I am unable to get this gradient descent solution correct

Question

Consider a linear-regression model with N=3 and D=1 with input-output pairs as follows:

yl=22, x 1=1, y2=3, x2=1, y3=3, x3=2

What is the gradient of mean-square error (MSE) with respect to B1 (when Bo=0 and B1=1? Give your answer correct to two decimal digits.

Answer 1

MSE Loss = sum((h - y) ** 2) / 2m

Gradient wrt b1 will be sum[(h - y) . x)] / m:

hypothesis: h = b0 + b1.x

for b0 = 0, b1 = 1:

h = x

input(x)        : [  1,  1,  2]

prediction(h)   : [  1,  1,  2]

Ground truth(y) : [ 22,  3,  3]

h - y           : [-21, -2, -1]

(h - y). x      : [-21, -2, -2]

gradient(b1)    : (-21 - 2 - 2) / 3 = -25 / 3 = -8.3333