Tensorflow not using GPU for one dataset, where it does for a very similar dataset

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I'm using TensorFlow to train a model using data originating from two sources. For both sources the training and validation data shape are almost identical and the dtypes throughout are np.float32.

The strange thing is, when I use the first data set the GPU on my machine is used, but when using the second data set the GPU is not used.

Does anyone have some suggestions on how to investigate?

print(s1_train_data.shape)
print(s1_train_data.values)
(1165032, 941)
[[ 0.45031181 -0.99680316  0.63686389 ...,  0.22323072 -0.37929842  0.        ]
 [-0.40660214  0.34022757 -0.00710014 ..., -1.43051076 -0.14785887  1.        ]
 [ 0.03955967 -0.91227823  0.37887612 ...,  0.16451506 -1.02560401  0.        ]
 ..., 
 [ 0.11746094 -0.18229018  0.43319091 ...,  0.36532226 -0.48208624  0.        ]
 [ 0.110379   -1.07364404  0.42837444 ...,  0.74732345  0.92880726  0.        ]
 [-0.81027234 -1.04290771 -0.56407243 ...,  0.25084609 -0.1797282   1.        ]]

print(s2_train_data.shape)
print(s2_train_data.values)
(559873, 941)
[[ 0.          0.          0.         ..., -1.02008295  0.27371082  0.        ]
 [ 0.          0.          0.         ..., -0.74775815  0.18743835  0.        ]
 [ 0.          0.          0.         ...,  0.6469788   0.67864949  1.        ]
 ..., 
 [ 0.          0.          0.         ..., -0.88198501 -0.02421325  1.        ]
 [ 0.          0.          0.         ...,  0.28361112 -1.08478808  1.        ]
 [ 0.          0.          0.         ...,  0.22360609  0.50698668  0.        ]]

asked 38 secs ago

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Tensorflow not using GPU for one dataset, where it does for a very similar dataset