submission_id: anhnv125-hyper-l3_v6
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: 2024-04-23T14:43:43+00:00
model_name: anhnv125-hyper-l3_v2
model_eval_status: success
model_group: anhnv125/Hyper-L3
num_battles: 6270
num_wins: 3481
celo_rating: 1191.22
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: 0.5551834130781499
preference_data_url: None
Resubmit model
Running pipeline stage MKMLizer
Starting job with name anhnv125-hyper-l3-v6-mkmlizer
Waiting for job on anhnv125-hyper-l3-v6-mkmlizer to finish
Stopping job with name anhnv125-hyper-l3-v6-mkmlizer
%s, retrying in %s seconds...
Starting job with name anhnv125-hyper-l3-v6-mkmlizer
Waiting for job on anhnv125-hyper-l3-v6-mkmlizer to finish
anhnv125-hyper-l3-v6-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
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anhnv125-hyper-l3-v6-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
anhnv125-hyper-l3-v6-mkmlizer: ║ /___/ ║
anhnv125-hyper-l3-v6-mkmlizer: ║ ║
anhnv125-hyper-l3-v6-mkmlizer: ║ Version: 0.8.10 ║
anhnv125-hyper-l3-v6-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
anhnv125-hyper-l3-v6-mkmlizer: ║ ║
anhnv125-hyper-l3-v6-mkmlizer: ║ The license key for the current software has been verified as ║
anhnv125-hyper-l3-v6-mkmlizer: ║ belonging to: ║
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anhnv125-hyper-l3-v6-mkmlizer: ║ Chai Research Corp. ║
anhnv125-hyper-l3-v6-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
anhnv125-hyper-l3-v6-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
anhnv125-hyper-l3-v6-mkmlizer: ║ ║
anhnv125-hyper-l3-v6-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
anhnv125-hyper-l3-v6-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-v6-mkmlizer: warnings.warn(warning_message, FutureWarning)
anhnv125-hyper-l3-v6-mkmlizer: Downloaded to shared memory in 14.523s
anhnv125-hyper-l3-v6-mkmlizer: quantizing model to /dev/shm/model_cache
anhnv125-hyper-l3-v6-mkmlizer: Saving flywheel model at /dev/shm/model_cache
anhnv125-hyper-l3-v6-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 36%|███▌ | 104/291 [00:01<00:01, 103.00it/s] Loading 0: 64%|██████▍ | 187/291 [00:07<00:04, 21.62it/s] Loading 0: 99%|█████████▉| 289/291 [00:08<00:00, 34.90it/s] Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
anhnv125-hyper-l3-v6-mkmlizer: quantized model in 20.712s
anhnv125-hyper-l3-v6-mkmlizer: Processed model anhnv125/Hyper-L3 in 36.464s
anhnv125-hyper-l3-v6-mkmlizer: creating bucket guanaco-mkml-models
anhnv125-hyper-l3-v6-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
anhnv125-hyper-l3-v6-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/anhnv125-hyper-l3-v6
anhnv125-hyper-l3-v6-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/anhnv125-hyper-l3-v6/config.json
anhnv125-hyper-l3-v6-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/anhnv125-hyper-l3-v6/tokenizer_config.json
anhnv125-hyper-l3-v6-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/anhnv125-hyper-l3-v6/special_tokens_map.json
anhnv125-hyper-l3-v6-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/anhnv125-hyper-l3-v6/tokenizer.json
anhnv125-hyper-l3-v6-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/anhnv125-hyper-l3-v6/flywheel_model.0.safetensors
anhnv125-hyper-l3-v6-mkmlizer: loading reward model from rirv938/reward_gpt2_medium_preference_24m_e2
anhnv125-hyper-l3-v6-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-v6-mkmlizer: warnings.warn(
anhnv125-hyper-l3-v6-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-v6-mkmlizer: warnings.warn(
anhnv125-hyper-l3-v6-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-v6-mkmlizer: warnings.warn(
anhnv125-hyper-l3-v6-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-v6-mkmlizer: return self.fget.__get__(instance, owner)()
anhnv125-hyper-l3-v6-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
anhnv125-hyper-l3-v6-mkmlizer: Saving duration: 0.249s
anhnv125-hyper-l3-v6-mkmlizer: Processed model rirv938/reward_gpt2_medium_preference_24m_e2 in 5.993s
anhnv125-hyper-l3-v6-mkmlizer: creating bucket guanaco-reward-models
anhnv125-hyper-l3-v6-mkmlizer: Bucket 's3://guanaco-reward-models/' created
anhnv125-hyper-l3-v6-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/anhnv125-hyper-l3-v6_reward
anhnv125-hyper-l3-v6-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/anhnv125-hyper-l3-v6_reward/special_tokens_map.json
anhnv125-hyper-l3-v6-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/anhnv125-hyper-l3-v6_reward/tokenizer_config.json
anhnv125-hyper-l3-v6-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/anhnv125-hyper-l3-v6_reward/config.json
anhnv125-hyper-l3-v6-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/anhnv125-hyper-l3-v6_reward/merges.txt
anhnv125-hyper-l3-v6-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/anhnv125-hyper-l3-v6_reward/vocab.json
anhnv125-hyper-l3-v6-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/anhnv125-hyper-l3-v6_reward/tokenizer.json
Job anhnv125-hyper-l3-v6-mkmlizer completed after 105.85s with status: succeeded
Stopping job with name anhnv125-hyper-l3-v6-mkmlizer
Pipeline stage MKMLizer completed in 111.64s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.30s
Running pipeline stage ISVCDeployer
Creating inference service anhnv125-hyper-l3-v6
Waiting for inference service anhnv125-hyper-l3-v6 to be ready
Inference service anhnv125-hyper-l3-v6 ready after 30.18705701828003s
Pipeline stage ISVCDeployer completed in 39.32s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.1596169471740723s
Received healthy response to inference request in 1.3648617267608643s
Received healthy response to inference request in 1.3207581043243408s
Received healthy response to inference request in 1.37184739112854s
Received healthy response to inference request in 1.3000900745391846s
5 requests
0 failed requests
5th percentile: 1.3042236804962157
10th percentile: 1.3083572864532471
20th percentile: 1.3166244983673097
30th percentile: 1.3295788288116455
40th percentile: 1.347220277786255
50th percentile: 1.3648617267608643
60th percentile: 1.3676559925079346
70th percentile: 1.3704502582550049
80th percentile: 1.5294013023376467
90th percentile: 1.8445091247558594
95th percentile: 2.002063035964966
99th percentile: 2.128106164932251
mean time: 1.5034348487854003
Pipeline stage StressChecker completed in 8.55s
Running pipeline stage DaemonicModelEvalScorer
Pipeline stage DaemonicModelEvalScorer completed in 0.06s
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
anhnv125-hyper-l3_v6 status is now deployed due to DeploymentManager action
anhnv125-hyper-l3_v6 status is now inactive due to auto deactivation removed underperforming models
admin requested tearing down of anhnv125-hyper-l3_v6
Running pipeline stage ISVCDeleter
Checking if service anhnv125-hyper-l3-v6 is running
Tearing down inference service anhnv125-hyper-l3-v6
Toredown service anhnv125-hyper-l3-v6
Pipeline stage ISVCDeleter completed in 3.96s
Running pipeline stage MKMLModelDeleter
Cleaning model data from S3
Cleaning model data from model cache
Deleting key anhnv125-hyper-l3-v6/config.json from bucket guanaco-mkml-models
Deleting key anhnv125-hyper-l3-v6/flywheel_model.0.safetensors from bucket guanaco-mkml-models
Deleting key anhnv125-hyper-l3-v6/special_tokens_map.json from bucket guanaco-mkml-models
Deleting key anhnv125-hyper-l3-v6/tokenizer.json from bucket guanaco-mkml-models
Deleting key anhnv125-hyper-l3-v6/tokenizer_config.json from bucket guanaco-mkml-models
Cleaning model data from model cache
Deleting key anhnv125-hyper-l3-v6_reward/config.json from bucket guanaco-reward-models
Deleting key anhnv125-hyper-l3-v6_reward/merges.txt from bucket guanaco-reward-models
Deleting key anhnv125-hyper-l3-v6_reward/reward.tensors from bucket guanaco-reward-models
Deleting key anhnv125-hyper-l3-v6_reward/special_tokens_map.json from bucket guanaco-reward-models
Deleting key anhnv125-hyper-l3-v6_reward/tokenizer.json from bucket guanaco-reward-models
Deleting key anhnv125-hyper-l3-v6_reward/tokenizer_config.json from bucket guanaco-reward-models
Deleting key anhnv125-hyper-l3-v6_reward/vocab.json from bucket guanaco-reward-models
Pipeline stage MKMLModelDeleter completed in 2.39s
anhnv125-hyper-l3_v6 status is now torndown due to DeploymentManager action

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