dataset_name: "Object_affordance"
task: "egothink_affordance"
output_type: generate_until
doc_to_visual: !function utils.egothink_doc_to_visual
doc_to_text: !function utils.egothink_doc_to_text
doc_to_target: !function utils.egothink_doc_to_answer
generation_kwargs:
  max_new_tokens: 30
  temperature: 0.2
  num_beams: 1
  do_sample: True
# 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: gpt_eval_score
    aggregation: !function utils.egothink_aggregate_results
    higher_is_better: true
# The return value of process_results will be used by metrics
process_results: !function utils.egothink_process_results

lmms_eval_specific_kwargs:
    default:
          pre_prompt: ""
          post_prompt: ""
include: _default_template_yaml