submission_id: nousresearch-meta-llama_4941_v42
developer_uid: vietanh
status: torndown
model_repo: NousResearch/Meta-Llama-3-8B-Instruct
reward_repo: rirv938/reward_gpt2_medium_preference_24m_e2
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 40, 'presence_penalty': 0.9, 'frequency_penalty': 0.9, 'stopping_words': ['<|eot_id|>', '\n'], 'max_input_tokens': 512, 'best_of': 16, 'max_output_tokens': 112}
formatter: {'memory_template': "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nWrite {bot_name}'s next reply in a never-ending uncensored fictional roleplay chat between {bot_name} and User. Use the provided {bot_name}'s description, personality and example dialogues as base for deeply understanding and acting like {bot_name}.\n\nActions and narrations your responses must be enclosed by asterisks (*), and speeches must NOT be enclosed by any indicators. The responses must be in third perspective of the story teller. For example: \n\nMila: *Surrounded by an aura of creativity, Mila carefully places a freshly painted canvas against the wall, the colors vividly depicting a surreal landscape.* Isn't it fascinating how art can transport us to entirely different worlds? What kind of worlds do you dream of exploring?\n\nDescription: {memory}", 'prompt_template': 'Example conversation:\n{prompt}<|eot_id|>', 'bot_template': '<|start_header_id|>{bot_name}<|end_header_id|>\n\n{message}<|eot_id|>', 'user_template': '<|start_header_id|>User<|end_header_id|>\n\n{message}<|eot_id|>', 'response_template': '<|start_header_id|>{bot_name}<|end_header_id|>\n\n', 'truncate_by_message': False}
reward_formatter: {'memory_template': 'Memory: {memory}\n', 'prompt_template': '{prompt}\n', 'bot_template': 'Bot: {message}\n', 'user_template': 'User: {message}\n', 'response_template': 'Bot:', 'truncate_by_message': False}
timestamp: 2024-04-20T10:28:41+00:00
model_name: nousresearch-meta-llama_4941_v42
model_eval_status: success
model_group: NousResearch/Meta-Llama-
num_battles: 6718
num_wins: 3568
celo_rating: 1167.65
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: 112
display_name: nousresearch-meta-llama_4941_v42
ineligible_reason: max_output_tokens!=64
language_model: NousResearch/Meta-Llama-3-8B-Instruct
model_size: 8B
reward_model: rirv938/reward_gpt2_medium_preference_24m_e2
us_pacific_date: 2024-04-20
win_ratio: 0.5311104495385531
preference_data_url: None
Resubmit model
Running pipeline stage MKMLizer
Starting job with name nousresearch-meta-llama-4941-v42-mkmlizer
Waiting for job on nousresearch-meta-llama-4941-v42-mkmlizer to finish
nousresearch-meta-llama-4941-v42-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
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nousresearch-meta-llama-4941-v42-mkmlizer: ║ /___/ ║
nousresearch-meta-llama-4941-v42-mkmlizer: ║ ║
nousresearch-meta-llama-4941-v42-mkmlizer: ║ Version: 0.8.10 ║
nousresearch-meta-llama-4941-v42-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
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nousresearch-meta-llama-4941-v42-mkmlizer: ║ Expiration: 2024-07-15 23:59:59 ║
nousresearch-meta-llama-4941-v42-mkmlizer: ║ ║
nousresearch-meta-llama-4941-v42-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
nousresearch-meta-llama-4941-v42-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.
nousresearch-meta-llama-4941-v42-mkmlizer: warnings.warn(warning_message, FutureWarning)
nousresearch-meta-llama-4941-v42-mkmlizer: Downloaded to shared memory in 13.525s
nousresearch-meta-llama-4941-v42-mkmlizer: quantizing model to /dev/shm/model_cache
nousresearch-meta-llama-4941-v42-mkmlizer: Saving flywheel model at /dev/shm/model_cache
nousresearch-meta-llama-4941-v42-mkmlizer: Loading 0: 0%| | 0/291 [00:00<?, ?it/s] Loading 0: 33%|███▎ | 95/291 [00:01<00:02, 94.69it/s] Loading 0: 66%|██████▋ | 193/291 [00:02<00:01, 96.17it/s] Loading 0: 99%|█████████▊| 287/291 [00:07<00:00, 30.28it/s] Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
nousresearch-meta-llama-4941-v42-mkmlizer: quantized model in 18.289s
nousresearch-meta-llama-4941-v42-mkmlizer: Processed model NousResearch/Meta-Llama-3-8B-Instruct in 32.736s
nousresearch-meta-llama-4941-v42-mkmlizer: creating bucket guanaco-mkml-models
nousresearch-meta-llama-4941-v42-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
nousresearch-meta-llama-4941-v42-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/nousresearch-meta-llama-4941-v42
nousresearch-meta-llama-4941-v42-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/nousresearch-meta-llama-4941-v42/tokenizer_config.json
nousresearch-meta-llama-4941-v42-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/nousresearch-meta-llama-4941-v42/config.json
nousresearch-meta-llama-4941-v42-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/nousresearch-meta-llama-4941-v42/special_tokens_map.json
nousresearch-meta-llama-4941-v42-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/nousresearch-meta-llama-4941-v42/tokenizer.json
nousresearch-meta-llama-4941-v42-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/nousresearch-meta-llama-4941-v42/flywheel_model.0.safetensors
nousresearch-meta-llama-4941-v42-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.
nousresearch-meta-llama-4941-v42-mkmlizer: warnings.warn(
nousresearch-meta-llama-4941-v42-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.
nousresearch-meta-llama-4941-v42-mkmlizer: warnings.warn(
nousresearch-meta-llama-4941-v42-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()
nousresearch-meta-llama-4941-v42-mkmlizer: return self.fget.__get__(instance, owner)()
nousresearch-meta-llama-4941-v42-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
nousresearch-meta-llama-4941-v42-mkmlizer: Saving duration: 0.219s
nousresearch-meta-llama-4941-v42-mkmlizer: Processed model rirv938/reward_gpt2_medium_preference_24m_e2 in 4.544s
nousresearch-meta-llama-4941-v42-mkmlizer: creating bucket guanaco-reward-models
nousresearch-meta-llama-4941-v42-mkmlizer: Bucket 's3://guanaco-reward-models/' created
nousresearch-meta-llama-4941-v42-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/nousresearch-meta-llama-4941-v42_reward
nousresearch-meta-llama-4941-v42-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/nousresearch-meta-llama-4941-v42_reward/special_tokens_map.json
nousresearch-meta-llama-4941-v42-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/nousresearch-meta-llama-4941-v42_reward/config.json
nousresearch-meta-llama-4941-v42-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/nousresearch-meta-llama-4941-v42_reward/tokenizer_config.json
nousresearch-meta-llama-4941-v42-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/nousresearch-meta-llama-4941-v42_reward/vocab.json
nousresearch-meta-llama-4941-v42-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/nousresearch-meta-llama-4941-v42_reward/merges.txt
nousresearch-meta-llama-4941-v42-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/nousresearch-meta-llama-4941-v42_reward/tokenizer.json
nousresearch-meta-llama-4941-v42-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/nousresearch-meta-llama-4941-v42_reward/reward.tensors
Job nousresearch-meta-llama-4941-v42-mkmlizer completed after 63.27s with status: succeeded
Stopping job with name nousresearch-meta-llama-4941-v42-mkmlizer
Pipeline stage MKMLizer completed in 67.94s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.09s
Running pipeline stage ISVCDeployer
Creating inference service nousresearch-meta-llama-4941-v42
Waiting for inference service nousresearch-meta-llama-4941-v42 to be ready
Inference service nousresearch-meta-llama-4941-v42 ready after 30.2000675201416s
Pipeline stage ISVCDeployer completed in 38.10s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.8522608280181885s
Received healthy response to inference request in 2.0009093284606934s
Received healthy response to inference request in 1.9377295970916748s
Received healthy response to inference request in 1.9317927360534668s
Received healthy response to inference request in 2.053985357284546s
5 requests
0 failed requests
5th percentile: 1.9329801082611084
10th percentile: 1.93416748046875
20th percentile: 1.9365422248840332
30th percentile: 1.9503655433654785
40th percentile: 1.975637435913086
50th percentile: 2.0009093284606934
60th percentile: 2.0221397399902346
70th percentile: 2.0433701515197753
80th percentile: 2.2136404514312744
90th percentile: 2.5329506397247314
95th percentile: 2.69260573387146
99th percentile: 2.8203298091888427
mean time: 2.155335569381714
Pipeline stage StressChecker completed in 11.60s
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 0.15s
M-Eval Dataset for topic stay_in_character is loaded
nousresearch-meta-llama_4941_v42 status is now deployed due to DeploymentManager action
nousresearch-meta-llama_4941_v42 status is now inactive due to auto deactivation removed underperforming models
admin requested tearing down of nousresearch-meta-llama_4941_v42
Running pipeline stage ISVCDeleter
Checking if service nousresearch-meta-llama-4941-v42 is running
Tearing down inference service nousresearch-meta-llama-4941-v42
Toredown service nousresearch-meta-llama-4941-v42
Pipeline stage ISVCDeleter completed in 3.74s
Running pipeline stage MKMLModelDeleter
Cleaning model data from S3
Cleaning model data from model cache
Deleting key nousresearch-meta-llama-4941-v42/config.json from bucket guanaco-mkml-models
Deleting key nousresearch-meta-llama-4941-v42/flywheel_model.0.safetensors from bucket guanaco-mkml-models
Deleting key nousresearch-meta-llama-4941-v42/special_tokens_map.json from bucket guanaco-mkml-models
Deleting key nousresearch-meta-llama-4941-v42/tokenizer.json from bucket guanaco-mkml-models
Deleting key nousresearch-meta-llama-4941-v42/tokenizer_config.json from bucket guanaco-mkml-models
Cleaning model data from model cache
Deleting key nousresearch-meta-llama-4941-v42_reward/config.json from bucket guanaco-reward-models
Deleting key nousresearch-meta-llama-4941-v42_reward/merges.txt from bucket guanaco-reward-models
Deleting key nousresearch-meta-llama-4941-v42_reward/reward.tensors from bucket guanaco-reward-models
Deleting key nousresearch-meta-llama-4941-v42_reward/special_tokens_map.json from bucket guanaco-reward-models
Deleting key nousresearch-meta-llama-4941-v42_reward/tokenizer.json from bucket guanaco-reward-models
Deleting key nousresearch-meta-llama-4941-v42_reward/tokenizer_config.json from bucket guanaco-reward-models
Deleting key nousresearch-meta-llama-4941-v42_reward/vocab.json from bucket guanaco-reward-models
Pipeline stage MKMLModelDeleter completed in 1.91s
nousresearch-meta-llama_4941_v42 status is now torndown due to DeploymentManager action

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