lmms_eval/tasks/coco_cap/coco2014_cap_val.yaml (41 lines of code) (raw):

dataset_path: lmms-lab/COCO-Caption dataset_kwargs: token: True task: "coco2014_cap_val" group : "coco_caption" test_split: val output_type: generate_until doc_to_visual: !function utils.coco_doc_to_visual doc_to_text: "Provide a one-sentence caption for the provided image." doc_to_target: "answer" generation_kwargs: max_new_tokens: 64 temperature: 0 top_p: 0 num_beams: 1 do_sample: false process_results: !function utils.coco_process_result # 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: coco_Bleu_4 aggregation : !function utils.coco_bleu4 higher_is_better : true - metric: coco_Bleu_3 aggregation : !function utils.coco_bleu3 higher_is_better : true - metric: coco_Bleu_2 aggregation : !function utils.coco_bleu2 higher_is_better : true - metric: coco_Bleu_1 aggregation : !function utils.coco_bleu1 higher_is_better : true - metric: coco_METEOR aggregation : !function utils.coco_meteor higher_is_better : true - metric: coco_ROUGE_L aggregation : !function utils.coco_rougel higher_is_better : true - metric: coco_CIDEr aggregation : !function utils.coco_cider higher_is_better : true #- metric: coco_SPICE # aggregation : !function utils.coco_spice # higher_is_better : true metadata: - version: 0.0