📄 Source: GoogleCloudAiplatformV1SchemaModelevaluationMetricsPairwiseTextGenerationEvaluationMetrics.php
<?php
/*
* Copyright 2014 Google Inc.
*
* Licensed under the Apache License, Version 2.0 (the "License"); you may not
* use this file except in compliance with the License. You may obtain a copy of
* the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
* WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
* License for the specific language governing permissions and limitations under
* the License.
*/
namespace Google\Service\Aiplatform;
class GoogleCloudAiplatformV1SchemaModelevaluationMetricsPairwiseTextGenerationEvaluationMetrics extends \Google\Model
{
/**
* Fraction of cases where the autorater agreed with the human raters.
*
* @var float
*/
public $accuracy;
/**
* Percentage of time the autorater decided the baseline model had the better
* response.
*
* @var float
*/
public $baselineModelWinRate;
/**
* A measurement of agreement between the autorater and human raters that
* takes the likelihood of random agreement into account.
*
* @var float
*/
public $cohensKappa;
/**
* Harmonic mean of precision and recall.
*
* @var float
*/
public $f1Score;
/**
* Number of examples where the autorater chose the baseline model, but humans
* preferred the model.
*
* @var string
*/
public $falseNegativeCount;
/**
* Number of examples where the autorater chose the model, but humans
* preferred the baseline model.
*
* @var string
*/
public $falsePositiveCount;
/**
* Percentage of time humans decided the baseline model had the better
* response.
*
* @var float
*/
public $humanPreferenceBaselineModelWinRate;
/**
* Percentage of time humans decided the model had the better response.
*
* @var float
*/
public $humanPreferenceModelWinRate;
/**
* Percentage of time the autorater decided the model had the better response.
*
* @var float
*/
public $modelWinRate;
/**
* Fraction of cases where the autorater and humans thought the model had a
* better response out of all cases where the autorater thought the model had
* a better response. True positive divided by all positive.
*
* @var float
*/
public $precision;
/**
* Fraction of cases where the autorater and humans thought the model had a
* better response out of all cases where the humans thought the model had a
* better response.
*
* @var float
*/
public $recall;
/**
* Number of examples where both the autorater and humans decided that the
* model had the worse response.
*
* @var string
*/
public $trueNegativeCount;
/**
* Number of examples where both the autorater and humans decided that the
* model had the better response.
*
* @var string
*/
public $truePositiveCount;
/**
* Fraction of cases where the autorater agreed with the human raters.
*
* @param float $accuracy
*/
public function setAccuracy($accuracy)
{
$this->accuracy = $accuracy;
}
/**
* @return float
*/
public function getAccuracy()
{
return $this->accuracy;
}
/**
* Percentage of time the autorater decided the baseline model had the better
* response.
*
* @param float $baselineModelWinRate
*/
public function setBaselineModelWinRate($baselineModelWinRate)
{
$this->baselineModelWinRate = $baselineModelWinRate;
}
/**
* @return float
*/
public function getBaselineModelWinRate()
{
return $this->baselineModelWinRate;
}
/**
* A measurement of agreement between the autorater and human raters that
* takes the likelihood of random agreement into account.
*
* @param float $cohensKappa
*/
public function setCohensKappa($cohensKappa)
{
$this->cohensKappa = $cohensKappa;
}
/**
* @return float
*/
public function getCohensKappa()
{
return $this->cohensKappa;
}
/**
* Harmonic mean of precision and recall.
*
* @param float $f1Score
*/
public function setF1Score($f1Score)
{
$this->f1Score = $f1Score;
}
/**
* @return float
*/
public function getF1Score()
{
return $this->f1Score;
}
/**
* Number of examples where the autorater chose the baseline model, but humans
* preferred the model.
*
* @param string $falseNegativeCount
*/
public function setFalseNegativeCount($falseNegativeCount)
{
$this->falseNegativeCount = $falseNegativeCount;
}
/**
* @return string
*/
public function getFalseNegativeCount()
{
return $this->falseNegativeCount;
}
/**
* Number of examples where the autorater chose the model, but humans
* preferred the baseline model.
*
* @param string $falsePositiveCount
*/
public function setFalsePositiveCount($falsePositiveCount)
{
$this->falsePositiveCount = $falsePositiveCount;
}
/**
* @return string
*/
public function getFalsePositiveCount()
{
return $this->falsePositiveCount;
}
/**
* Percentage of time humans decided the baseline model had the better
* response.
*
* @param float $humanPreferenceBaselineModelWinRate
*/
public function setHumanPreferenceBaselineModelWinRate($humanPreferenceBaselineModelWinRate)
{
$this->humanPreferenceBaselineModelWinRate = $humanPreferenceBaselineModelWinRate;
}
/**
* @return float
*/
public function getHumanPreferenceBaselineModelWinRate()
{
return $this->humanPreferenceBaselineModelWinRate;
}
/**
* Percentage of time humans decided the model had the better response.
*
* @param float $humanPreferenceModelWinRate
*/
public function setHumanPreferenceModelWinRate($humanPreferenceModelWinRate)
{
$this->humanPreferenceModelWinRate = $humanPreferenceModelWinRate;
}
/**
* @return float
*/
public function getHumanPreferenceModelWinRate()
{
return $this->humanPreferenceModelWinRate;
}
/**
* Percentage of time the autorater decided the model had the better response.
*
* @param float $modelWinRate
*/
public function setModelWinRate($modelWinRate)
{
$this->modelWinRate = $modelWinRate;
}
/**
* @return float
*/
public function getModelWinRate()
{
return $this->modelWinRate;
}
/**
* Fraction of cases where the autorater and humans thought the model had a
* better response out of all cases where the autorater thought the model had
* a better response. True positive divided by all positive.
*
* @param float $precision
*/
public function setPrecision($precision)
{
$this->precision = $precision;
}
/**
* @return float
*/
public function getPrecision()
{
return $this->precision;
}
/**
* Fraction of cases where the autorater and humans thought the model had a
* better response out of all cases where the humans thought the model had a
* better response.
*
* @param float $recall
*/
public function setRecall($recall)
{
$this->recall = $recall;
}
/**
* @return float
*/
public function getRecall()
{
return $this->recall;
}
/**
* Number of examples where both the autorater and humans decided that the
* model had the worse response.
*
* @param string $trueNegativeCount
*/
public function setTrueNegativeCount($trueNegativeCount)
{
$this->trueNegativeCount = $trueNegativeCount;
}
/**
* @return string
*/
public function getTrueNegativeCount()
{
return $this->trueNegativeCount;
}
/**
* Number of examples where both the autorater and humans decided that the
* model had the better response.
*
* @param string $truePositiveCount
*/
public function setTruePositiveCount($truePositiveCount)
{
$this->truePositiveCount = $truePositiveCount;
}
/**
* @return string
*/
public function getTruePositiveCount()
{
return $this->truePositiveCount;
}
}
// Adding a class alias for backwards compatibility with the previous class name.
class_alias(GoogleCloudAiplatformV1SchemaModelevaluationMetricsPairwiseTextGenerationEvaluationMetrics::class, 'Google_Service_Aiplatform_GoogleCloudAiplatformV1SchemaModelevaluationMetricsPairwiseTextGenerationEvaluationMetrics');
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