diff --git a/insurance_qa_eval.py b/insurance_qa_eval.py
index bd643bf..9284587 100644
--- a/insurance_qa_eval.py
+++ b/insurance_qa_eval.py
@@ -136,7 +136,7 @@ class Evaluator:
if hist.history['val_loss'][0] < val_loss['loss']:
val_loss = {'loss': hist.history['val_loss'][0], 'epoch': i}
log('%s -- Epoch %d ' % (self.get_time(), i) +
- 'Loss = %.4f ' % hist.history['val_loss'][0] +
+ 'Loss = %.4f, Validation Loss = %.4f ' % (hist.history['loss'][0], hist.history['val_loss'][0]) +
'(Best: Loss = %.4f, Epoch = %d)' % (val_loss['loss'], val_loss['epoch']))
self.save_epoch(i)
@@ -207,6 +207,26 @@ class Evaluator:
if __name__ == '__main__':
+ if len(sys.argv) >= 2 and sys.argv[1] == 'serve':
+ from flask import Flask
+ app = Flask(__name__)
+ port = 5000
+ lines = list()
+ def log(x):
+ lines.append(x)
+
+ @app.route('/')
+ def home():
+ return ('Training Log
' +
+ ''.join(['{}
'.format(line) for line in lines]) +
+ '')
+
+ def start_server():
+ app.run(debug=False, use_evalex=False, port=port)
+
+ thread.start_new_thread(start_server, tuple())
+ print('Serving to port %d' % port, file=sys.stderr)
+
import numpy as np
conf = {
@@ -230,26 +250,6 @@ if __name__ == '__main__':
}
}
- if len(sys.argv) >= 2 and sys.argv[1] == 'serve':
- from flask import Flask
- app = Flask(__name__)
- port = 5000
- lines = list()
- def log(x):
- lines.append(x)
-
- @app.route('/')
- def home():
- return ('Training Log
' +
- ''.join(['{}
'.format(line) for line in lines]) +
- '')
-
- def start_server():
- app.run(debug=False, use_evalex=False, port=port)
-
- thread.start_new_thread(start_server, tuple())
- print('Serving to port %d' % port, file=sys.stderr)
-
from keras_models import AttentionModel
evaluator = Evaluator(conf, model=AttentionModel, optimizer='rmsprop')