submission_id: cycy233-l3-duduk-v0-e3-0_v1
developer_uid: shiroe40
status: inactive
model_repo: cycy233/L3-duduk-v0-e3.0
reward_repo: ChaiML/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\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}
timestamp: 2024-06-28T03:31:08+00:00
model_name: auto
model_group: cycy233/L3-duduk-v0-e3.0
num_battles: 19654
num_wins: 9970
celo_rating: 1188.79
propriety_score: 0.7065559991594873
propriety_total_count: 9518.0
submission_type: basic
model_architecture: LlamaForCausalLM
model_num_parameters: 8030261248.0
best_of: 16
max_input_tokens: 512
max_output_tokens: 64
display_name: auto
ineligible_reason: None
language_model: cycy233/L3-duduk-v0-e3.0
model_size: 8B
reward_model: ChaiML/reward_gpt2_medium_preference_24m_e2
us_pacific_date: 2024-06-27
win_ratio: 0.5072758725959092
Resubmit model
Running pipeline stage MKMLizer
Starting job with name cycy233-l3-duduk-v0-e3-0-v1-mkmlizer
Waiting for job on cycy233-l3-duduk-v0-e3-0-v1-mkmlizer to finish
Failed to get response for submission cycy233-l3-exp-v2-e1-5_v1: ('Connection aborted.', RemoteDisconnected('Remote end closed connection without response'))
Failed to get response for submission cycy233-l3-exp-v2-e1-5_v1: ('Connection aborted.', RemoteDisconnected('Remote end closed connection without response'))
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ _____ __ __ ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ /___/ ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ Version: 0.8.14 ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ https://mk1.ai ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ The license key for the current software has been verified as ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ belonging to: ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ Chai Research Corp. ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ║ ║
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
cycy233-l3-duduk-v0-e3-0-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.
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: warnings.warn(warning_message, FutureWarning)
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: Downloaded to shared memory in 41.675s
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: quantizing model to /dev/shm/model_cache
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 29%|██▊ | 83/291 [00:01<00:03, 68.83it/s] Loading 0: 64%|██████▍ | 187/291 [00:02<00:01, 82.06it/s] Loading 0: 99%|█████████▊| 287/291 [00:02<00:00, 119.42it/s] Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: quantized model in 25.821s
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: Processed model cycy233/L3-duduk-v0-e3.0 in 70.158s
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: creating bucket guanaco-mkml-models
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/cycy233-l3-duduk-v0-e3-0-v1
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/cycy233-l3-duduk-v0-e3-0-v1/config.json
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/cycy233-l3-duduk-v0-e3-0-v1/special_tokens_map.json
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/cycy233-l3-duduk-v0-e3-0-v1/tokenizer_config.json
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/cycy233-l3-duduk-v0-e3-0-v1/tokenizer.json
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/cycy233-l3-duduk-v0-e3-0-v1/flywheel_model.0.safetensors
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
cycy233-l3-duduk-v0-e3-0-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.
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: warnings.warn(
cycy233-l3-duduk-v0-e3-0-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.
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: warnings.warn(
cycy233-l3-duduk-v0-e3-0-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.
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: warnings.warn(
cycy233-l3-duduk-v0-e3-0-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()
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: return self.fget.__get__(instance, owner)()
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: Saving duration: 0.459s
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 7.331s
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: creating bucket guanaco-reward-models
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: Bucket 's3://guanaco-reward-models/' created
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/cycy233-l3-duduk-v0-e3-0-v1_reward
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/cycy233-l3-duduk-v0-e3-0-v1_reward/config.json
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/cycy233-l3-duduk-v0-e3-0-v1_reward/tokenizer_config.json
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/cycy233-l3-duduk-v0-e3-0-v1_reward/special_tokens_map.json
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/cycy233-l3-duduk-v0-e3-0-v1_reward/merges.txt
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/cycy233-l3-duduk-v0-e3-0-v1_reward/vocab.json
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/cycy233-l3-duduk-v0-e3-0-v1_reward/tokenizer.json
cycy233-l3-duduk-v0-e3-0-v1-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/cycy233-l3-duduk-v0-e3-0-v1_reward/reward.tensors
Job cycy233-l3-duduk-v0-e3-0-v1-mkmlizer completed after 148.86s with status: succeeded
Stopping job with name cycy233-l3-duduk-v0-e3-0-v1-mkmlizer
Pipeline stage MKMLizer completed in 149.71s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.11s
Running pipeline stage ISVCDeployer
Creating inference service cycy233-l3-duduk-v0-e3-0-v1
Waiting for inference service cycy233-l3-duduk-v0-e3-0-v1 to be ready
Inference service cycy233-l3-duduk-v0-e3-0-v1 ready after 160.7700481414795s
Pipeline stage ISVCDeployer completed in 167.35s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.6728336811065674s
Received healthy response to inference request in 1.341914176940918s
Received healthy response to inference request in 1.3157386779785156s
Received healthy response to inference request in 1.6942055225372314s
Received healthy response to inference request in 1.362835168838501s
5 requests
0 failed requests
5th percentile: 1.320973777770996
10th percentile: 1.3262088775634766
20th percentile: 1.3366790771484376
30th percentile: 1.3460983753204345
40th percentile: 1.3544667720794679
50th percentile: 1.362835168838501
60th percentile: 1.4953833103179932
70th percentile: 1.6279314517974852
80th percentile: 1.8899311542510988
90th percentile: 2.281382417678833
95th percentile: 2.4771080493927
99th percentile: 2.633688554763794
mean time: 1.6775054454803466
Pipeline stage StressChecker completed in 9.08s
cycy233-l3-duduk-v0-e3-0_v1 status is now deployed due to DeploymentManager action
cycy233-l3-duduk-v0-e3-0_v1 status is now inactive due to auto deactivation removed underperforming models

Usage Metrics

Latency Metrics