Rasterize doesn't preserves the class attributes original values

I’m using this GDAL based rasterize function in python in order to create raster from shapefile based on numerical class values.

I am using:
function of GDALMy class attributes are very long numbers :

so I use those clases for the rasterizing as following (the code is from here: https://pcjericks.github.io/py-gdalogr-cookbook/raster_layers.html):

#Rasterize function
def rasterise_me(raster, vector, attribute,
                fname_out="", format="MEM"):
    """Rasterises a vector dataset by attribute to match a given
    raster dataset. This functions allows for the raster and vector
    to have different projections, and will ensure that the output
    is consistent with the input raster.
    
    By default, it returns a handle to an open GDAL dataset that you
    can e.g. `ReadAsArray`. If you want to generate a  GTiff on disk,
    set format to `GTiff` and `fname_out` to a sensible filename.
    
    Parameters
    ----------
    raster: str
        The raster filaname used as input. It will not be overwritten.
    vector: str
        The vector filename
    attribute: str
        The attribute that you want to rasterize. Ideally, this is
        numeric.
    fname_out: str, optional
        The output filename.
    format: str, optional
        The output file format, such as GTiff, or whatever else GDAL
        understands
    """
    # Open input raster file. Need to do this to figure out
    # extent, projection & resolution.
    gdal.UseExceptions()
    g = gdal.Open(raster) 
    geoT = g.GetGeoTransform()
    nx, ny = g.RasterXSize, g.RasterYSize 
    srs = g.GetProjection()
    min_x = min(geoT[0], geoT[0]+nx*geoT[1])
    max_x = max(geoT[0], geoT[0]+nx*geoT[1])
    min_y = min(geoT[3], geoT[3] + geoT[-1]*ny)
    max_y = max(geoT[3], geoT[3] + geoT[-1]*ny)
    # Reproject vector to match raster file
    vector_tmp = gdal.VectorTranslate("", vector, format="Memory",
                                    dstSRS=srs)
    # Do the magic
    ds_dst= gdal.Rasterize(fname_out, vector_tmp, attribute=attribute,
                        outputSRS=srs, xRes=geoT[1], yRes=geoT[-1],
                        outputBounds=[min_x, min_y, max_x, max_y],
                        format=format, outputType=gdal.GDT_Int32)
    return ds_dst

rasterize=rasterise_me(r"29052019.tif", r"shape.shp", "shape ID",fname_out="raster.tif")

that works and generated a raster, thought the raster seemes to have the same classes but I thought it’s becuasethe class is very big number:

after that I concat this data about the pixels to big table but then when I check the classes in the big table I can see that they are wrong- they are all the same negative number:

I don’t know where do I lose the numbers values or why.
I have tried to check the dtype of this column but it’s int64 before and after the rasterize process.

My end goal: to preserve the original class attributes in the final results