submission_id: hastagaras-sciemet-8b-l3_1113_v1
developer_uid: Hastagaras
status: inactive
model_repo: Hastagaras/Sciemet-8B-L3-MK.I-Alpha
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 0.95, 'top_p': 1.0, 'min_p': 0.08, 'top_k': 100, '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: 2024-06-15T00:27:51+00:00
model_name: test
model_eval_status: success
model_group: Hastagaras/Sciemet-8B-L3
num_battles: 15337
num_wins: 8148
celo_rating: 1215.7
propriety_score: 0.6707723518330677
propriety_total_count: 6901.0
submission_type: basic
model_architecture: LlamaForCausalLM
model_num_parameters: 8030261248.0
best_of: 16
max_input_tokens: 512
max_output_tokens: 64
display_name: test
ineligible_reason: None
language_model: Hastagaras/Sciemet-8B-L3-MK.I-Alpha
model_size: 8B
reward_model: ChaiML/reward_gpt2_medium_preference_24m_e2
us_pacific_date: 2024-06-14
win_ratio: 0.5312642628936559
Resubmit model
Running pipeline stage MKMLizer
Starting job with name hastagaras-sciemet-8b-l3-1113-v1-mkmlizer
Waiting for job on hastagaras-sciemet-8b-l3-1113-v1-mkmlizer to finish
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
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hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: ║ Version: 0.8.14 ║
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
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hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: ║ Chai Research Corp. ║
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hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
hastagaras-sciemet-8b-l3-1113-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.
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: warnings.warn(warning_message, FutureWarning)
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: Downloaded to shared memory in 37.881s
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: quantizing model to /dev/shm/model_cache
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 5%|▍ | 14/291 [00:00<00:02, 124.77it/s] Loading 0: 11%|█ | 32/291 [00:00<00:01, 150.90it/s] Loading 0: 17%|█▋ | 50/291 [00:00<00:01, 156.98it/s] Loading 0: 23%|██▎ | 68/291 [00:00<00:01, 161.41it/s] Loading 0: 29%|██▉ | 85/291 [00:00<00:02, 87.52it/s] Loading 0: 35%|███▌ | 103/291 [00:00<00:01, 104.52it/s] Loading 0: 42%|████▏ | 121/291 [00:01<00:01, 120.07it/s] Loading 0: 48%|████▊ | 139/291 [00:01<00:01, 132.61it/s] Loading 0: 54%|█████▍ | 157/291 [00:01<00:00, 142.62it/s] Loading 0: 60%|██████ | 176/291 [00:01<00:00, 153.73it/s] Loading 0: 66%|██████▋ | 193/291 [00:01<00:01, 95.03it/s] Loading 0: 73%|███████▎ | 211/291 [00:01<00:00, 109.35it/s] Loading 0: 79%|███████▊ | 229/291 [00:01<00:00, 122.85it/s] Loading 0: 85%|████████▍ | 247/291 [00:01<00:00, 134.31it/s] Loading 0: 91%|█████████ | 265/291 [00:02<00:00, 142.68it/s] Loading 0: 97%|█████████▋| 282/291 [00:02<00:00, 147.40it/s] Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: quantized model in 22.505s
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: Processed model Hastagaras/Sciemet-8B-L3-MK.I-Alpha in 62.886s
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: creating bucket guanaco-mkml-models
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/hastagaras-sciemet-8b-l3-1113-v1
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/hastagaras-sciemet-8b-l3-1113-v1/config.json
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/hastagaras-sciemet-8b-l3-1113-v1/tokenizer_config.json
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/hastagaras-sciemet-8b-l3-1113-v1/special_tokens_map.json
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/hastagaras-sciemet-8b-l3-1113-v1/tokenizer.json
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/hastagaras-sciemet-8b-l3-1113-v1/flywheel_model.0.safetensors
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
hastagaras-sciemet-8b-l3-1113-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.
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: warnings.warn(
hastagaras-sciemet-8b-l3-1113-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.
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: warnings.warn(
hastagaras-sciemet-8b-l3-1113-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.
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: warnings.warn(
hastagaras-sciemet-8b-l3-1113-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()
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: return self.fget.__get__(instance, owner)()
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: Saving duration: 0.403s
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 4.074s
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: creating bucket guanaco-reward-models
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: Bucket 's3://guanaco-reward-models/' created
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/hastagaras-sciemet-8b-l3-1113-v1_reward
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/hastagaras-sciemet-8b-l3-1113-v1_reward/special_tokens_map.json
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/hastagaras-sciemet-8b-l3-1113-v1_reward/config.json
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/hastagaras-sciemet-8b-l3-1113-v1_reward/merges.txt
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/hastagaras-sciemet-8b-l3-1113-v1_reward/tokenizer_config.json
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/hastagaras-sciemet-8b-l3-1113-v1_reward/vocab.json
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/hastagaras-sciemet-8b-l3-1113-v1_reward/tokenizer.json
hastagaras-sciemet-8b-l3-1113-v1-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/hastagaras-sciemet-8b-l3-1113-v1_reward/reward.tensors
Job hastagaras-sciemet-8b-l3-1113-v1-mkmlizer completed after 93.2s with status: succeeded
Stopping job with name hastagaras-sciemet-8b-l3-1113-v1-mkmlizer
Pipeline stage MKMLizer completed in 96.48s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.09s
Running pipeline stage ISVCDeployer
Creating inference service hastagaras-sciemet-8b-l3-1113-v1
Waiting for inference service hastagaras-sciemet-8b-l3-1113-v1 to be ready
Inference service hastagaras-sciemet-8b-l3-1113-v1 ready after 40.28077006340027s
Pipeline stage ISVCDeployer completed in 47.80s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.1907970905303955s
Received healthy response to inference request in 1.3281617164611816s
Received healthy response to inference request in 1.325122356414795s
%s, retrying in %s seconds...
Received healthy response to inference request in 1.2703063488006592s
Received healthy response to inference request in 1.3515968322753906s
Received healthy response to inference request in 1.304483413696289s
Received healthy response to inference request in 1.2718398571014404s
Received healthy response to inference request in 1.3340489864349365s
5 requests
0 failed requests
5th percentile: 1.2706130504608155
10th percentile: 1.2709197521209716
20th percentile: 1.271533155441284
30th percentile: 1.2783685684204102
40th percentile: 1.2914259910583497
50th percentile: 1.304483413696289
60th percentile: 1.316309642791748
70th percentile: 1.328135871887207
80th percentile: 1.3375585556030274
90th percentile: 1.344577693939209
95th percentile: 1.3480872631072998
99th percentile: 1.3508949184417725
mean time: 1.3064550876617431
Pipeline stage StressChecker completed in 17.22s
Running pipeline stage DaemonicModelEvalScorer
Pipeline stage DaemonicModelEvalScorer completed in 0.04s
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
hastagaras-sciemet-8b-l3_1113_v1 status is now deployed due to DeploymentManager action
hastagaras-sciemet-8b-l3_1113_v1 status is now inactive due to auto deactivation removed underperforming models

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