def on_epoch_end(self, epoch, logs={}):
ypred = self.task.predict(self.model, self.val_gr)
acc = ev.binclass_accuracy(self.val_gr['score'], ypred)[0]
print(
' val acc %f'
% (acc, ))
logs['acc'] = acc
def on_epoch_end(self, epoch, logs={}):
ypred = self.task.predict(self.model, self.val_gr)
if 'qids' not in self.val_gr or self.val_gr['qids'] is None:
acc = ev.binclass_accuracy(self.val_gr['score'], ypred)[0]
print(' val acc %f' % (acc,))
else:
acc = ev.recall_at(self.val_gr['qids'], self.val_gr['score'], ypred, N=1)
print(' val abcdacc %f' % (acc,))
logs['acc'] = acc
def on_epoch_end(self, epoch, logs={}):
ypred = self.task.predict(self.model, self.val_gr)
tmp = []
for yp in ypred:
tmp.append(yp[0])
ypred = np.array(tmp)
acc, y0acc, y1acc, balacc, f_score = ev.binclass_accuracy(
self.val_gr['score'], ypred)
print(' val acc %f val f1 %f' % (acc, f_score))
logs['acc'] = acc
def on_epoch_end(self, epoch, logs={}):
ypred = self.task.predict(self.model, self.val_gr)
if 'qids' not in self.val_gr or self.val_gr['qids'] is None:
acc = ev.binclass_accuracy(self.val_gr['score'], ypred)[0]
print(
' val acc %f'
% (acc, ))
else:
acc = ev.recall_at(self.val_gr['qids'],
self.val_gr['score'],
ypred,
N=1)
print(
' val abcdacc %f'
% (acc, ))
logs['acc'] = acc
def on_epoch_end(self, epoch, logs={}):
ypred = self.model.predict(self.val_gr)['score'][:,0]
acc = ev.binclass_accuracy(self.val_gr['score'], ypred)[0]
print(' val acc %f' % (acc,))
logs['acc'] = acc