Why custom training a Spacy model runs only the Initializing pipeline but the Training pipeline is not running?

Question

I am training a custom NER model with Spacy version 3.5.0 using some dummy data. My entire code and dummy data is given below. This is exact same code give in the 2nd half of this link. The code is running fine, but it only executes until the Initializing pipeline step of the training and the Training pipeline is not executed.

Any idea why the training pipeline is not being executed?

import pandas as pd
import os
from tqdm import tqdm
from spacy.tokens import DocBin

train = [
          ("An average-sized strawberry has about 200 seeds on its outer surface and are quite edible.",{"entities":[(17,27,"Fruit")]}),
          ("The outer skin of Guava is bitter tasting and thick, dark green for raw fruits and as the fruit ripens, the bitterness subsides. ",{"entities":[(18,23,"Fruit")]}),
          ("Grapes are one of the most widely grown types of fruits in the world, chiefly for the making of different wines. ",{"entities":[(0,6,"Fruit")]}),
          ("Watermelon is composed of 92 percent water and significant amounts of Vitamins and antioxidants. ",{"entities":[(0,10,"Fruit")]}),
          ("Papaya fruits are usually cylindrical in shape and the size can go beyond 20 inches. ",{"entities":[(0,6,"Fruit")]}),
          ("Mango, the King of the fruits is a drupe fruit that grows in tropical regions. ",{"entities":[(0,5,"Fruit")]}),
          ("undefined",{"entities":[(0,6,"Fruit")]}),
          ("Oranges are great source of vitamin C",{"entities":[(0,7,"Fruit")]}),
          ("A apple a day keeps doctor away. ",{"entities":[(2,7,"Fruit")]})
        ]

db = DocBin() # create a DocBin object

for text, annot in tqdm(train): # data in previous format
    doc = nlp.make_doc(text) # create doc object from text
    ents = []
    for start, end, label in annot["entities"]: # add character indexes
        span = doc.char_span(start, end, label=label, alignment_mode="contract")
        if span is None:
            print("Skipping entity")
        else:
            ents.append(span)
    doc.ents = ents # label the text with the ents
    db.add(doc)

db.to_disk("./train.spacy") # save the docbin object

!python -m spacy init fill-config base_config.cfg config.cfg

!python -m spacy train config.cfg --output ./output --paths.train ./train.spacy --paths.dev ./train.spacy

Expected output

Output I got

Answer 1

Same issue here.

My output ends at

[INFO] Added vectors: en_core_web_lg

And then the cell stops executing.

I do not even get Finished initializing or anything. What could be the reason for this?