Commit 601be343 authored by Baber's avatar Baber
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Merge branch 'main' into feature/eval_from_config

parents d0884a96 68c3a811
# Generated by utils.py
dataset_name: orm
doc_to_text: "You are an expert in Natural Language Inference (NLI) specializing in\
\ the Oromo language.\nAnalyze the premise and hypothesis given in Oromo, and determine\
\ the relationship between them.\n Respond with one of the following options: 'entailment',\
\ 'contradiction', or 'neutral'. \n\nPremise: {{premise}} \nHypothesis: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_orm_prompt_4
# Generated by utils.py
dataset_name: sna
doc_to_text: "You are an expert in Natural Language Inference (NLI) specializing in\
\ the chiShona language.\nAnalyze the premise and hypothesis given in chiShona,\
\ and determine the relationship between them.\n Respond with one of the following\
\ options: 'entailment', 'contradiction', or 'neutral'. \n\nPremise: {{premise}}\
\ \nHypothesis: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_sna_prompt_4
# Generated by utils.py
dataset_name: sot
doc_to_text: "You are an expert in Natural Language Inference (NLI) specializing in\
\ the Sesotho language.\nAnalyze the premise and hypothesis given in Sesotho, and\
\ determine the relationship between them.\n Respond with one of the following options:\
\ 'entailment', 'contradiction', or 'neutral'. \n\nPremise: {{premise}} \nHypothesis:\
\ {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_sot_prompt_4
# Generated by utils.py
dataset_name: swa
doc_to_text: "You are an expert in Natural Language Inference (NLI) specializing in\
\ the Swahili language.\nAnalyze the premise and hypothesis given in Swahili, and\
\ determine the relationship between them.\n Respond with one of the following options:\
\ 'entailment', 'contradiction', or 'neutral'. \n\nPremise: {{premise}} \nHypothesis:\
\ {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_swa_prompt_4
# Generated by utils.py
dataset_name: twi
doc_to_text: "You are an expert in Natural Language Inference (NLI) specializing in\
\ the Twi language.\nAnalyze the premise and hypothesis given in Twi, and determine\
\ the relationship between them.\n Respond with one of the following options: 'entailment',\
\ 'contradiction', or 'neutral'. \n\nPremise: {{premise}} \nHypothesis: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_twi_prompt_4
# Generated by utils.py
dataset_name: wol
doc_to_text: "You are an expert in Natural Language Inference (NLI) specializing in\
\ the Wolof language.\nAnalyze the premise and hypothesis given in Wolof, and determine\
\ the relationship between them.\n Respond with one of the following options: 'entailment',\
\ 'contradiction', or 'neutral'. \n\nPremise: {{premise}} \nHypothesis: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_wol_prompt_4
# Generated by utils.py
dataset_name: xho
doc_to_text: "You are an expert in Natural Language Inference (NLI) specializing in\
\ the isiXhosa language.\nAnalyze the premise and hypothesis given in isiXhosa,\
\ and determine the relationship between them.\n Respond with one of the following\
\ options: 'entailment', 'contradiction', or 'neutral'. \n\nPremise: {{premise}}\
\ \nHypothesis: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_xho_prompt_4
tag:
- afrixnli_tasks
- afrixnli_tasks_prompt_4
dataset_path: masakhane/afrixnli
dataset_name: null
output_type: multiple_choice
validation_split: validation
test_split: test
fewshot_split: validation
doc_to_target: !function utils.doc_to_target
doc_to_choice:
- "entailment"
- "neutral"
- "contradiction"
should_decontaminate: true
doc_to_decontamination_query: premise
metric_list:
- metric: f1
aggregation: !function utils.weighted_f1_score
average: weighted
higher_is_better: True
ignore_case: true
ignore_punctuation: true
- metric: acc
aggregation: mean
higher_is_better: true
ignore_case: true
ignore_punctuation: true
metadata:
version: 1.0
# Generated by utils.py
dataset_name: yor
doc_to_text: "You are an expert in Natural Language Inference (NLI) specializing in\
\ the Yoruba language.\nAnalyze the premise and hypothesis given in Yoruba, and\
\ determine the relationship between them.\n Respond with one of the following options:\
\ 'entailment', 'contradiction', or 'neutral'. \n\nPremise: {{premise}} \nHypothesis:\
\ {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_yor_prompt_4
# Generated by utils.py
dataset_name: zul
doc_to_text: "You are an expert in Natural Language Inference (NLI) specializing in\
\ the Zulu language.\nAnalyze the premise and hypothesis given in Zulu, and determine\
\ the relationship between them.\n Respond with one of the following options: 'entailment',\
\ 'contradiction', or 'neutral'. \n\nPremise: {{premise}} \nHypothesis: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_zul_prompt_4
from lm_eval.utils import weighted_f1_score
def doc_to_text(doc):
output = """Please identify whether the premise entails or contradicts the hypothesis in the following premise
and hypothesis. The answer should be exact entailment, contradiction, or neutral.
Premise: {premise}
Hypothesis: {hypothesis}
Is it entailment, contradiction, or neutral?"""
text = output.format(premise=doc["premise"], hypothesis=doc["hypothesis"])
return text
def doc_to_target(doc):
replacements = {0: "entailment", 1: "neutral", 2: "contradiction"}
return replacements[doc["label"]]
# Generated by utils.py
dataset_name: amh
doc_to_text: "Based on the given statement, is the following claim 'true', 'false',\
\ or 'inconclusive'. \nStatement: {{premise}} \nClaim: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_amh_prompt_5
# Generated by utils.py
dataset_name: eng
doc_to_text: "Based on the given statement, is the following claim 'true', 'false',\
\ or 'inconclusive'. \nStatement: {{premise}} \nClaim: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_eng_prompt_5
# Generated by utils.py
dataset_name: ewe
doc_to_text: "Based on the given statement, is the following claim 'true', 'false',\
\ or 'inconclusive'. \nStatement: {{premise}} \nClaim: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_ewe_prompt_5
# Generated by utils.py
dataset_name: fra
doc_to_text: "Based on the given statement, is the following claim 'true', 'false',\
\ or 'inconclusive'. \nStatement: {{premise}} \nClaim: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_fra_prompt_5
# Generated by utils.py
dataset_name: hau
doc_to_text: "Based on the given statement, is the following claim 'true', 'false',\
\ or 'inconclusive'. \nStatement: {{premise}} \nClaim: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_hau_prompt_5
# Generated by utils.py
dataset_name: ibo
doc_to_text: "Based on the given statement, is the following claim 'true', 'false',\
\ or 'inconclusive'. \nStatement: {{premise}} \nClaim: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_ibo_prompt_5
# Generated by utils.py
dataset_name: kin
doc_to_text: "Based on the given statement, is the following claim 'true', 'false',\
\ or 'inconclusive'. \nStatement: {{premise}} \nClaim: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_kin_prompt_5
# Generated by utils.py
dataset_name: lin
doc_to_text: "Based on the given statement, is the following claim 'true', 'false',\
\ or 'inconclusive'. \nStatement: {{premise}} \nClaim: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_lin_prompt_5
# Generated by utils.py
dataset_name: lug
doc_to_text: "Based on the given statement, is the following claim 'true', 'false',\
\ or 'inconclusive'. \nStatement: {{premise}} \nClaim: {{hypothesis}}"
include: afrixnli_yaml
task: afrixnli_lug_prompt_5
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