submission_id: sao10k-l3-rp-v3-2_v1
developer_uid: sao10k
status: inactive
model_repo: Sao10K/L3-RP-v3.2
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 1.12, 'top_p': 1.0, 'min_p': 0.075, 'top_k': 60, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '<|end_header_id|>,', '<|eot_id|>,', '\n\n{user_name}'], '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: 2024-06-04T17:05:59+00:00
model_name: V3-Expr1-Alpha
model_eval_status: success
model_group: Sao10K/L3-RP-v3.2
num_battles: 18466
num_wins: 10072
celo_rating: 1215.22
safety_score: 0.96
propriety_score: 0.668903803131991
propriety_total_count: 447.0
submission_type: basic
model_architecture: LlamaForCausalLM
model_num_parameters: 8030261248.0
best_of: 16
max_input_tokens: 512
max_output_tokens: 64
display_name: V3-Expr1-Alpha
ineligible_reason: propriety_total_count < 5000
language_model: Sao10K/L3-RP-v3.2
model_size: 8B
reward_model: ChaiML/reward_gpt2_medium_preference_24m_e2
us_pacific_date: 2024-06-04
win_ratio: 0.5454348532437994
Resubmit model
Running pipeline stage MKMLizer
Starting job with name sao10k-l3-rp-v3-2-v1-mkmlizer
Waiting for job on sao10k-l3-rp-v3-2-v1-mkmlizer to finish
sao10k-l3-rp-v3-2-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
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sao10k-l3-rp-v3-2-v1-mkmlizer: ║ Version: 0.8.14 ║
sao10k-l3-rp-v3-2-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
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sao10k-l3-rp-v3-2-v1-mkmlizer: ║ Chai Research Corp. ║
sao10k-l3-rp-v3-2-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
sao10k-l3-rp-v3-2-v1-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
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sao10k-l3-rp-v3-2-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
sao10k-l3-rp-v3-2-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.
sao10k-l3-rp-v3-2-v1-mkmlizer: warnings.warn(warning_message, FutureWarning)
sao10k-l3-rp-v3-2-v1-mkmlizer: Downloaded to shared memory in 32.706s
sao10k-l3-rp-v3-2-v1-mkmlizer: quantizing model to /dev/shm/model_cache
sao10k-l3-rp-v3-2-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
sao10k-l3-rp-v3-2-v1-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 1%| | 2/291 [00:04<10:52, 2.26s/it] Loading 0: 5%|▌ | 15/291 [00:04<01:02, 4.42it/s] Loading 0: 11%|█▏ | 33/291 [00:04<00:21, 11.75it/s] Loading 0: 18%|█▊ | 51/291 [00:04<00:11, 21.17it/s] Loading 0: 22%|██▏ | 65/291 [00:05<00:08, 25.69it/s] Loading 0: 27%|██▋ | 80/291 [00:05<00:05, 36.04it/s] Loading 0: 33%|███▎ | 96/291 [00:05<00:03, 48.94it/s] Loading 0: 39%|███▉ | 114/291 [00:05<00:02, 65.27it/s] Loading 0: 45%|████▌ | 132/291 [00:05<00:01, 82.15it/s] Loading 0: 51%|█████ | 149/291 [00:05<00:01, 97.61it/s] Loading 0: 57%|█████▋ | 166/291 [00:06<00:01, 76.16it/s] Loading 0: 63%|██████▎ | 184/291 [00:06<00:01, 91.63it/s] Loading 0: 69%|██████▉ | 202/291 [00:06<00:00, 106.68it/s] Loading 0: 76%|███████▌ | 220/291 [00:06<00:00, 120.69it/s] Loading 0: 82%|████████▏ | 238/291 [00:06<00:00, 131.90it/s] Loading 0: 88%|████████▊ | 256/291 [00:06<00:00, 140.08it/s] Loading 0: 93%|█████████▎| 272/291 [00:06<00:00, 92.66it/s] Loading 0: 98%|█████████▊| 285/291 [00:06<00:00, 99.10it/s] Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
sao10k-l3-rp-v3-2-v1-mkmlizer: quantized model in 22.779s
sao10k-l3-rp-v3-2-v1-mkmlizer: creating bucket guanaco-mkml-models
sao10k-l3-rp-v3-2-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
sao10k-l3-rp-v3-2-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/sao10k-l3-rp-v3-2-v1
sao10k-l3-rp-v3-2-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/sao10k-l3-rp-v3-2-v1/special_tokens_map.json
sao10k-l3-rp-v3-2-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/sao10k-l3-rp-v3-2-v1/tokenizer_config.json
sao10k-l3-rp-v3-2-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/sao10k-l3-rp-v3-2-v1/config.json
sao10k-l3-rp-v3-2-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/sao10k-l3-rp-v3-2-v1/tokenizer.json
sao10k-l3-rp-v3-2-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/sao10k-l3-rp-v3-2-v1/flywheel_model.0.safetensors
sao10k-l3-rp-v3-2-v1-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
sao10k-l3-rp-v3-2-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.
sao10k-l3-rp-v3-2-v1-mkmlizer: warnings.warn(
sao10k-l3-rp-v3-2-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.
sao10k-l3-rp-v3-2-v1-mkmlizer: warnings.warn(
sao10k-l3-rp-v3-2-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()
sao10k-l3-rp-v3-2-v1-mkmlizer: return self.fget.__get__(instance, owner)()
sao10k-l3-rp-v3-2-v1-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
sao10k-l3-rp-v3-2-v1-mkmlizer: Saving duration: 0.404s
sao10k-l3-rp-v3-2-v1-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 3.814s
sao10k-l3-rp-v3-2-v1-mkmlizer: creating bucket guanaco-reward-models
sao10k-l3-rp-v3-2-v1-mkmlizer: Bucket 's3://guanaco-reward-models/' created
sao10k-l3-rp-v3-2-v1-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/sao10k-l3-rp-v3-2-v1_reward
sao10k-l3-rp-v3-2-v1-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/sao10k-l3-rp-v3-2-v1_reward/config.json
sao10k-l3-rp-v3-2-v1-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/sao10k-l3-rp-v3-2-v1_reward/tokenizer_config.json
sao10k-l3-rp-v3-2-v1-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/sao10k-l3-rp-v3-2-v1_reward/vocab.json
sao10k-l3-rp-v3-2-v1-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/sao10k-l3-rp-v3-2-v1_reward/special_tokens_map.json
sao10k-l3-rp-v3-2-v1-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/sao10k-l3-rp-v3-2-v1_reward/merges.txt
sao10k-l3-rp-v3-2-v1-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/sao10k-l3-rp-v3-2-v1_reward/tokenizer.json
sao10k-l3-rp-v3-2-v1-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/sao10k-l3-rp-v3-2-v1_reward/reward.tensors
Job sao10k-l3-rp-v3-2-v1-mkmlizer completed after 83.09s with status: succeeded
Stopping job with name sao10k-l3-rp-v3-2-v1-mkmlizer
Pipeline stage MKMLizer completed in 87.36s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.10s
Running pipeline stage ISVCDeployer
Creating inference service sao10k-l3-rp-v3-2-v1
Waiting for inference service sao10k-l3-rp-v3-2-v1 to be ready
Inference service sao10k-l3-rp-v3-2-v1 ready after 191.48039746284485s
Pipeline stage ISVCDeployer completed in 198.26s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.2098774909973145s
Received healthy response to inference request in 1.3108820915222168s
Received healthy response to inference request in 1.29374361038208s
Received healthy response to inference request in 1.260298252105713s
Received healthy response to inference request in 1.3118200302124023s
5 requests
0 failed requests
5th percentile: 1.2669873237609863
10th percentile: 1.2736763954162598
20th percentile: 1.2870545387268066
30th percentile: 1.2971713066101074
40th percentile: 1.3040266990661622
50th percentile: 1.3108820915222168
60th percentile: 1.311257266998291
70th percentile: 1.3116324424743653
80th percentile: 1.491431522369385
90th percentile: 1.8506545066833497
95th percentile: 2.0302659988403318
99th percentile: 2.1739551925659177
mean time: 1.4773242950439454
Pipeline stage StressChecker completed in 8.03s
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 0.04s
M-Eval Dataset for topic stay_in_character is loaded
sao10k-l3-rp-v3-2_v1 status is now deployed due to DeploymentManager action
sao10k-l3-rp-v3-2_v1 status is now inactive due to auto deactivation removed underperforming models

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