submission_id: jellywibble-lora-120k-p_2801_v24
developer_uid: chai_backend_admin
alignment_samples: 0
best_of: 4
celo_rating: 1224.88
display_name: jellywibble-lora-120k-p_2801_v24
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}
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': 4, 'max_output_tokens': 64}
is_internal_developer: True
language_model: Jellywibble/lora_120k_pref_data_ep3_stacked_elo_alignment
max_input_tokens: 512
max_output_tokens: 64
model_architecture: LlamaForCausalLM
model_group: Jellywibble/lora_120k_pr
model_name: jellywibble-lora-120k-p_2801_v24
model_num_parameters: 8030261248.0
model_repo: Jellywibble/lora_120k_pref_data_ep3_stacked_elo_alignment
model_size: 8B
num_battles: 12471
num_wins: 6597
propriety_score: 0.7363560033585222
propriety_total_count: 1191.0
ranking_group: single
reward_formatter: {'bot_template': '{bot_name}: {message}\n', 'memory_template': "{bot_name}'s Persona: {memory}\n####\n", 'prompt_template': '{prompt}\n<START>\n', 'response_template': '{bot_name}:', 'truncate_by_message': False, 'user_template': '{user_name}: {message}\n'}
reward_repo: ChaiML/reward_gpt2_medium_preference_24m_e2
status: torndown
submission_type: basic
timestamp: 2024-07-23T03:39:08+00:00
us_pacific_date: 2024-07-22
win_ratio: 0.5289872504209767
Download Preference Data
Resubmit model
Running pipeline stage MKMLizer
Starting job with name jellywibble-lora-120k-p-2801-v24-mkmlizer
Waiting for job on jellywibble-lora-120k-p-2801-v24-mkmlizer to finish
jellywibble-lora-120k-p-2801-v24-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║     _____            __           __                                ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║       /___/                                                         ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║                                                                     ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║  Version: 0.9.5.post3                                               ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║  https://mk1.ai                                                     ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║                                                                     ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║  The license key for the current software has been verified as      ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║  belonging to:                                                      ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║                                                                     ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║  Chai Research Corp.                                                ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ║                                                                     ║
jellywibble-lora-120k-p-2801-v24-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
Failed to get response for submission chaiml-sao10k-l3-rp-v3-3_v46: ('http://chaiml-sao10k-l3-rp-v3-3-v46-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"TypeError : SamplingParameters.__init__() got an unexpected keyword argument \'reward_max_tokens\'"}')
jellywibble-lora-120k-p-2801-v24-mkmlizer: Downloaded to shared memory in 42.306s
jellywibble-lora-120k-p-2801-v24-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpnqtcd3je, device:0
jellywibble-lora-120k-p-2801-v24-mkmlizer: Saving flywheel model at /dev/shm/model_cache
jellywibble-lora-120k-p-2801-v24-mkmlizer: 
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Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
jellywibble-lora-120k-p-2801-v24-mkmlizer: quantized model in 25.054s
jellywibble-lora-120k-p-2801-v24-mkmlizer: Processed model Jellywibble/lora_120k_pref_data_ep3_stacked_elo_alignment in 67.361s
jellywibble-lora-120k-p-2801-v24-mkmlizer: creating bucket guanaco-mkml-models
jellywibble-lora-120k-p-2801-v24-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
jellywibble-lora-120k-p-2801-v24-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/jellywibble-lora-120k-p-2801-v24
jellywibble-lora-120k-p-2801-v24-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/jellywibble-lora-120k-p-2801-v24/config.json
jellywibble-lora-120k-p-2801-v24-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/jellywibble-lora-120k-p-2801-v24/special_tokens_map.json
jellywibble-lora-120k-p-2801-v24-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/jellywibble-lora-120k-p-2801-v24/tokenizer_config.json
jellywibble-lora-120k-p-2801-v24-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/jellywibble-lora-120k-p-2801-v24/tokenizer.json
jellywibble-lora-120k-p-2801-v24-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/jellywibble-lora-120k-p-2801-v24/flywheel_model.0.safetensors
jellywibble-lora-120k-p-2801-v24-mkmlizer: loading reward model from ChaiML/reward_gpt2_medium_preference_24m_e2
jellywibble-lora-120k-p-2801-v24-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py:950: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
jellywibble-lora-120k-p-2801-v24-mkmlizer:   warnings.warn(
jellywibble-lora-120k-p-2801-v24-mkmlizer: /opt/conda/lib/python3.10/site-packages/transformers/models/auto/tokenization_auto.py:778: FutureWarning: The `use_auth_token` argument is deprecated and will be removed in v5 of Transformers. Please use `token` instead.
jellywibble-lora-120k-p-2801-v24-mkmlizer:   warnings.warn(
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
jellywibble-lora-120k-p-2801-v24-mkmlizer: Saving model to /tmp/reward_cache/reward.tensors
jellywibble-lora-120k-p-2801-v24-mkmlizer: Saving duration: 0.340s
jellywibble-lora-120k-p-2801-v24-mkmlizer: Processed model ChaiML/reward_gpt2_medium_preference_24m_e2 in 6.068s
jellywibble-lora-120k-p-2801-v24-mkmlizer: creating bucket guanaco-reward-models
jellywibble-lora-120k-p-2801-v24-mkmlizer: Bucket 's3://guanaco-reward-models/' created
jellywibble-lora-120k-p-2801-v24-mkmlizer: uploading /tmp/reward_cache to s3://guanaco-reward-models/jellywibble-lora-120k-p-2801-v24_reward
jellywibble-lora-120k-p-2801-v24-mkmlizer: cp /tmp/reward_cache/config.json s3://guanaco-reward-models/jellywibble-lora-120k-p-2801-v24_reward/config.json
jellywibble-lora-120k-p-2801-v24-mkmlizer: cp /tmp/reward_cache/special_tokens_map.json s3://guanaco-reward-models/jellywibble-lora-120k-p-2801-v24_reward/special_tokens_map.json
jellywibble-lora-120k-p-2801-v24-mkmlizer: cp /tmp/reward_cache/tokenizer_config.json s3://guanaco-reward-models/jellywibble-lora-120k-p-2801-v24_reward/tokenizer_config.json
jellywibble-lora-120k-p-2801-v24-mkmlizer: cp /tmp/reward_cache/merges.txt s3://guanaco-reward-models/jellywibble-lora-120k-p-2801-v24_reward/merges.txt
jellywibble-lora-120k-p-2801-v24-mkmlizer: cp /tmp/reward_cache/vocab.json s3://guanaco-reward-models/jellywibble-lora-120k-p-2801-v24_reward/vocab.json
jellywibble-lora-120k-p-2801-v24-mkmlizer: cp /tmp/reward_cache/tokenizer.json s3://guanaco-reward-models/jellywibble-lora-120k-p-2801-v24_reward/tokenizer.json
jellywibble-lora-120k-p-2801-v24-mkmlizer: cp /tmp/reward_cache/reward.tensors s3://guanaco-reward-models/jellywibble-lora-120k-p-2801-v24_reward/reward.tensors
Job jellywibble-lora-120k-p-2801-v24-mkmlizer completed after 106.81s with status: succeeded
Stopping job with name jellywibble-lora-120k-p-2801-v24-mkmlizer
Pipeline stage MKMLizer completed in 107.96s
Running pipeline stage MKMLKubeTemplater
Pipeline stage MKMLKubeTemplater completed in 0.08s
Running pipeline stage ISVCDeployer
Creating inference service jellywibble-lora-120k-p-2801-v24
Waiting for inference service jellywibble-lora-120k-p-2801-v24 to be ready
Inference service jellywibble-lora-120k-p-2801-v24 ready after 50.4980788230896s
Pipeline stage ISVCDeployer completed in 53.03s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.1595168113708496s
Received healthy response to inference request in 1.1115434169769287s
Received healthy response to inference request in 1.1358842849731445s
Received healthy response to inference request in 1.109372854232788s
Received healthy response to inference request in 1.1051676273345947s
5 requests
0 failed requests
5th percentile: 1.1060086727142333
10th percentile: 1.1068497180938721
20th percentile: 1.1085318088531495
30th percentile: 1.1098069667816162
40th percentile: 1.1106751918792725
50th percentile: 1.1115434169769287
60th percentile: 1.121279764175415
70th percentile: 1.1310161113739015
80th percentile: 1.3406107902526858
90th percentile: 1.7500638008117677
95th percentile: 1.9547903060913083
99th percentile: 2.118571510314941
mean time: 1.3242969989776612
Pipeline stage StressChecker completed in 7.26s
jellywibble-lora-120k-p_2801_v24 status is now deployed due to DeploymentManager action
jellywibble-lora-120k-p_2801_v24 status is now inactive due to auto deactivation removed underperforming models
admin requested tearing down of jellywibble-lora-120k-p_2801_v24
Running pipeline stage ISVCDeleter
Checking if service jellywibble-lora-120k-p-2801-v24 is running
Tearing down inference service jellywibble-lora-120k-p-2801-v24
Service jellywibble-lora-120k-p-2801-v24 has been torndown
Pipeline stage ISVCDeleter completed in 4.40s
Running pipeline stage MKMLModelDeleter
Cleaning model data from S3
Cleaning model data from model cache
Deleting key jellywibble-lora-120k-p-2801-v24/config.json from bucket guanaco-mkml-models
Deleting key jellywibble-lora-120k-p-2801-v24/flywheel_model.0.safetensors from bucket guanaco-mkml-models
Deleting key jellywibble-lora-120k-p-2801-v24/special_tokens_map.json from bucket guanaco-mkml-models
Deleting key jellywibble-lora-120k-p-2801-v24/tokenizer.json from bucket guanaco-mkml-models
Deleting key jellywibble-lora-120k-p-2801-v24/tokenizer_config.json from bucket guanaco-mkml-models
Cleaning model data from model cache
Deleting key jellywibble-lora-120k-p-2801-v24_reward/config.json from bucket guanaco-reward-models
Deleting key jellywibble-lora-120k-p-2801-v24_reward/merges.txt from bucket guanaco-reward-models
Deleting key jellywibble-lora-120k-p-2801-v24_reward/reward.tensors from bucket guanaco-reward-models
Deleting key jellywibble-lora-120k-p-2801-v24_reward/special_tokens_map.json from bucket guanaco-reward-models
Deleting key jellywibble-lora-120k-p-2801-v24_reward/tokenizer.json from bucket guanaco-reward-models
Deleting key jellywibble-lora-120k-p-2801-v24_reward/tokenizer_config.json from bucket guanaco-reward-models
Deleting key jellywibble-lora-120k-p-2801-v24_reward/vocab.json from bucket guanaco-reward-models
Pipeline stage MKMLModelDeleter completed in 5.26s
jellywibble-lora-120k-p_2801_v24 status is now torndown due to DeploymentManager action

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