Voyage / results_winogrande.json
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{
"results": {
"winogrande": {
"acc,none": 0.7655880031570639,
"acc_stderr,none": 0.011906130106237992,
"alias": "winogrande"
}
},
"configs": {
"winogrande": {
"task": "winogrande",
"dataset_path": "/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/eval/winogrande",
"dataset_name": "winogrande_xl",
"training_split": "train",
"validation_split": "validation",
"doc_to_text": "def doc_to_text(doc):\n answer_to_num = {\"1\": 0, \"2\": 1}\n return answer_to_num[doc[\"answer\"]]\n",
"doc_to_target": "def doc_to_target(doc):\n idx = doc[\"sentence\"].index(\"_\") + 1\n return doc[\"sentence\"][idx:].strip()\n",
"doc_to_choice": "def doc_to_choice(doc):\n idx = doc[\"sentence\"].index(\"_\")\n options = [doc[\"option1\"], doc[\"option2\"]]\n return [doc[\"sentence\"][:idx] + opt for opt in options]\n",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 5,
"metric_list": [
{
"metric": "acc",
"aggregation": "mean",
"higher_is_better": true
}
],
"output_type": "multiple_choice",
"repeats": 1,
"should_decontaminate": true,
"doc_to_decontamination_query": "sentence",
"metadata": {
"version": 1.0
}
}
},
"versions": {
"winogrande": 1.0
},
"n-shot": {
"winogrande": 5
},
"config": {
"model": "vllm",
"model_args": "pretrained=/lustre07/scratch/gagan30/arocr/meta-llama/self_rewarding_models/Voyage-dpo-1,tensor_parallel_size=1,dtype=auto,gpu_memory_utilization=0.9,data_parallel_size=1,max_model_len=4096",
"batch_size": "auto:128",
"batch_sizes": [],
"device": "cuda",
"use_cache": "/lustre07/scratch/gagan30/arocr/cache/",
"limit": null,
"bootstrap_iters": 100000,
"gen_kwargs": null
},
"git_hash": null
}