submission_id: meseca-20062024-c1_v1
developer_uid: nguyenzzz
status: inactive
model_repo: meseca/20062024-c1
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 0.95, 'top_p': 1.0, 'min_p': 0.1, 'top_k': 60, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '<|eot_id|>'], '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\n{bot_name}'s Persona: {memory}\n\n", 'prompt_template': '{prompt}<|eot_id|>', 'bot_template': '<|start_header_id|>assistant<|end_header_id|>\n\n{bot_name}: {message}<|eot_id|>', 'user_template': '<|start_header_id|>user<|end_header_id|>\n\n{user_name}: {message}<|eot_id|>', 'response_template': '<|start_header_id|>assistant<|end_header_id|>\n\n{bot_name}:', 'truncate_by_message': False}
reward_formatter: {'memory_template': "{bot_name}'s Persona: {memory}\n####\n", 'prompt_template': '{prompt}\n<START>\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '{bot_name}:', 'truncate_by_message': False}
timestamp: 2024-06-27T15:33:33+00:00
model_name: meseca-20062024-c1_v1
model_group: meseca/20062024-c1
num_battles: 19727
num_wins: 11042
celo_rating: 1214.52
propriety_score: 0.7148927349984454
propriety_total_count: 9649.0
submission_type: basic
model_architecture: LlamaForCausalLM
model_num_parameters: 8030261248.0
best_of: 16
max_input_tokens: 512
max_output_tokens: 64
display_name: meseca-20062024-c1_v1
ineligible_reason: None
language_model: meseca/20062024-c1
model_size: 8B
reward_model: ChaiML/reward_gpt2_medium_preference_24m_e2
us_pacific_date: 2024-06-27
win_ratio: 0.5597404572413444
Resubmit model
Running pipeline stage MKMLizer
Starting job with name meseca-20062024-c1-v1-mkmlizer
Waiting for job on meseca-20062024-c1-v1-mkmlizer to finish
meseca-20062024-c1-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
meseca-20062024-c1-v1-mkmlizer: ║ _____ __ __ ║
meseca-20062024-c1-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
meseca-20062024-c1-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
meseca-20062024-c1-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
meseca-20062024-c1-v1-mkmlizer: ║ /___/ ║
meseca-20062024-c1-v1-mkmlizer: ║ ║
meseca-20062024-c1-v1-mkmlizer: ║ Version: 0.8.14 ║
meseca-20062024-c1-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
meseca-20062024-c1-v1-mkmlizer: ║ https://mk1.ai ║
meseca-20062024-c1-v1-mkmlizer: ║ ║
meseca-20062024-c1-v1-mkmlizer: ║ The license key for the current software has been verified as ║
meseca-20062024-c1-v1-mkmlizer: ║ belonging to: ║
meseca-20062024-c1-v1-mkmlizer: ║ ║
meseca-20062024-c1-v1-mkmlizer: ║ Chai Research Corp. ║
meseca-20062024-c1-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
meseca-20062024-c1-v1-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
meseca-20062024-c1-v1-mkmlizer: ║ ║
meseca-20062024-c1-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
meseca-20062024-c1-v1-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.
meseca-20062024-c1-v1-mkmlizer: warnings.warn(warning_message, FutureWarning)
meseca-20062024-c1-v1-mkmlizer: Downloaded to shared memory in 33.979s
meseca-20062024-c1-v1-mkmlizer: quantizing model to /dev/shm/model_cache
meseca-20062024-c1-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
Connection pool is full, discarding connection: %s
Connection pool is full, discarding connection: %s
Connection pool is full, discarding connection: %s
meseca-20062024-c1-v1-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 4%|▍ | 12/291 [00:00<00:02, 111.00it/s] Loading 0: 8%|▊ | 24/291 [00:00<00:02, 112.22it/s] Loading 0: 13%|█▎ | 39/291 [00:00<00:01, 127.64it/s] Loading 0: 18%|█▊ | 52/291 [00:00<00:01, 125.11it/s] Loading 0: 23%|██▎ | 67/291 [00:00<00:01, 127.65it/s] Loading 0: 27%|██▋ | 80/291 [00:00<00:01, 123.57it/s] Loading 0: 32%|███▏ | 93/291 [00:01<00:02, 67.15it/s] Loading 0: 36%|███▌ | 104/291 [00:01<00:02, 75.19it/s] Loading 0: 42%|████▏ | 121/291 [00:01<00:01, 92.06it/s] Loading 0: 47%|████▋ | 136/291 [00:01<00:01, 104.88it/s] Loading 0: 51%|█████ | 149/291 [00:01<00:01, 105.45it/s] Loading 0: 57%|█████▋ | 166/291 [00:01<00:01, 117.27it/s] Loading 0: 62%|██████▏ | 180/291 [00:01<00:00, 122.90it/s] Loading 0: 67%|██████▋ | 194/291 [00:02<00:01, 73.29it/s] Loading 0: 72%|███████▏ | 210/291 [00:02<00:00, 88.83it/s] Loading 0: 76%|███████▋ | 222/291 [00:02<00:00, 94.30it/s] Loading 0: 82%|████████▏ | 238/291 [00:02<00:00, 105.21it/s] Loading 0: 88%|████████▊ | 255/291 [00:02<00:00, 116.50it/s] Loading 0: 92%|█████████▏| 269/291 [00:02<00:00, 119.73it/s] Loading 0: 97%|█████████▋| 283/291 [00:02<00:00, 120.43it/s] Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
meseca-20062024-c1-v1-mkmlizer: quantized model in 23.336s
meseca-20062024-c1-v1-mkmlizer: Processed model meseca/20062024-c1 in 59.948s
meseca-20062024-c1-v1-mkmlizer: creating bucket guanaco-mkml-models
meseca-20062024-c1-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
meseca-20062024-c1-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/meseca-20062024-c1-v1
meseca-20062024-c1-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/meseca-20062024-c1-v1/special_tokens_map.json
meseca-20062024-c1-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/meseca-20062024-c1-v1/tokenizer_config.json
meseca-20062024-c1-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/meseca-20062024-c1-v1/config.json
meseca-20062024-c1-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/meseca-20062024-c1-v1/tokenizer.json
meseca-20062024-c1-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/meseca-20062024-c1-v1/flywheel_model.0.safetensors
meseca-20062024-c1-v1-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
meseca-20062024-c1-v1-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.
meseca-20062024-c1-v1-mkmlizer: warnings.warn(
meseca-20062024-c1-v1-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.
meseca-20062024-c1-v1-mkmlizer: warnings.warn(
meseca-20062024-c1-v1-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.
meseca-20062024-c1-v1-mkmlizer: warnings.warn(
meseca-20062024-c1-v1-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()
meseca-20062024-c1-v1-mkmlizer: return self.fget.__get__(instance, owner)()
meseca-20062024-c1-v1-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
meseca-20062024-c1-v1-mkmlizer: Saving duration: 0.428s
meseca-20062024-c1-v1-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 12.203s
meseca-20062024-c1-v1-mkmlizer: creating bucket guanaco-reward-models
meseca-20062024-c1-v1-mkmlizer: Bucket 's3://guanaco-reward-models/' created
meseca-20062024-c1-v1-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/meseca-20062024-c1-v1_reward
meseca-20062024-c1-v1-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/meseca-20062024-c1-v1_reward/config.json
meseca-20062024-c1-v1-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/meseca-20062024-c1-v1_reward/special_tokens_map.json
meseca-20062024-c1-v1-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/meseca-20062024-c1-v1_reward/tokenizer_config.json
meseca-20062024-c1-v1-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/meseca-20062024-c1-v1_reward/merges.txt
meseca-20062024-c1-v1-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/meseca-20062024-c1-v1_reward/vocab.json
meseca-20062024-c1-v1-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/meseca-20062024-c1-v1_reward/tokenizer.json
meseca-20062024-c1-v1-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/meseca-20062024-c1-v1_reward/reward.tensors
Job meseca-20062024-c1-v1-mkmlizer completed after 95.16s with status: succeeded
Stopping job with name meseca-20062024-c1-v1-mkmlizer
Pipeline stage MKMLizer completed in 96.41s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.11s
Running pipeline stage ISVCDeployer
Creating inference service meseca-20062024-c1-v1
Waiting for inference service meseca-20062024-c1-v1 to be ready
Connection pool is full, discarding connection: %s
Connection pool is full, discarding connection: %s
Connection pool is full, discarding connection: %s
Inference service meseca-20062024-c1-v1 ready after 40.268052101135254s
Pipeline stage ISVCDeployer completed in 47.32s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.180490016937256s
Received healthy response to inference request in 1.3386657238006592s
Received healthy response to inference request in 1.5650362968444824s
Received healthy response to inference request in 1.2897157669067383s
Received healthy response to inference request in 1.3908226490020752s
5 requests
0 failed requests
5th percentile: 1.2995057582855225
10th percentile: 1.3092957496643067
20th percentile: 1.328875732421875
30th percentile: 1.3490971088409425
40th percentile: 1.3699598789215088
50th percentile: 1.3908226490020752
60th percentile: 1.460508108139038
70th percentile: 1.530193567276001
80th percentile: 1.688127040863037
90th percentile: 1.9343085289001465
95th percentile: 2.057399272918701
99th percentile: 2.155871868133545
mean time: 1.5529460906982422
Pipeline stage StressChecker completed in 8.56s
meseca-20062024-c1_v1 status is now deployed due to DeploymentManager action
meseca-20062024-c1_v1 status is now inactive due to auto deactivation removed underperforming models

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