mistral-v3-v11_reward/reward.tensors from bucket guanaco-reward-models
Deleting key anhnv125-mistral-v3-v11_reward/special_tokens_map.json from bucket guanaco-reward-models
Deleting key anhnv125-mistral-v3-v11_reward/tokenizer.json from bucket guanaco-reward-models
Deleting key anhnv125-mistral-v3-v11_reward/tokenizer_config.json from bucket guanaco-reward-models
Deleting key anhnv125-mistral-v3-v11_reward/vocab.json from bucket guanaco-reward-models
Pipeline stage MKMLModelDeleter completed in 2.55s
anhnv125-mistral-v3_v11 status is now torndown due to DeploymentManager action
admin requested tearing down of anhnv125-mistral-v3_v11
Running pipeline stage ISVCDeleter
Pipeline stage %s skipped, reason=%s
Pipeline stage ISVCDeleter completed in 0.09s
Running pipeline stage MKMLModelDeleter
Pipeline stage %s skipped, reason=%s
Pipeline stage MKMLModelDeleter completed in 0.07s
anhnv125-mistral-v3_v11 status is now torndown due to DeploymentManager action

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