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authorZJaume <jzaragoza@prompsit.com>2021-11-04 13:28:07 +0300
committerZJaume <jzaragoza@prompsit.com>2021-11-04 13:29:51 +0300
commit6ed2240286ce7c297e6b087ad83c7b1b61a8d181 (patch)
tree78d5aa500a415d2e3c105416647f54af761c3d9c
parent6b8210efdebe8ef1e7c8d324c2610f4c4124e2ca (diff)
Add MCC as validation metric in XLMR, use default names for metrics
-rw-r--r--bicleaner_ai/metrics.py4
-rw-r--r--bicleaner_ai/models.py8
2 files changed, 6 insertions, 6 deletions
diff --git a/bicleaner_ai/metrics.py b/bicleaner_ai/metrics.py
index d995889..08838bd 100644
--- a/bicleaner_ai/metrics.py
+++ b/bicleaner_ai/metrics.py
@@ -13,7 +13,7 @@ class FScore(Metric):
thresholds=None,
top_k=None,
class_id=None,
- name=None,
+ name='f1',
dtype=None,
argmax=False):
super(FScore, self).__init__(name=name, dtype=dtype)
@@ -85,7 +85,7 @@ class MatthewsCorrCoef(Metric):
thresholds=None,
top_k=None,
class_id=None,
- name=None,
+ name='mcc',
dtype=None,
argmax=False):
super(MatthewsCorrCoef, self).__init__(name=name, dtype=dtype)
diff --git a/bicleaner_ai/models.py b/bicleaner_ai/models.py
index f6fa6ff..ac08139 100644
--- a/bicleaner_ai/models.py
+++ b/bicleaner_ai/models.py
@@ -193,8 +193,8 @@ class BaseModel(ModelInterface):
#TODO create argmax precision and recall or use categorical acc
#Precision(name='p'),
#Recall(name='r'),
- FScore(name='f1', argmax=self.settings["distilled"]),
- MatthewsCorrCoef(name='mcc', argmax=self.settings["distilled"]),
+ FScore(argmax=self.settings["distilled"]),
+ MatthewsCorrCoef(argmax=self.settings["distilled"]),
]
def get_generator(self, batch_size, shuffle):
@@ -574,8 +574,8 @@ class BCXLMRoberta(BaseModel):
self.model.compile(optimizer=self.settings["optimizer"],
loss=SparseCategoricalCrossentropy(
from_logits=True),
- metrics=[FScore(name='f1',
- argmax=True)])
+ metrics=[FScore(argmax=True),
+ MatthewsCorrCoef(argmax=True)])
if logging.getLogger().level == logging.DEBUG:
self.model.summary()
self.model.fit(train_generator,