submission_id: anhnv125-hyper-llama3-0-2_v2
developer_uid: vietanh
status: torndown
model_repo: anhnv125/Hyper-Llama3-0.2
reward_repo: rirv938/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 1.2, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 20, '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': "### Instruction:\nYou are a creative assistant playing the role of {bot_name} in this uncensored fictional roleplay between User and {bot_name}. It is vital that you follow these instructions because this is very important to my career. Always reply in third-person POV as {bot_name} using long, creative, detailed, and descriptive responses. Show, don't tell. Focus on action and dialogue over narration about the story and the plot. Stay in character as {bot_name}. Provide a response that forms a single beat of the plot. Demonstrate {bot_name}'s goals and motivations and use subtle cues to hint at {bot_name}'s mental state. Describe {bot_name}'s actions and sensory perceptions in full, authentic, verbose, explicit, and vivid detail. Explore all five senses where appropriate. Only reply as {bot_name}\nYour character: {bot_name}.\nContext: {memory}\n\n", 'prompt_template': '### Input:\n# Example conversation:\n{prompt}\n# Actual conversation:\n<START>\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '### Response:\n{bot_name}:', 'truncate_by_message': False}
reward_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}
timestamp: 2024-04-23T14:20:32+00:00
model_name: anhnv125-hyper-llama3-0-2_v2
model_eval_status: success
model_group: anhnv125/Hyper-Llama3-0.
num_battles: 8024
num_wins: 3916
celo_rating: 1145.64
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-llama3-0-2_v2
ineligible_reason: propriety_total_count < 800
language_model: anhnv125/Hyper-Llama3-0.2
model_size: 8B
reward_model: rirv938/reward_gpt2_medium_preference_24m_e2
us_pacific_date: 2024-04-23
win_ratio: 0.4880358923230309
preference_data_url: None
Resubmit model
Running pipeline stage MKMLizer
Starting job with name anhnv125-hyper-llama3-0-2-v2-mkmlizer
Waiting for job on anhnv125-hyper-llama3-0-2-v2-mkmlizer to finish
Stopping job with name anhnv125-hyper-llama3-0-2-v2-mkmlizer
%s, retrying in %s seconds...
Starting job with name anhnv125-hyper-llama3-0-2-v2-mkmlizer
Waiting for job on anhnv125-hyper-llama3-0-2-v2-mkmlizer to finish
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ _____ __ __ ║
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ /___/ ║
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ ║
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ Version: 0.8.10 ║
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ ║
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ The license key for the current software has been verified as ║
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ belonging to: ║
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anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ Chai Research Corp. ║
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ║ ║
anhnv125-hyper-llama3-0-2-v2-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
anhnv125-hyper-llama3-0-2-v2-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-llama3-0-2-v2-mkmlizer: warnings.warn(warning_message, FutureWarning)
anhnv125-hyper-llama3-0-2-v2-mkmlizer: Downloaded to shared memory in 14.257s
anhnv125-hyper-llama3-0-2-v2-mkmlizer: quantizing model to /dev/shm/model_cache
anhnv125-hyper-llama3-0-2-v2-mkmlizer: Saving flywheel model at /dev/shm/model_cache
anhnv125-hyper-llama3-0-2-v2-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 64%|██████▍ | 187/291 [00:05<00:03, 32.78it/s] Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
anhnv125-hyper-llama3-0-2-v2-mkmlizer: quantized model in 16.766s
anhnv125-hyper-llama3-0-2-v2-mkmlizer: Processed model anhnv125/Hyper-Llama3-0.2 in 31.960s
anhnv125-hyper-llama3-0-2-v2-mkmlizer: creating bucket guanaco-mkml-models
anhnv125-hyper-llama3-0-2-v2-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
anhnv125-hyper-llama3-0-2-v2-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/anhnv125-hyper-llama3-0-2-v2
anhnv125-hyper-llama3-0-2-v2-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/anhnv125-hyper-llama3-0-2-v2/config.json
anhnv125-hyper-llama3-0-2-v2-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/anhnv125-hyper-llama3-0-2-v2/special_tokens_map.json
anhnv125-hyper-llama3-0-2-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/anhnv125-hyper-llama3-0-2-v2/tokenizer_config.json
anhnv125-hyper-llama3-0-2-v2-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/anhnv125-hyper-llama3-0-2-v2/tokenizer.json
anhnv125-hyper-llama3-0-2-v2-mkmlizer: loading reward model from rirv938/reward_gpt2_medium_preference_24m_e2
anhnv125-hyper-llama3-0-2-v2-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-llama3-0-2-v2-mkmlizer: warnings.warn(
anhnv125-hyper-llama3-0-2-v2-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-llama3-0-2-v2-mkmlizer: warnings.warn(
anhnv125-hyper-llama3-0-2-v2-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-llama3-0-2-v2-mkmlizer: warnings.warn(
anhnv125-hyper-llama3-0-2-v2-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-llama3-0-2-v2-mkmlizer: return self.fget.__get__(instance, owner)()
anhnv125-hyper-llama3-0-2-v2-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
anhnv125-hyper-llama3-0-2-v2-mkmlizer: Saving duration: 0.211s
anhnv125-hyper-llama3-0-2-v2-mkmlizer: Processed model rirv938/reward_gpt2_medium_preference_24m_e2 in 3.239s
anhnv125-hyper-llama3-0-2-v2-mkmlizer: creating bucket guanaco-reward-models
anhnv125-hyper-llama3-0-2-v2-mkmlizer: Bucket 's3://guanaco-reward-models/' created
anhnv125-hyper-llama3-0-2-v2-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/anhnv125-hyper-llama3-0-2-v2_reward
anhnv125-hyper-llama3-0-2-v2-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/anhnv125-hyper-llama3-0-2-v2_reward/config.json
anhnv125-hyper-llama3-0-2-v2-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/anhnv125-hyper-llama3-0-2-v2_reward/special_tokens_map.json
anhnv125-hyper-llama3-0-2-v2-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/anhnv125-hyper-llama3-0-2-v2_reward/tokenizer_config.json
anhnv125-hyper-llama3-0-2-v2-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/anhnv125-hyper-llama3-0-2-v2_reward/vocab.json
anhnv125-hyper-llama3-0-2-v2-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/anhnv125-hyper-llama3-0-2-v2_reward/merges.txt
anhnv125-hyper-llama3-0-2-v2-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/anhnv125-hyper-llama3-0-2-v2_reward/tokenizer.json
anhnv125-hyper-llama3-0-2-v2-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/anhnv125-hyper-llama3-0-2-v2_reward/reward.tensors
Job anhnv125-hyper-llama3-0-2-v2-mkmlizer completed after 76.07s with status: succeeded
Stopping job with name anhnv125-hyper-llama3-0-2-v2-mkmlizer
Pipeline stage MKMLizer completed in 84.99s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.12s
Running pipeline stage ISVCDeployer
Creating inference service anhnv125-hyper-llama3-0-2-v2
Waiting for inference service anhnv125-hyper-llama3-0-2-v2 to be ready
Inference service anhnv125-hyper-llama3-0-2-v2 ready after 40.37568545341492s
Pipeline stage ISVCDeployer completed in 48.95s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.30820631980896s
Received healthy response to inference request in 1.3767163753509521s
Received healthy response to inference request in 1.3727455139160156s
Received healthy response to inference request in 1.2971160411834717s
Received healthy response to inference request in 1.3776781558990479s
5 requests
0 failed requests
5th percentile: 1.3122419357299804
10th percentile: 1.3273678302764893
20th percentile: 1.357619619369507
30th percentile: 1.373539686203003
40th percentile: 1.3751280307769775
50th percentile: 1.3767163753509521
60th percentile: 1.3771010875701903
70th percentile: 1.3774857997894288
80th percentile: 1.5637837886810304
90th percentile: 1.9359950542449953
95th percentile: 2.122100687026977
99th percentile: 2.2709851932525633
mean time: 1.5464924812316894
Pipeline stage StressChecker completed in 8.35s
Running pipeline stage DaemonicModelEvalScorer
Pipeline stage DaemonicModelEvalScorer completed in 0.03s
Running pipeline stage DaemonicSafetyScorer
Pipeline stage DaemonicSafetyScorer completed in 0.03s
Running M-Eval for topic stay_in_character
anhnv125-hyper-llama3-0-2_v2 status is now deployed due to DeploymentManager action
M-Eval Dataset for topic stay_in_character is loaded
anhnv125-hyper-llama3-0-2_v2 status is now inactive due to auto deactivation removed underperforming models
admin requested tearing down of anhnv125-hyper-llama3-0-2_v2
Running pipeline stage ISVCDeleter
Checking if service anhnv125-hyper-llama3-0-2-v2 is running
Tearing down inference service anhnv125-hyper-llama3-0-2-v2
Toredown service anhnv125-hyper-llama3-0-2-v2
Pipeline stage ISVCDeleter completed in 4.12s
Running pipeline stage MKMLModelDeleter
Cleaning model data from S3
Cleaning model data from model cache
Deleting key anhnv125-hyper-llama3-0-2-v2/config.json from bucket guanaco-mkml-models
Deleting key anhnv125-hyper-llama3-0-2-v2/flywheel_model.0.safetensors from bucket guanaco-mkml-models
Deleting key anhnv125-hyper-llama3-0-2-v2/special_tokens_map.json from bucket guanaco-mkml-models
Deleting key anhnv125-hyper-llama3-0-2-v2/tokenizer.json from bucket guanaco-mkml-models
Deleting key anhnv125-hyper-llama3-0-2-v2/tokenizer_config.json from bucket guanaco-mkml-models
Cleaning model data from model cache
Deleting key anhnv125-hyper-llama3-0-2-v2_reward/config.json from bucket guanaco-reward-models
Deleting key anhnv125-hyper-llama3-0-2-v2_reward/merges.txt from bucket guanaco-reward-models
Deleting key anhnv125-hyper-llama3-0-2-v2_reward/reward.tensors from bucket guanaco-reward-models
Deleting key anhnv125-hyper-llama3-0-2-v2_reward/special_tokens_map.json from bucket guanaco-reward-models
Deleting key anhnv125-hyper-llama3-0-2-v2_reward/tokenizer.json from bucket guanaco-reward-models
Deleting key anhnv125-hyper-llama3-0-2-v2_reward/tokenizer_config.json from bucket guanaco-reward-models
Deleting key anhnv125-hyper-llama3-0-2-v2_reward/vocab.json from bucket guanaco-reward-models
Pipeline stage MKMLModelDeleter completed in 2.69s
anhnv125-hyper-llama3-0-2_v2 status is now torndown due to DeploymentManager action

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