<jupyter_start><jupyter_text>Accuracy<jupyter_code>fig=plt.figure(figsize=(10,10))
plt.plot(train_accs, 'b')
plt.plot(val_accs, 'r')
plt.savefig('accuracy.png', dpi = 300)
np.array(val_accs).argmax()
val_accs[18]
val_accs[47]
val_accs[21]<jupyter_output><empty_output><jupyter_text>Brier score<jupyter_code>fig=plt.figure(figsize=(10,10))
plt.plot(train_briers, 'b')
plt.plot(valid_briers, 'r')
plt.savefig('Briers.png', dpi = 300)
np.argmin(train_briers)
np.argmin(valid_briers)<jupyter_output><empty_output><jupyter_text>Cross EntropyGot NAN values after 10 epochs<jupyter_code>fig=plt.figure(figsize=(10,10))
plt.plot(train_cross_entropys, 'b')
plt.plot(val_cross_entropys, 'r')
plt.savefig('cross entropy.png', dpi = 300)<jupyter_output><empty_output><jupyter_text>Adapted ECE<jupyter_code>fig=plt.figure(figsize=(10,10))
plt.plot(train_adapt_eces, 'b')
plt.plot(val_adapt_eces, 'r')
plt.savefig('Adapted ECE.png', dpi = 300)
np.argmin(train_adapt_eces)
np.argmin(val_adapt_eces)<jupyter_output><empty_output><jupyter_text>RMSE adapted ECE<jupyter_code>fig=plt.figure(figsize=(10,10))
plt.plot(train_adapt_rmse_eces, 'b')
plt.plot(val_adapt_rmse_eces, 'r')
plt.savefig('RMSE Adapted ECE.png', dpi = 300)
np.argmin(train_adapt_rmse_eces)
np.argmin(val_adapt_rmse_eces)<jupyter_output><empty_output><jupyter_text>ECE<jupyter_code>fig=plt.figure(figsize=(10,10))
plt.plot(train_eces, 'b')
plt.plot(val_eces, 'r')
plt.savefig('ece.png', dpi = 300)<jupyter_output><empty_output><jupyter_text>Absolute Calibration<jupyter_code>fig=plt.figure(figsize=(10,10))
plt.plot(train_abs_calibration, 'b')
plt.plot(valid_abs_calibration, 'r')
plt.savefig('Absolute Calibration.png', dpi = 300)
np.array(valid_abs_calibration).argmin()
np.array(train_abs_calibration).argmin()<jupyter_output><empty_output><jupyter_text>MCE<jupyter_code>fig=plt.figure(figsize=(10,10))
plt.plot(train_max_eces, 'b')
plt.plot(val_max_eces, 'r')
plt.savefig('mce.png', dpi = 300)<jupyter_output><empty_output><jupyter_text>MSE Calibration<jupyter_code>fig=plt.figure(figsize=(10,10))
plt.plot(train_mse_calibration, 'b')
plt.plot(valid_mse_calibration, 'r')
plt.savefig('MSE Calibration.png', dpi = 300)
np.array(valid_abs_calibration).argmin()
np.array(train_abs_calibration).argmin()<jupyter_output><empty_output>
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