No, your model still isn’t learning. The loss is still extremely noisy. The parameters that you can look into are:

Number of Hidden Layers.
Number of Neurons in the Hidden Layers.
Batch Sizes.
Add Dropout Layers in the Network
Optimizers (and their parameters like learn rate, weight decay, etc).

Do all of the above only on the small subset of data. The goal is to overfit the model on this tiny batch.
Losses1465×2507 190 KB
I’ve attached an image from one of my projects. As you can see, it is still noisy, but there is a definite decrease. This is the kind of curve you should expect.