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rvl-cdip

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notebook used to create the dataset

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  1. create_dataset.ipynb +366 -0
create_dataset.ipynb ADDED
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+ {
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+ "cells": [
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+ {
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+ "cell_type": "code",
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+ "execution_count": 13,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "from datasets import load_dataset, DatasetDict"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 2,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "name": "stdout",
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+ "output_type": "stream",
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+ "text": [
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+ "{'letter': 0, 'form': 1, 'email': 2, 'handwritten': 3, 'advertissement': 4, 'scientific report': 5, 'scientific publication': 6, 'specification': 7, 'file folder': 8, 'news article': 9, 'budget': 10, 'invoice': 11, 'presentation': 12, 'questionnaire': 13, 'resume': 14, 'memo': 15}\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "labels = [\n",
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+ " \"letter\", \n",
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+ " \"form\", \n",
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+ " \"email\", \n",
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+ " \"handwritten\", \n",
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+ " \"advertissement\", \n",
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+ " \"scientific report\", \n",
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+ " \"scientific publication\", \n",
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+ " \"specification\",\n",
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+ " \"file folder\", \n",
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+ " \"news article\", \n",
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+ " \"budget\", \n",
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+ " \"invoice\", \n",
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+ " \"presentation\", \n",
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+ " \"questionnaire\", \n",
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+ " \"resume\", \n",
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+ " \"memo\",\n",
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+ "]\n",
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+ "id2label = {i: label for i, label in enumerate(labels)}\n",
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+ "label2id = {label: i for i, label in enumerate(labels)}\n",
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+ "\n",
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+ "print(label2id)"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 10,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "name": "stderr",
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+ "output_type": "stream",
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+ "text": [
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+ "Resolving data files: 100%|██████████| 319999/319999 [00:01<00:00, 179922.60it/s]\n",
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+ "Using custom data configuration default-92674f9f14bd5f68\n",
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+ "Reusing dataset image_folder (/home/chainyo/.cache/huggingface/datasets/image_folder/default-92674f9f14bd5f68/0.0.0/ee92df8e96c6907f3c851a987be3fd03d4b93b247e727b69a8e23ac94392a091)\n",
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+ "100%|██████████| 1/1 [00:00<00:00, 1.10it/s]\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "train_dataset = load_dataset(\"imagefolder\", data_dir=\"data/train\")\n",
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+ "train_dataset = train_dataset[\"train\"]"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 11,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "name": "stderr",
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+ "output_type": "stream",
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+ "text": [
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+ "Resolving data files: 100%|██████████| 40000/40000 [00:00<00:00, 42366.47it/s] \n",
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+ "Using custom data configuration default-3ddea2d6bbc33b4c\n",
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+ "Reusing dataset image_folder (/home/chainyo/.cache/huggingface/datasets/image_folder/default-3ddea2d6bbc33b4c/0.0.0/ee92df8e96c6907f3c851a987be3fd03d4b93b247e727b69a8e23ac94392a091)\n",
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+ "100%|██████████| 1/1 [00:00<00:00, 8.93it/s]\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "test_dataset = load_dataset(\"imagefolder\", data_dir=\"data/test\")\n",
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+ "test_dataset = test_dataset[\"train\"]"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 12,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "name": "stderr",
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+ "output_type": "stream",
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+ "text": [
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+ "Resolving data files: 100%|██████████| 40000/40000 [00:00<00:00, 127231.79it/s]\n",
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+ "Using custom data configuration default-8c91b9b2f12e1b5f\n",
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+ "Reusing dataset image_folder (/home/chainyo/.cache/huggingface/datasets/image_folder/default-8c91b9b2f12e1b5f/0.0.0/ee92df8e96c6907f3c851a987be3fd03d4b93b247e727b69a8e23ac94392a091)\n",
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+ "100%|██████████| 1/1 [00:00<00:00, 7.66it/s]\n"
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+ ]
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+ }
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+ ],
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+ "source": [
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+ "val_dataset = load_dataset(\"imagefolder\", data_dir=\"data/val\")\n",
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+ "val_dataset = val_dataset[\"train\"]"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 15,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "dataset = DatasetDict({\n",
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+ " \"train\": train_dataset,\n",
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+ " \"val\": val_dataset,\n",
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+ " \"test\": test_dataset\n",
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+ "})"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 16,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "data": {
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+ "text/plain": [
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+ "DatasetDict({\n",
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+ " train: Dataset({\n",
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+ " features: ['image', 'label'],\n",
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+ " num_rows: 319999\n",
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+ " })\n",
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+ " val: Dataset({\n",
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+ " features: ['image', 'label'],\n",
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+ " num_rows: 40000\n",
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+ " })\n",
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+ " test: Dataset({\n",
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+ " features: ['image', 'label'],\n",
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+ " num_rows: 40000\n",
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+ " })\n",
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+ "})"
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+ ]
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+ },
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+ "execution_count": 16,
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+ "metadata": {},
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+ "output_type": "execute_result"
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+ }
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+ ],
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+ "source": [
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+ "dataset"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 17,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "name": "stderr",
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+ "output_type": "stream",
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+ "text": [
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+ "Pushing split train to the Hub.\n",
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+ "The repository already exists: the `private` keyword argument will be ignored.\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.93ba/s]7%|██████▋ | 80/119 [41:35<20:58, 32.26s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.91ba/s]8%|██████▊ | 81/119 [41:59<18:53, 29.82s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.83ba/s]9%|██████▉ | 82/119 [42:26<17:58, 29.14s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.92ba/s]0%|██████▉ | 83/119 [42:51<16:44, 27.90s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.84ba/s]1%|███████ | 84/119 [43:19<16:19, 27.98s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.87ba/s]1%|███████▏ | 85/119 [43:50<16:15, 28.68s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.83ba/s]2%|███████▏ | 86/119 [44:21<16:16, 29.60s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.85ba/s]3%|███████▎ | 87/119 [44:51<15:43, 29.49s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.82ba/s]4%|███████▍ | 88/119 [45:27<16:14, 31.43s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.80ba/s]5%|███████▍ | 89/119 [46:00<15:58, 31.93s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.56ba/s]6%|███████▌ | 90/119 [46:37<16:13, 33.58s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.77ba/s]6%|███████▋ | 91/119 [47:11<15:46, 33.80s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.66ba/s]7%|███████▋ | 92/119 [47:47<15:29, 34.42s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.69ba/s]8%|███████▊ | 93/119 [48:24<15:10, 35.03s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.65ba/s]9%|███████▉ | 94/119 [49:12<16:15, 39.04s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.60ba/s]0%|███████▉ | 95/119 [49:49<15:20, 38.35s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.61ba/s]1%|████████ | 96/119 [50:37<15:52, 41.41s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.58ba/s]2%|████████▏ | 97/119 [51:18<15:04, 41.10s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.53ba/s]2%|████████▏ | 98/119 [52:06<15:04, 43.09s/it]\n",
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+ "100%|██████████| 3/3 [00:02<00:00, 1.43ba/s]3%|████████▎ | 99/119 [52:59<15:25, 46.28s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.52ba/s]4%|████████▍ | 100/119 [53:47<14:48, 46.76s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.58ba/s]5%|████████▍ | 101/119 [54:41<14:38, 48.81s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.54ba/s]6%|████████▌ | 102/119 [55:29<13:44, 48.53s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.57ba/s]7%|████████▋ | 103/119 [56:10<12:20, 46.31s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.82ba/s]7%|████████▋ | 104/119 [56:57<11:41, 46.75s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.93ba/s]8%|████████▊ | 105/119 [57:26<09:39, 41.37s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.87ba/s]9%|████████▉ | 106/119 [57:52<07:55, 36.60s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.97ba/s]0%|████████▉ | 107/119 [58:23<06:59, 35.00s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.89ba/s]1%|█████████ | 108/119 [58:57<06:20, 34.57s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.86ba/s]2%|█████████▏| 109/119 [59:26<05:31, 33.11s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.86ba/s]2%|█████████▏| 110/119 [59:55<04:45, 31.72s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.92ba/s]3%|█████████▎| 111/119 [1:00:23<04:05, 30.69s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.78ba/s]4%|█████████▍| 112/119 [1:00:49<03:25, 29.33s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.86ba/s]5%|█████████▍| 113/119 [1:01:31<03:17, 33.00s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.78ba/s]6%|█████████▌| 114/119 [1:01:59<02:38, 31.70s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.89ba/s]7%|█████████▋| 115/119 [1:02:31<02:06, 31.72s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.77ba/s]7%|█████████▋| 116/119 [1:03:03<01:35, 31.71s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.87ba/s]8%|█████████▊| 117/119 [1:03:39<01:06, 33.04s/it]\n",
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+ "Pushing dataset shards to the dataset hub: 100%|██████████| 119/119 [1:04:41<00:00, 32.62s/it]\n",
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+ "Pushing split val to the Hub.\n",
291
+ "The repository already exists: the `private` keyword argument will be ignored.\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.57ba/s]0%| | 0/15 [00:00<?, ?it/s]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.98ba/s]7%|▋ | 1/15 [00:41<09:34, 41.03s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 2.14ba/s]3%|█▎ | 2/15 [01:05<06:49, 31.53s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 2.08ba/s]0%|██ | 3/15 [01:19<04:41, 23.44s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.80ba/s]0%|████ | 6/15 [02:34<03:44, 24.99s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.87ba/s]0%|██████ | 9/15 [04:01<02:54, 29.16s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.59ba/s]7%|██████▋ | 10/15 [04:28<02:23, 28.66s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.78ba/s]3%|███████▎ | 11/15 [04:48<01:44, 26.10s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.58ba/s]0%|████████ | 12/15 [05:28<01:30, 30.17s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.95ba/s]7%|████████▋ | 13/15 [06:10<01:07, 33.95s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.83ba/s]3%|█████████▎| 14/15 [06:37<00:31, 31.72s/it]\n",
307
+ "Pushing dataset shards to the dataset hub: 100%|██████████| 15/15 [06:58<00:00, 27.89s/it]\n",
308
+ "Pushing split test to the Hub.\n",
309
+ "The repository already exists: the `private` keyword argument will be ignored.\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.66ba/s]0%| | 0/15 [00:00<?, ?it/s]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.86ba/s]7%|▋ | 1/15 [00:37<08:48, 37.75s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 2.11ba/s]3%|█▎ | 2/15 [00:58<05:57, 27.51s/it]\n",
313
+ "100%|██████████| 3/3 [00:01<00:00, 2.10ba/s]0%|██ | 3/15 [01:18<04:49, 24.15s/it]\n",
314
+ "100%|██████████| 3/3 [00:01<00:00, 1.94ba/s]7%|██▋ | 4/15 [01:37<04:03, 22.12s/it]\n",
315
+ "100%|██████████| 3/3 [00:01<00:00, 1.80ba/s]3%|███▎ | 5/15 [02:08<04:14, 25.41s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.83ba/s]0%|████ | 6/15 [02:31<03:40, 24.50s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.71ba/s]7%|████▋ | 7/15 [02:57<03:20, 25.08s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.66ba/s]3%|█████▎ | 8/15 [03:19<02:49, 24.22s/it]\n",
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+ "100%|██████████| 3/3 [00:01<00:00, 1.77ba/s]0%|██████ | 9/15 [03:48<02:32, 25.49s/it]\n",
320
+ "100%|██████████| 3/3 [00:01<00:00, 1.75ba/s]7%|██████▋ | 10/15 [04:13<02:07, 25.58s/it]\n",
321
+ "100%|██████████| 3/3 [00:01<00:00, 1.73ba/s]3%|███████▎ | 11/15 [04:37<01:39, 24.99s/it]\n",
322
+ "100%|██████████| 3/3 [00:01<00:00, 1.57ba/s]0%|████████ | 12/15 [05:10<01:22, 27.46s/it]\n",
323
+ "100%|██████████| 3/3 [00:01<00:00, 1.73ba/s]7%|████████▋ | 13/15 [05:53<01:04, 32.24s/it]\n",
324
+ "100%|██████████| 3/3 [00:01<00:00, 1.81ba/s]3%|█████████▎| 14/15 [06:20<00:30, 30.55s/it]\n",
325
+ "Pushing dataset shards to the dataset hub: 100%|██████████| 15/15 [06:48<00:00, 27.20s/it]\n"
326
+ ]
327
+ }
328
+ ],
329
+ "source": [
330
+ "dataset.push_to_hub(\"ChainYo/rvl-cdip\")"
331
+ ]
332
+ },
333
+ {
334
+ "cell_type": "code",
335
+ "execution_count": null,
336
+ "metadata": {},
337
+ "outputs": [],
338
+ "source": []
339
+ }
340
+ ],
341
+ "metadata": {
342
+ "interpreter": {
343
+ "hash": "d6f5ad4d04cbfdf412f1cb227626c5243110bb053a071a535525d68cbde39709"
344
+ },
345
+ "kernelspec": {
346
+ "display_name": "Python 3.8.13 ('datasets')",
347
+ "language": "python",
348
+ "name": "python3"
349
+ },
350
+ "language_info": {
351
+ "codemirror_mode": {
352
+ "name": "ipython",
353
+ "version": 3
354
+ },
355
+ "file_extension": ".py",
356
+ "mimetype": "text/x-python",
357
+ "name": "python",
358
+ "nbconvert_exporter": "python",
359
+ "pygments_lexer": "ipython3",
360
+ "version": "3.8.13"
361
+ },
362
+ "orig_nbformat": 4
363
+ },
364
+ "nbformat": 4,
365
+ "nbformat_minor": 2
366
+ }