High Number of Tokens for openai-completions Models

[selinaxiao]

I created the config file with hard-coded prompts to try out gpt-3.5-turbo on 5 examples, but the number of tokens is exceedingly high for this config file. What should I do to reduce the number of tokens?
The following is my config file:

task: newyorker_caption_contest_zeroshot
dataset_path: csv
dataset_path: selinax10010/matching 
dataset_name: null 
dataset_kwargs: null 
output_type: multiple_choice
training_split: train 
validation_split: validation 
test_split: test 
process_docs: !function utils.process_docs
description: "role: system\nYou are CaptionContestGPT, an expert language model at understanding \
the famous New Yorker caption contest. You follow the contest each week, and \
understand what makes for a humorous caption for each cartoon. You are aware of\
the various theories of humor, and read/anaylze the caption contest entries and \
winners each week.\n\nSome things to remember:\n\n- You're well versed in the \
history of the New Yorker Caption contest, and the types of captions that are \
selected as finalists/winners vs. those that are not.\n- Provide the answer in \
the requested format. \n~~~\nrole: user\nI will describe a New Yorker cartoon \
to you. Then, I will give you 5 choices (labelled A-E) for captions. One of the \
captions was the winning caption for that cartoon, the other captions do not \
correspond to this cartoon. Your job is to find the correct match and respond \
with \"Answer: X\" where X is either A, B, C, D, or E.\n\n\n"
doc_to_text: "{{query}}\nChoices:\nA: {{choices_text[0]}}\nB: {{choices_text[1]}}\nC: \
{{choices_text[2]}}\nD: {{choices_text[3]}}\nE: {{choices_text[4]}}\n\nWhich of the 5 options \
(A, B, C, D, or E) is the caption that truly corresponds to the cartoon?\n~~~"
doc_to_target: "{{label}}"
doc_to_choice: "{{choices}}"
num_fewshot: 0
metric_list:
  - metric: acc
    aggregation: mean
    higher_is_better: true
  - metric: acc_norm
    aggregation: mean
    higher_is_better: true
  - metric: mcc
    aggregation: matthews_corrcoef
    higher_is_better: true
metadata:
  version: 1.0