Understanding the output about finbert HOT 3 CLOSED

Let me know if the understanding is correct. for the first question:

1. Every column of model's output matrix is respectively an output class (positive [col1], negative [col2] and neutral [col3])

from finbert.

Let me know if the understanding is correct. for the first question:

1. Every column of model's output matrix is respectively an output class (positive [col1], negative [col2] and neutral [col3])

That is correct.

2. The sentiment score is one way to interpret the outcome. Subtract negative softmax value from the positive. We use it to transform the score into a continuous range from -1 to 1.

3. Could you explain a bit more what you mean by this?

from finbert.

Sure..
In case I provide only one sentence as input, the logits variable evaluates a 1x3 array; Following that we do an argmax which gives a 1x1 array with any one of following value in it (0, 1, 2). Then when we do np.squeeze in this 1x1 array to calculate predictions variable, it evaluates nothing..
Pardon me, cannot share a screenshot. Let me know if I could explain you the issue..

from finbert.