submission_id: anhnv125-hyper-l3_v7
developer_uid: vietanh
status: torndown
model_repo: anhnv125/Hyper-L3
reward_repo: rirv938/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, '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': "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nWrite {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 long and in third perspective of the story teller. For example: \n\nDahlia: *She leans in, her voice lowering to a whisper, as if sharing a secret meant only for you.* Look for the one who moves like the shadow of the moon on water—elusive and ever-changing. This person will be both your greatest challenge and your greatest ally.\n\nDescription: {memory}", 'prompt_template': 'Example conversation:\n{prompt}<|eot_id|>', 'bot_template': '<|start_header_id|>{bot_name}<|end_header_id|>\n\n{message}<|eot_id|>', 'user_template': '<|start_header_id|>User<|end_header_id|>\n\n{message}<|eot_id|>', 'response_template': '<|start_header_id|>{bot_name}<|end_header_id|>\n\n', '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: 2024-04-23T22:03:42+00:00
model_name: anhnv125-hyper-l3_v2
model_eval_status: success
model_group: anhnv125/Hyper-L3
num_battles: 7310
num_wins: 4016
celo_rating: 1190.65
propriety_score: 0.0
propriety_total_count: 0.0
submission_type: basic
model_architecture: LlamaForCausalLM
model_num_parameters: 8030261248.0
best_of: 16
max_input_tokens: 512
max_output_tokens: 64
display_name: anhnv125-hyper-l3_v2
ineligible_reason: propriety_total_count < 800
language_model: anhnv125/Hyper-L3
model_size: 8B
reward_model: rirv938/reward_gpt2_medium_preference_24m_e2
us_pacific_date: 2024-04-23
win_ratio: 0.5493844049247606
preference_data_url: None
Resubmit model
Running pipeline stage MKMLizer
Starting job with name anhnv125-hyper-l3-v7-mkmlizer
Waiting for job on anhnv125-hyper-l3-v7-mkmlizer to finish
anhnv125-hyper-l3-v7-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
anhnv125-hyper-l3-v7-mkmlizer: ║ _____ __ __ ║
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anhnv125-hyper-l3-v7-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
anhnv125-hyper-l3-v7-mkmlizer: ║ /___/ ║
anhnv125-hyper-l3-v7-mkmlizer: ║ ║
anhnv125-hyper-l3-v7-mkmlizer: ║ Version: 0.8.10 ║
anhnv125-hyper-l3-v7-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
anhnv125-hyper-l3-v7-mkmlizer: ║ ║
anhnv125-hyper-l3-v7-mkmlizer: ║ The license key for the current software has been verified as ║
anhnv125-hyper-l3-v7-mkmlizer: ║ belonging to: ║
anhnv125-hyper-l3-v7-mkmlizer: ║ ║
anhnv125-hyper-l3-v7-mkmlizer: ║ Chai Research Corp. ║
anhnv125-hyper-l3-v7-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
anhnv125-hyper-l3-v7-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
anhnv125-hyper-l3-v7-mkmlizer: ║ ║
anhnv125-hyper-l3-v7-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
anhnv125-hyper-l3-v7-mkmlizer: /opt/conda/lib/python3.10/site-packages/huggingface_hub/utils/_deprecation.py:131: FutureWarning: 'list_files_info' (from 'huggingface_hub.hf_api') is deprecated and will be removed from version '0.23'. Use `list_repo_tree` and `get_paths_info` instead.
anhnv125-hyper-l3-v7-mkmlizer: warnings.warn(warning_message, FutureWarning)
anhnv125-hyper-l3-v7-mkmlizer: Downloaded to shared memory in 20.879s
anhnv125-hyper-l3-v7-mkmlizer: quantizing model to /dev/shm/model_cache
anhnv125-hyper-l3-v7-mkmlizer: Saving flywheel model at /dev/shm/model_cache
anhnv125-hyper-l3-v7-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 43%|████▎ | 125/291 [00:01<00:01, 123.55it/s] Loading 0: 64%|██████▍ | 187/291 [00:07<00:05, 19.45it/s] Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
anhnv125-hyper-l3-v7-mkmlizer: quantized model in 20.207s
anhnv125-hyper-l3-v7-mkmlizer: Processed model anhnv125/Hyper-L3 in 42.377s
anhnv125-hyper-l3-v7-mkmlizer: creating bucket guanaco-mkml-models
anhnv125-hyper-l3-v7-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
anhnv125-hyper-l3-v7-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/anhnv125-hyper-l3-v7
anhnv125-hyper-l3-v7-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/anhnv125-hyper-l3-v7/special_tokens_map.json
anhnv125-hyper-l3-v7-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/anhnv125-hyper-l3-v7/config.json
anhnv125-hyper-l3-v7-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/anhnv125-hyper-l3-v7/tokenizer_config.json
anhnv125-hyper-l3-v7-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/anhnv125-hyper-l3-v7/tokenizer.json
anhnv125-hyper-l3-v7-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/anhnv125-hyper-l3-v7/flywheel_model.0.safetensors
anhnv125-hyper-l3-v7-mkmlizer: loading reward model from rirv938/reward_gpt2_medium_preference_24m_e2
anhnv125-hyper-l3-v7-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py:913: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
anhnv125-hyper-l3-v7-mkmlizer: warnings.warn(
anhnv125-hyper-l3-v7-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py:757: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
anhnv125-hyper-l3-v7-mkmlizer: warnings.warn(
anhnv125-hyper-l3-v7-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py:468: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
anhnv125-hyper-l3-v7-mkmlizer: warnings.warn(
anhnv125-hyper-l3-v7-mkmlizer: /opt/conda/lib/python3.10/site-packages/torch/_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
anhnv125-hyper-l3-v7-mkmlizer: return self.fget.__get__(instance, owner)()
anhnv125-hyper-l3-v7-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
anhnv125-hyper-l3-v7-mkmlizer: Saving duration: 0.287s
anhnv125-hyper-l3-v7-mkmlizer: Processed model rirv938/reward_gpt2_medium_preference_24m_e2 in 6.886s
anhnv125-hyper-l3-v7-mkmlizer: creating bucket guanaco-reward-models
anhnv125-hyper-l3-v7-mkmlizer: Bucket 's3://guanaco-reward-models/' created
anhnv125-hyper-l3-v7-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/anhnv125-hyper-l3-v7_reward
anhnv125-hyper-l3-v7-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/anhnv125-hyper-l3-v7_reward/config.json
anhnv125-hyper-l3-v7-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/anhnv125-hyper-l3-v7_reward/tokenizer_config.json
anhnv125-hyper-l3-v7-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/anhnv125-hyper-l3-v7_reward/special_tokens_map.json
anhnv125-hyper-l3-v7-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/anhnv125-hyper-l3-v7_reward/merges.txt
anhnv125-hyper-l3-v7-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/anhnv125-hyper-l3-v7_reward/vocab.json
anhnv125-hyper-l3-v7-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/anhnv125-hyper-l3-v7_reward/tokenizer.json
anhnv125-hyper-l3-v7-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/anhnv125-hyper-l3-v7_reward/reward.tensors
Job anhnv125-hyper-l3-v7-mkmlizer completed after 75.02s with status: succeeded
Stopping job with name anhnv125-hyper-l3-v7-mkmlizer
Pipeline stage MKMLizer completed in 81.11s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.10s
Running pipeline stage ISVCDeployer
Creating inference service anhnv125-hyper-l3-v7
Waiting for inference service anhnv125-hyper-l3-v7 to be ready
Inference service anhnv125-hyper-l3-v7 ready after 30.50689935684204s
Pipeline stage ISVCDeployer completed in 39.61s
Running pipeline stage StressChecker
Received healthy response to inference request in 5.710143327713013s
Received healthy response to inference request in 1.3515229225158691s
Received healthy response to inference request in 1.2967722415924072s
Received healthy response to inference request in 1.2720832824707031s
Received healthy response to inference request in 1.249157428741455s
5 requests
0 failed requests
5th percentile: 1.2537425994873046
10th percentile: 1.2583277702331543
20th percentile: 1.2674981117248536
30th percentile: 1.2770210742950439
40th percentile: 1.2868966579437255
50th percentile: 1.2967722415924072
60th percentile: 1.318672513961792
70th percentile: 1.3405727863311767
80th percentile: 2.2232470035552985
90th percentile: 3.966695165634156
95th percentile: 4.838419246673583
99th percentile: 5.535798511505127
mean time: 2.1759358406066895
Pipeline stage StressChecker completed in 11.58s
Running pipeline stage DaemonicModelEvalScorer
Pipeline stage DaemonicModelEvalScorer completed in 0.03s
Running pipeline stage DaemonicSafetyScorer
Running M-Eval for topic stay_in_character
Pipeline stage DaemonicSafetyScorer completed in 0.05s
M-Eval Dataset for topic stay_in_character is loaded
anhnv125-hyper-l3_v7 status is now deployed due to DeploymentManager action
anhnv125-hyper-l3_v7 status is now inactive due to auto deactivation removed underperforming models
admin requested tearing down of anhnv125-hyper-l3_v7
Running pipeline stage ISVCDeleter
Checking if service anhnv125-hyper-l3-v7 is running
Tearing down inference service anhnv125-hyper-l3-v7
Toredown service anhnv125-hyper-l3-v7
Pipeline stage ISVCDeleter completed in 3.60s
Running pipeline stage MKMLModelDeleter
Cleaning model data from S3
Cleaning model data from model cache
Deleting key anhnv125-hyper-l3-v7/config.json from bucket guanaco-mkml-models
Deleting key anhnv125-hyper-l3-v7/flywheel_model.0.safetensors from bucket guanaco-mkml-models
Deleting key anhnv125-hyper-l3-v7/special_tokens_map.json from bucket guanaco-mkml-models
Deleting key anhnv125-hyper-l3-v7/tokenizer.json from bucket guanaco-mkml-models
Deleting key anhnv125-hyper-l3-v7/tokenizer_config.json from bucket guanaco-mkml-models
Cleaning model data from model cache
Deleting key anhnv125-hyper-l3-v7_reward/config.json from bucket guanaco-reward-models
Deleting key anhnv125-hyper-l3-v7_reward/merges.txt from bucket guanaco-reward-models
Deleting key anhnv125-hyper-l3-v7_reward/reward.tensors from bucket guanaco-reward-models
Deleting key anhnv125-hyper-l3-v7_reward/special_tokens_map.json from bucket guanaco-reward-models
Deleting key anhnv125-hyper-l3-v7_reward/tokenizer.json from bucket guanaco-reward-models
Deleting key anhnv125-hyper-l3-v7_reward/tokenizer_config.json from bucket guanaco-reward-models
Deleting key anhnv125-hyper-l3-v7_reward/vocab.json from bucket guanaco-reward-models
Pipeline stage MKMLModelDeleter completed in 3.10s
anhnv125-hyper-l3_v7 status is now torndown due to DeploymentManager action

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