pruksmhc

{
  "results": {
    "mmstar": {
      "alias": "mmstar",
      "coarse perception,none": 0.7502214478878857,
      "coarse perception_stderr,none": "N/A",
      "average,none": 0.6282898425011137,
      "average_stderr,none": "N/A",
      "fine-grained perception,none": 0.5771677720461803,
      "fine-grained perception_stderr,none": "N/A",

pruksmhc

import os
import re
import pandas as pd
import multiprocessing as mp
import time
from datasets import Dataset, load_from_disk
import gc
from tqdm import tqdm
import psutil
import os

pruksmhc

import multiprocessing as mp
from datasets import load_dataset
from transformers import AutoTokenizer
from itertools import islice
import tqdm

MAX_DOCS_PER_LANG = 10_000
langs = [
    'rus_Cyrl', 'cmn_Hani', 'deu_Latn', 'jpn_Jpan', 'spa_Latn',

pruksmhc

Setup Tutorial

graph LR

A[Multitask: Pretrain Task 1, Pretrain task2]  --> B((Target Task 1))

A --> C(Round Rect)

pruksmhc

Setup Tutorial

graph LR

A[Multitask: Pretrain Task 1, Pretrain task2]  --> B((Target Task 1))

A --> C(Round Rect)

pruksmhc

Setup Tutorial

graph LR

A[Multitask: Pretrain Task 1, Pretrain task2]  --> B((Target Task 1))

A --> C(Round Rect)