{
"results": {
"winogender": {
"acc,none": 0.51875,
"acc_stderr,none": 0.011417876682209652,
"alias": "winogender"
},
"winogender_all": {
"acc,none": 0.5222222222222223,
"acc_stderr,none": 0.018628427766624305,
"alias": " - winogender_all"
},
"winogender_female": {
"acc,none": 0.5208333333333334,
"acc_stderr,none": 0.032314224248709875,
"alias": " - winogender_female"
},
"winogender_gotcha": {
"acc,none": 0.5083333333333333,
"acc_stderr,none": 0.03233781906798062,
"alias": " - winogender_gotcha"
},
"winogender_gotcha_female": {
"acc,none": 0.55,
"acc_stderr,none": 0.04560517440787951,
"alias": " - winogender_gotcha_female"
},
"winogender_gotcha_male": {
"acc,none": 0.4666666666666667,
"acc_stderr,none": 0.0457329560380023,
"alias": " - winogender_gotcha_male"
},
"winogender_male": {
"acc,none": 0.5208333333333334,
"acc_stderr,none": 0.032314224248709875,
"alias": " - winogender_male"
},
"winogender_neutral": {
"acc,none": 0.525,
"acc_stderr,none": 0.0323018581793835,
"alias": " - winogender_neutral"
}
},
"groups": {
"winogender": {
"acc,none": 0.51875,
"acc_stderr,none": 0.011417876682209652,
"alias": "winogender"
}
},
"group_subtasks": {
"winogender": [
"winogender_female",
"winogender_all",
"winogender_male",
"winogender_gotcha",
"winogender_gotcha_male",
"winogender_neutral",
"winogender_gotcha_female"
]
},
"configs": {
"winogender_all": {
"task": "winogender_all",
"group": [
"social_bias",
"winogender"
],
"dataset_path": "oskarvanderwal/winogender",
"dataset_name": "all",
"test_split": "test",
"doc_to_text": "{{sentence}} ‘{{pronoun.capitalize()}}’ refers to the",
"doc_to_target": "label",
"doc_to_choice": "{{[occupation, participant]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"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,
"num_fewshot": 0
}
},
"winogender_female": {
"task": "winogender_female",
"group": [
"social_bias",
"winogender"
],
"dataset_path": "oskarvanderwal/winogender",
"dataset_name": "all",
"test_split": "test",
"process_docs": "def filter_female(dataset: datasets.Dataset) -> datasets.Dataset:\n return filter_dataset(dataset, \"female\")\n",
"doc_to_text": "{{sentence}} ‘{{pronoun.capitalize()}}’ refers to the",
"doc_to_target": "label",
"doc_to_choice": "{{[occupation, participant]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"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,
"num_fewshot": 0
}
},
"winogender_gotcha": {
"task": "winogender_gotcha",
"group": [
"social_bias",
"winogender"
],
"dataset_path": "oskarvanderwal/winogender",
"dataset_name": "gotcha",
"test_split": "test",
"doc_to_text": "{{sentence}} ‘{{pronoun.capitalize()}}’ refers to the",
"doc_to_target": "label",
"doc_to_choice": "{{[occupation, participant]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"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,
"num_fewshot": 0
}
},
"winogender_gotcha_female": {
"task": "winogender_gotcha_female",
"group": [
"social_bias",
"winogender"
],
"dataset_path": "oskarvanderwal/winogender",
"dataset_name": "gotcha",
"test_split": "test",
"process_docs": "def filter_female(dataset: datasets.Dataset) -> datasets.Dataset:\n return filter_dataset(dataset, \"female\")\n",
"doc_to_text": "{{sentence}} ‘{{pronoun.capitalize()}}’ refers to the",
"doc_to_target": "label",
"doc_to_choice": "{{[occupation, participant]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"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,
"num_fewshot": 0
}
},
"winogender_gotcha_male": {
"task": "winogender_gotcha_male",
"group": [
"social_bias",
"winogender"
],
"dataset_path": "oskarvanderwal/winogender",
"dataset_name": "gotcha",
"test_split": "test",
"process_docs": "def filter_male(dataset: datasets.Dataset) -> datasets.Dataset:\n return filter_dataset(dataset, \"male\")\n",
"doc_to_text": "{{sentence}} ‘{{pronoun.capitalize()}}’ refers to the",
"doc_to_target": "label",
"doc_to_choice": "{{[occupation, participant]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"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,
"num_fewshot": 0
}
},
"winogender_male": {
"task": "winogender_male",
"group": [
"social_bias",
"winogender"
],
"dataset_path": "oskarvanderwal/winogender",
"dataset_name": "all",
"test_split": "test",
"process_docs": "def filter_male(dataset: datasets.Dataset) -> datasets.Dataset:\n return filter_dataset(dataset, \"male\")\n",
"doc_to_text": "{{sentence}} ‘{{pronoun.capitalize()}}’ refers to the",
"doc_to_target": "label",
"doc_to_choice": "{{[occupation, participant]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"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,
"num_fewshot": 0
}
},
"winogender_neutral": {
"task": "winogender_neutral",
"group": [
"social_bias",
"winogender"
],
"dataset_path": "oskarvanderwal/winogender",
"dataset_name": "all",
"test_split": "test",
"process_docs": "def filter_neutral(dataset: datasets.Dataset) -> datasets.Dataset:\n return filter_dataset(dataset, \"neutral\")\n",
"doc_to_text": "{{sentence}} ‘{{pronoun.capitalize()}}’ refers to the",
"doc_to_target": "label",
"doc_to_choice": "{{[occupation, participant]}}",
"description": "",
"target_delimiter": " ",
"fewshot_delimiter": "\n\n",
"num_fewshot": 0,
"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,
"num_fewshot": 0
}
}
},
"versions": {
"winogender_all": 1.0,
"winogender_female": 1.0,
"winogender_gotcha": 1.0,
"winogender_gotcha_female": 1.0,
"winogender_gotcha_male": 1.0,
"winogender_male": 1.0,
"winogender_neutral": 1.0
},
"n-shot": {
"winogender": 0,
"winogender_all": 0,
"winogender_female": 0,
"winogender_gotcha": 0,
"winogender_gotcha_female": 0,
"winogender_gotcha_male": 0,
"winogender_male": 0,
"winogender_neutral": 0
},
"n-samples": {
"winogender_female": {
"original": 240,
"effective": 240
},
"winogender_all": {
"original": 720,
"effective": 720
},
"winogender_male": {
"original": 240,
"effective": 240
},
"winogender_gotcha": {
"original": 240,
"effective": 240
},
"winogender_gotcha_male": {
"original": 120,
"effective": 120
},
"winogender_neutral": {
"original": 240,
"effective": 240
},
"winogender_gotcha_female": {
"original": 120,
"effective": 120
}
},
"config": {
"model": "hf",
"model_args": "pretrained=EleutherAI/pythia-410m-seed3,revision=step118000",
"model_num_parameters": 405334016,
"model_dtype": "torch.float16",
"model_revision": "step118000",
"model_sha": "bfe4b744fcbe68297119acaf78c183a22f7bcb59",
"batch_size": "128",
"batch_sizes": [],
"device": "cuda",
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"limit": null,
"bootstrap_iters": 100000,
"gen_kwargs": null,
"random_seed": 0,
"numpy_seed": 1234,
"torch_seed": 1234,
"fewshot_seed": 1234
},
"git_hash": "51a7ca9",
"date": 1726040133.520794,
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"model_name": "EleutherAI/pythia-410m-seed3",
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}