submission_id: thetsar1209-llama3-carp-v0-4_v5
developer_uid: TheTsar1209
status: inactive
model_repo: TheTsar1209/llama3-carp-v0.4
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': ['<|im_end|>'], 'max_input_tokens': 512, 'best_of': 16, 'max_output_tokens': 64}
formatter: {'memory_template': '<|im_start|>system\nYou are {bot_name}\nDescription : {memory}\n', 'prompt_template': 'Example conversation:\n{prompt}<|im_end|>\n', 'bot_template': '<|im_start|>assistant\n{message}<|im_end|>\n', 'user_template': '<|im_start|>user\n{message}<|im_end|>\n', 'response_template': '<|im_start|>assistant\n', 'truncate_by_message': True}
reward_formatter: {'memory_template': '<|im_start|>system\n{memory}<|im_end|>\n', 'prompt_template': '<|im_start|>user\n{prompt}<|im_end|>\n', 'bot_template': '<|im_start|>assistant\n{bot_name}: {message}<|im_end|>\n', 'user_template': '<|im_start|>user\n{user_name}: {message}<|im_end|>\n', 'response_template': '<|im_start|>assistant\n{bot_name}:', 'truncate_by_message': True}
timestamp: 2024-05-21T23:21:27+00:00
model_name: thetsar1209-llama3-carp-v0-4_v1
model_eval_status: success
model_group: TheTsar1209/llama3-carp-
num_battles: 19882
num_wins: 10288
celo_rating: 1183.3
safety_score: 0.93
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: thetsar1209-llama3-carp-v0-4_v1
ineligible_reason: propriety_total_count < 5000
language_model: TheTsar1209/llama3-carp-v0.4
model_size: 8B
reward_model: ChaiML/reward_gpt2_medium_preference_24m_e2
us_pacific_date: 2024-05-21
win_ratio: 0.5174529725379741
Resubmit model
Running pipeline stage MKMLizer
Starting job with name thetsar1209-llama3-carp-v0-4-v5-mkmlizer
Waiting for job on thetsar1209-llama3-carp-v0-4-v5-mkmlizer to finish
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
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thetsar1209-llama3-carp-v0-4-v5-mkmlizer: ║ ║
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: ║ Version: 0.8.14 ║
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: ║ https://mk1.ai ║
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thetsar1209-llama3-carp-v0-4-v5-mkmlizer: ║ belonging to: ║
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: ║ ║
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: ║ Chai Research Corp. ║
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
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thetsar1209-llama3-carp-v0-4-v5-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
thetsar1209-llama3-carp-v0-4-v5-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.
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: warnings.warn(warning_message, FutureWarning)
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: Downloaded to shared memory in 22.681s
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: quantizing model to /dev/shm/model_cache
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: Saving flywheel model at /dev/shm/model_cache
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 4%|▍ | 13/291 [00:00<00:02, 121.37it/s] Loading 0: 9%|▉ | 26/291 [00:00<00:02, 123.13it/s] Loading 0: 14%|█▎ | 40/291 [00:00<00:02, 122.86it/s] Loading 0: 19%|█▊ | 54/291 [00:00<00:01, 127.67it/s] Loading 0: 23%|██▎ | 67/291 [00:00<00:01, 123.29it/s] Loading 0: 29%|██▊ | 83/291 [00:01<00:03, 61.99it/s] Loading 0: 32%|███▏ | 93/291 [00:01<00:02, 68.42it/s] Loading 0: 36%|███▌ | 104/291 [00:01<00:02, 74.70it/s] Loading 0: 42%|████▏ | 121/291 [00:01<00:01, 93.76it/s] Loading 0: 46%|████▌ | 133/291 [00:01<00:01, 99.52it/s] Loading 0: 51%|█████ | 147/291 [00:01<00:01, 106.91it/s] Loading 0: 55%|█████▍ | 159/291 [00:01<00:01, 106.04it/s] Loading 0: 59%|█████▉ | 173/291 [00:01<00:01, 109.89it/s] Loading 0: 64%|██████▍ | 187/291 [00:02<00:01, 66.51it/s] Loading 0: 68%|██████▊ | 197/291 [00:02<00:01, 72.32it/s] Loading 0: 73%|███████▎ | 211/291 [00:02<00:00, 85.70it/s] Loading 0: 78%|███████▊ | 228/291 [00:02<00:00, 102.03it/s] Loading 0: 83%|████████▎ | 241/291 [00:02<00:00, 105.84it/s] Loading 0: 88%|████████▊ | 255/291 [00:02<00:00, 113.77it/s] Loading 0: 92%|█████████▏| 268/291 [00:02<00:00, 115.94it/s] Loading 0: 97%|█████████▋| 282/291 [00:02<00:00, 117.93it/s] Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: quantized model in 20.034s
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: Processed model TheTsar1209/llama3-carp-v0.4 in 43.889s
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: creating bucket guanaco-mkml-models
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/thetsar1209-llama3-carp-v0-4-v5
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/thetsar1209-llama3-carp-v0-4-v5/special_tokens_map.json
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/thetsar1209-llama3-carp-v0-4-v5/tokenizer_config.json
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/thetsar1209-llama3-carp-v0-4-v5/config.json
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/thetsar1209-llama3-carp-v0-4-v5/tokenizer.json
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/thetsar1209-llama3-carp-v0-4-v5/flywheel_model.0.safetensors
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
thetsar1209-llama3-carp-v0-4-v5-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.
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: warnings.warn(
thetsar1209-llama3-carp-v0-4-v5-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.
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: warnings.warn(
thetsar1209-llama3-carp-v0-4-v5-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.
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: warnings.warn(
thetsar1209-llama3-carp-v0-4-v5-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()
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: return self.fget.__get__(instance, owner)()
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: Saving duration: 0.254s
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 3.842s
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: creating bucket guanaco-reward-models
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: Bucket 's3://guanaco-reward-models/' created
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/thetsar1209-llama3-carp-v0-4-v5_reward
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/thetsar1209-llama3-carp-v0-4-v5_reward/special_tokens_map.json
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/thetsar1209-llama3-carp-v0-4-v5_reward/tokenizer_config.json
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/thetsar1209-llama3-carp-v0-4-v5_reward/merges.txt
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/thetsar1209-llama3-carp-v0-4-v5_reward/vocab.json
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/thetsar1209-llama3-carp-v0-4-v5_reward/config.json
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/thetsar1209-llama3-carp-v0-4-v5_reward/tokenizer.json
thetsar1209-llama3-carp-v0-4-v5-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/thetsar1209-llama3-carp-v0-4-v5_reward/reward.tensors
Job thetsar1209-llama3-carp-v0-4-v5-mkmlizer completed after 73.19s with status: succeeded
Stopping job with name thetsar1209-llama3-carp-v0-4-v5-mkmlizer
Pipeline stage MKMLizer completed in 76.09s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.08s
Running pipeline stage ISVCDeployer
Creating inference service thetsar1209-llama3-carp-v0-4-v5
Waiting for inference service thetsar1209-llama3-carp-v0-4-v5 to be ready
Inference service thetsar1209-llama3-carp-v0-4-v5 ready after 40.27964377403259s
Pipeline stage ISVCDeployer completed in 47.25s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.2008912563323975s
Received healthy response to inference request in 1.3865697383880615s
Received healthy response to inference request in 1.2848494052886963s
Received healthy response to inference request in 1.2881102561950684s
Received healthy response to inference request in 1.2702393531799316s
5 requests
0 failed requests
5th percentile: 1.2731613636016845
10th percentile: 1.2760833740234374
20th percentile: 1.2819273948669434
30th percentile: 1.2855015754699708
40th percentile: 1.2868059158325196
50th percentile: 1.2881102561950684
60th percentile: 1.3274940490722655
70th percentile: 1.366877841949463
80th percentile: 1.5494340419769288
90th percentile: 1.8751626491546631
95th percentile: 2.03802695274353
99th percentile: 2.168318395614624
mean time: 1.4861320018768311
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
thetsar1209-llama3-carp-v0-4_v5 status is now deployed due to DeploymentManager action
thetsar1209-llama3-carp-v0-4_v5 status is now inactive due to auto deactivation removed underperforming models

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