dataset_path: CaraJ/MME-CoT
dataset_kwargs:
  token: True
task: "mme_cot_direct"
test_split: test
output_type: generate_until
doc_to_visual: !function utils.mmecot_doc_to_visual
doc_to_text: !function utils.mmecot_doc_to_text
doc_to_target: "answer"
generation_kwargs:
  max_new_tokens: 8192
  temperature: 0
  top_p: 0.95
  num_beams: 1
  do_sample: false
# The return value of process_results will be used by metrics
process_results: !function utils.mmecot_process_results
# Note that the metric name can be either a registed metric function (such as the case for GQA) or a key name returned by process_results
metric_list:
  - metric: submission
    aggregation: !function utils.mmecot_direct_aggregate_results
    higher_is_better: true

lmms_eval_specific_kwargs:
  default:
    postfix_type: "direct"

metadata:
  - version: 0.0
