deep learning/CrossDataset_TPU.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Tu_-h1N65PCG",
        "outputId": "ddc4aa08-7310-49fa-b812-1d9685b2918e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "10.38.210.218:8470\n"
          ]
        }
      ],
      "source": [
        "import os\n",
        "assert os.environ['COLAB_TPU_ADDR'], 'Make sure to select TPU from Edit > Notebook settings > Hardware accelerator'\n",
        "print(os.environ['COLAB_TPU_ADDR'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "HjE_Rexiq_y3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "66a0a3b3-c734-4c90-db65-24407bff87ee"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting torch-xla==1.9\n",
            "  Downloading https://storage.googleapis.com/tpu-pytorch/wheels/torch_xla-1.9-cp37-cp37m-linux_x86_64.whl (149.9 MB)\n",
            "\u001b[K     |████████████████████████████████| 149.9 MB 32 kB/s \n",
            "\u001b[?25hCollecting cloud-tpu-client==0.10\n",
            "  Downloading cloud_tpu_client-0.10-py3-none-any.whl (7.4 kB)\n",
            "Collecting torch==1.9.0\n",
            "  Downloading torch-1.9.0-cp37-cp37m-manylinux1_x86_64.whl (831.4 MB)\n",
            "\u001b[K     |████████████████████████████████| 831.4 MB 2.5 kB/s \n",
            "\u001b[?25hRequirement already satisfied: oauth2client in /usr/local/lib/python3.7/dist-packages (from cloud-tpu-client==0.10) (4.1.3)\n",
            "Collecting google-api-python-client==1.8.0\n",
            "  Downloading google_api_python_client-1.8.0-py3-none-any.whl (57 kB)\n",
            "\u001b[K     |████████████████████████████████| 57 kB 5.1 MB/s \n",
            "\u001b[?25hRequirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch==1.9.0) (3.10.0.2)\n",
            "Requirement already satisfied: uritemplate<4dev,>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from google-api-python-client==1.8.0->cloud-tpu-client==0.10) (3.0.1)\n",
            "Requirement already satisfied: google-auth-httplib2>=0.0.3 in /usr/local/lib/python3.7/dist-packages (from google-api-python-client==1.8.0->cloud-tpu-client==0.10) (0.0.4)\n",
            "Requirement already satisfied: google-api-core<2dev,>=1.13.0 in /usr/local/lib/python3.7/dist-packages (from google-api-python-client==1.8.0->cloud-tpu-client==0.10) (1.26.3)\n",
            "Requirement already satisfied: six<2dev,>=1.6.1 in /usr/local/lib/python3.7/dist-packages (from google-api-python-client==1.8.0->cloud-tpu-client==0.10) (1.15.0)\n",
            "Requirement already satisfied: httplib2<1dev,>=0.9.2 in /usr/local/lib/python3.7/dist-packages (from google-api-python-client==1.8.0->cloud-tpu-client==0.10) (0.17.4)\n",
            "Requirement already satisfied: google-auth>=1.4.1 in /usr/local/lib/python3.7/dist-packages (from google-api-python-client==1.8.0->cloud-tpu-client==0.10) (1.35.0)\n",
            "Requirement already satisfied: pytz in /usr/local/lib/python3.7/dist-packages (from google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client==0.10) (2018.9)\n",
            "Requirement already satisfied: setuptools>=40.3.0 in /usr/local/lib/python3.7/dist-packages (from google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client==0.10) (57.4.0)\n",
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            "Requirement already satisfied: packaging>=14.3 in /usr/local/lib/python3.7/dist-packages (from google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client==0.10) (21.3)\n",
            "Requirement already satisfied: protobuf>=3.12.0 in /usr/local/lib/python3.7/dist-packages (from google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client==0.10) (3.17.3)\n",
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            "Requirement already satisfied: cachetools<5.0,>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from google-auth>=1.4.1->google-api-python-client==1.8.0->cloud-tpu-client==0.10) (4.2.4)\n",
            "Requirement already satisfied: rsa<5,>=3.1.4 in /usr/local/lib/python3.7/dist-packages (from google-auth>=1.4.1->google-api-python-client==1.8.0->cloud-tpu-client==0.10) (4.8)\n",
            "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging>=14.3->google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client==0.10) (3.0.6)\n",
            "Requirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /usr/local/lib/python3.7/dist-packages (from pyasn1-modules>=0.2.1->google-auth>=1.4.1->google-api-python-client==1.8.0->cloud-tpu-client==0.10) (0.4.8)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client==0.10) (2021.10.8)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client==0.10) (1.24.3)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client==0.10) (2.10)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client==0.10) (3.0.4)\n",
            "Installing collected packages: google-api-python-client, torch-xla, torch, cloud-tpu-client\n",
            "  Attempting uninstall: google-api-python-client\n",
            "    Found existing installation: google-api-python-client 1.12.8\n",
            "    Uninstalling google-api-python-client-1.12.8:\n",
            "      Successfully uninstalled google-api-python-client-1.12.8\n",
            "  Attempting uninstall: torch\n",
            "    Found existing installation: torch 1.10.0+cu111\n",
            "    Uninstalling torch-1.10.0+cu111:\n",
            "      Successfully uninstalled torch-1.10.0+cu111\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "torchvision 0.11.1+cu111 requires torch==1.10.0, but you have torch 1.9.0 which is incompatible.\n",
            "torchtext 0.11.0 requires torch==1.10.0, but you have torch 1.9.0 which is incompatible.\n",
            "torchaudio 0.10.0+cu111 requires torch==1.10.0, but you have torch 1.9.0 which is incompatible.\n",
            "earthengine-api 0.1.293 requires google-api-python-client<2,>=1.12.1, but you have google-api-python-client 1.8.0 which is incompatible.\u001b[0m\n",
            "Successfully installed cloud-tpu-client-0.10 google-api-python-client-1.8.0 torch-1.9.0 torch-xla-1.9\n",
            "Collecting transformers\n",
            "  Downloading transformers-4.15.0-py3-none-any.whl (3.4 MB)\n",
            "\u001b[K     |████████████████████████████████| 3.4 MB 5.3 MB/s \n",
            "\u001b[?25hCollecting jsonlines\n",
            "  Downloading jsonlines-3.0.0-py3-none-any.whl (8.5 kB)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from transformers) (2019.12.20)\n",
            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.7/dist-packages (from transformers) (4.62.3)\n",
            "Collecting sacremoses\n",
            "  Downloading sacremoses-0.0.47-py2.py3-none-any.whl (895 kB)\n",
            "\u001b[K     |████████████████████████████████| 895 kB 47.1 MB/s \n",
            "\u001b[?25hCollecting pyyaml>=5.1\n",
            "  Downloading PyYAML-6.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (596 kB)\n",
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            "\u001b[?25hRequirement already satisfied: importlib-metadata in /usr/local/lib/python3.7/dist-packages (from transformers) (4.10.0)\n",
            "Collecting huggingface-hub<1.0,>=0.1.0\n",
            "  Downloading huggingface_hub-0.4.0-py3-none-any.whl (67 kB)\n",
            "\u001b[K     |████████████████████████████████| 67 kB 3.9 MB/s \n",
            "\u001b[?25hCollecting tokenizers<0.11,>=0.10.1\n",
            "  Downloading tokenizers-0.10.3-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (3.3 MB)\n",
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            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (2021.10.8)\n",
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            "Requirement already satisfied: click in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (7.1.2)\n",
            "Installing collected packages: pyyaml, tokenizers, sacremoses, huggingface-hub, transformers, jsonlines\n",
            "  Attempting uninstall: pyyaml\n",
            "    Found existing installation: PyYAML 3.13\n",
            "    Uninstalling PyYAML-3.13:\n",
            "      Successfully uninstalled PyYAML-3.13\n",
            "Successfully installed huggingface-hub-0.4.0 jsonlines-3.0.0 pyyaml-6.0 sacremoses-0.0.47 tokenizers-0.10.3 transformers-4.15.0\n",
            "Collecting sharepy\n",
            "  Downloading sharepy-1.3.0.tar.gz (4.1 kB)\n",
            "Building wheels for collected packages: sharepy\n",
            "  Building wheel for sharepy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sharepy: filename=sharepy-1.3.0-py3-none-any.whl size=4853 sha256=00e77a0800456ea47faf84e7284ac5792f022a0fb4df8740652f5cacd55b1280\n",
            "  Stored in directory: /root/.cache/pip/wheels/1a/aa/6c/53034fd3d05b04fcefd1d7968ba71614f815895e40deb34117\n",
            "Successfully built sharepy\n",
            "Installing collected packages: sharepy\n",
            "Successfully installed sharepy-1.3.0\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (4.62.3)\n"
          ]
        }
      ],
      "source": [
        "! rm -r  sample_data\n",
        "! mkdir data\n",
        "! mkdir \"deep learning\"\n",
        "! mkdir \"deep learning/models\"\n",
        "! pip install cloud-tpu-client==0.10 torch==1.9.0 https://storage.googleapis.com/tpu-pytorch/wheels/torch_xla-1.9-cp37-cp37m-linux_x86_64.whl\n",
        "! pip install transformers jsonlines\n",
        "! pip install sharepy\n",
        "! pip install tqdm"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lGk_tJyp5DoS",
        "outputId": "5869434d-f5b2-4144-ce03-922058a5d261"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Enter your username: vzeng@cougarnet.uh.edu\n",
            "Enter your password: ··········\n",
            "Authentication successful   \n",
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Data/Processed/419.jsonl to data/Processed/419.jsonl\n"
          ]
        },
        {
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          ]
        },
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          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Data/Processed/amazon.jsonl to data/Processed/amazon.jsonl\n"
          ]
        },
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        },
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            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Data/Processed/decop.jsonl to data/Processed/decop.jsonl\n"
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            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Data/Processed/email_benchmarking.jsonl to data/Processed/email_benchmarking.jsonl\n"
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        },
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          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Data/Cleaned/amazon.jsonl to data/Cleaned/amazon.jsonl\n"
          ]
        },
        {
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Data/Cleaned/liar.jsonl to data/Cleaned/liar.jsonl\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 1.6823711395263672/1.6823711395263672 [00:00<00:00, 28.51MB/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Data/Cleaned/email_benchmarking.jsonl to data/Cleaned/email_benchmarking.jsonl\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 35.04428005218506/35.04428005218506 [00:00<00:00, 76.28MB/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Data/Cleaned/job_scams.jsonl to data/Cleaned/job_scams.jsonl\n"
          ]
        },
        {
          "output_type": "stream",
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          "text": [
            "100%|██████████| 17.586992263793945/17.586992263793945 [00:07<00:00,  2.31MB/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/Pilot Study/email_benchmarking1.th to deep learning/Pilot Study/models/email_benchmarking1/email_benchmarking1.th\n"
          ]
        },
        {
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          "text": [
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          ]
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        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/Pilot Study/amazon_1.th to deep learning/Pilot Study/models/amazon_1/amazon_1.th\n"
          ]
        },
        {
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/Pilot Study/job_scams1.th to deep learning/Pilot Study/models/job_scams1/job_scams1.th\n"
          ]
        },
        {
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          ]
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        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/Pilot Study/liar1.th to deep learning/Pilot Study/models/liar1/liar1.th\n"
          ]
        },
        {
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        {
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          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/Pilot Study/welfake1.th to deep learning/Pilot Study/models/welfake1/welfake1.th\n"
          ]
        },
        {
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        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/Pilot Study/op_spam_positive.th to deep learning/Pilot Study/models/op_spam_positive/op_spam_positive.th\n"
          ]
        },
        {
          "output_type": "stream",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/Pilot Study/op_spam_negative.th to deep learning/Pilot Study/models/op_spam_negative/op_spam_negative.th\n"
          ]
        },
        {
          "output_type": "stream",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/Pilot Study/welfake_flipped.th to deep learning/Pilot Study/models/welfake_flipped/welfake_flipped.th\n"
          ]
        },
        {
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/amazon/amazon.th to deep learning/cleaned_models/amazon/amazon.th\n"
          ]
        },
        {
          "output_type": "stream",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/amazon/amazon_v2.th to deep learning/cleaned_models/amazon/amazon_v2.th\n"
          ]
        },
        {
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/email_benchmarking/email_benchmarking.th to deep learning/cleaned_models/email_benchmarking/email_benchmarking.th\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/email_benchmarking/email_benchmarking_v2.th to deep learning/cleaned_models/email_benchmarking/email_benchmarking_v2.th\n"
          ]
        },
        {
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/job_scams/job_scams.th to deep learning/cleaned_models/job_scams/job_scams.th\n"
          ]
        },
        {
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/job_scams/job_scams_v2.th to deep learning/cleaned_models/job_scams/job_scams_v2.th\n"
          ]
        },
        {
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/liar/liar.th to deep learning/cleaned_models/liar/liar.th\n"
          ]
        },
        {
          "output_type": "stream",
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        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/liar/liar_v2.th to deep learning/cleaned_models/liar/liar_v2.th\n"
          ]
        },
        {
          "output_type": "stream",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/welfake/welfake.th to deep learning/cleaned_models/welfake/welfake.th\n"
          ]
        },
        {
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        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/welfake/welfake_v2.th to deep learning/cleaned_models/welfake/welfake_v2.th\n"
          ]
        },
        {
          "output_type": "stream",
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        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/combined/combined_bert.th to deep learning/cleaned_models/combined/combined_bert.th\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 417.72770404815674/417.72770404815674 [00:06<00:00, 61.80MB/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/combined/combined_roberta.th to deep learning/cleaned_models/combined/combined_roberta.th\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/combined/combined_bert_large.th to deep learning/cleaned_models/combined/combined_bert_large.th\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 1278.6268129348755/1278.6268129348755 [00:19<00:00, 66.10MB/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/combined/combined_roberta_large.th to deep learning/cleaned_models/combined/combined_roberta_large.th\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/combined/combined_bert_v2.th to deep learning/cleaned_models/combined/combined_bert_v2.th\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/combined/combined_roberta_v2.th to deep learning/cleaned_models/combined/combined_roberta_v2.th\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/combined/combined_bert_large_v2.th to deep learning/cleaned_models/combined/combined_bert_large_v2.th\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
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          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/cleaned_models/combined/combined_roberta_large_v2.th to deep learning/cleaned_models/combined/combined_roberta_large_v2.th\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 1355.751935005188/1355.751935005188 [00:19<00:00, 68.62MB/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/combined_scams.th to deep learning/models/combined_scams/combined_scams.th\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 417.72770404815674/417.72770404815674 [00:05<00:00, 77.09MB/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading https://uofh.sharepoint.com/:u:/r/sites/ReDAS/Shared%20Documents/CrossDatasetExperiment%20Datasets/Models/a7bfc9522/liar1_wd01_b64_100epochs.th to deep learning/models/liar1_wd01_b64_100epochs.th\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 418.20139598846436/418.20139598846436 [03:37<00:00,  1.92MB/s]\n"
          ]
        }
      ],
      "source": [
        "import os\n",
        "os.chdir(\"/content\")\n",
        "from download_data import download_data\n",
        "\n",
        "download_data()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "\n",
        "from glob import glob \n",
        "os.chdir(\"/content/deep learning\")\n",
        "print(os.getcwd())\n",
        "from test_model_xla import test_xla_mp"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-njWFyCCm_JL",
        "outputId": "0dff2768-10f3-4931-ab45-53f60641ee4a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/deep learning\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:root:Waiting for TPU to be start up with version pytorch-1.9...\n",
            "WARNING:root:Waiting for TPU to be start up with version pytorch-1.9...\n",
            "WARNING:root:Waiting for TPU to be start up with version pytorch-1.9...\n",
            "WARNING:root:TPU has started up successfully with version pytorch-1.9\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "models = [\"cleaned_models/liar/liar_v2\"]\n",
        "cleaned_datasets = ['Cleaned/amazon.jsonl', 'Cleaned/email_benchmarking.jsonl', 'Cleaned/job_scams.jsonl', 'Cleaned/liar.jsonl', 'Cleaned/welfake.jsonl']\n",
        "for model in models:\n",
        "    print(f\"\\n\\nTesting {model}\")\n",
        "    test_xla_mp(model, cleaned_datasets)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lLsj3bggmec9",
        "outputId": "7a7cfeb7-ff4e-4ad8-e352-17a2c30dc8f5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n",
            "Testing cleaned_models/liar/liar_v2\n",
            "Loading ../data/Cleaned/amazon.jsonl\n",
            "20976 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 6/6 [00:31<00:00,  5.22s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[6680 3801]\n",
            " [6495 4000]]\n",
            "Final Test Accuracy: 0.5091533180778032\n",
            "Final Test Recall: 0.38113387327298714\n",
            "Final Test F1 Score: 0.43725404459991263\n",
            "Loading ../data/Cleaned/email_benchmarking.jsonl\n",
            "15336 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 5/5 [00:17<00:00,  3.52s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[2033 7169]\n",
            " [ 426 5708]]\n",
            "Final Test Accuracy: 0.5047600417318727\n",
            "Final Test Recall: 0.9305510270622759\n",
            "Final Test F1 Score: 0.6004944505812424\n",
            "Loading ../data/Cleaned/job_scams.jsonl\n",
            "14344 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 4/4 [00:16<00:00,  4.08s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[11532  2204]\n",
            " [  480   128]]\n",
            "Final Test Accuracy: 0.8128834355828221\n",
            "Final Test Recall: 0.21052631578947367\n",
            "Final Test F1 Score: 0.08707482993197278\n",
            "Loading ../data/Cleaned/liar.jsonl\n",
            "1282 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 1/1 [00:09<00:00,  9.49s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[482 249]\n",
            " [213 338]]\n",
            "Final Test Accuracy: 0.6396255850234009\n",
            "Final Test Recall: 0.6134301270417423\n",
            "Final Test F1 Score: 0.59402460456942\n",
            "Loading ../data/Cleaned/welfake.jsonl\n",
            "62101 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 17/17 [00:54<00:00,  3.22s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[25165  9450]\n",
            " [14812 12674]]\n",
            "Final Test Accuracy: 0.6093138596801984\n",
            "Final Test Recall: 0.46110747289529214\n",
            "Final Test F1 Score: 0.5109453739165492\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "models = [\"cleaned_models/amazon/amazon_v2\", \"cleaned_models/email_benchmarking/email_benchmarking_v2\", \"cleaned_models/job_scams/job_scams_v2\", \"cleaned_models/liar/liar_v2\"]\n",
        "cleaned_datasets = ['Cleaned/amazon.jsonl', 'Cleaned/email_benchmarking.jsonl', 'Cleaned/job_scams.jsonl', 'Cleaned/liar.jsonl', 'Cleaned/welfake.jsonl']\n",
        "for model in models:\n",
        "    print(f\"\\n\\nTesting {model}\")\n",
        "    test_xla_mp(model, cleaned_datasets)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jRtgqTOPxO21",
        "outputId": "e79fb46e-0184-4ef3-b547-f9c1cc78819b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n",
            "Testing cleaned_models/amazon/amazon_v2\n",
            "Loading ../data/Cleaned/amazon.jsonl\n",
            "2098 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 1/1 [00:02<00:00,  2.04s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[745 311]\n",
            " [301 741]]\n",
            "Final Test Accuracy: 0.7082936129647283\n",
            "Final Test Recall: 0.7111324376199616\n",
            "Final Test F1 Score: 0.7077363896848137\n",
            "Loading ../data/Cleaned/email_benchmarking.jsonl\n",
            "15336 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 5/5 [00:13<00:00,  2.61s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[8440  762]\n",
            " [3487 2647]]\n",
            "Final Test Accuracy: 0.7229394887845592\n",
            "Final Test Recall: 0.4315291816106945\n",
            "Final Test F1 Score: 0.5547521743686472\n",
            "Loading ../data/Cleaned/job_scams.jsonl\n",
            "14343 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 4/4 [00:12<00:00,  3.03s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[   49   559]\n",
            " [  664 13071]]\n",
            "Final Test Accuracy: 0.9147319249808269\n",
            "Final Test Recall: 0.9516563523844194\n",
            "Final Test F1 Score: 0.9553078750228393\n",
            "Loading ../data/Cleaned/liar.jsonl\n",
            "12812 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 4/4 [00:02<00:00,  1.47it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[6813  345]\n",
            " [5355  299]]\n",
            "Final Test Accuracy: 0.555104589447393\n",
            "Final Test Recall: 0.05288291475061903\n",
            "Final Test F1 Score: 0.09495077802476977\n",
            "Loading ../data/Cleaned/welfake.jsonl\n",
            "62101 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 17/17 [00:50<00:00,  2.98s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[33807   808]\n",
            " [22479  5007]]\n",
            "Final Test Accuracy: 0.6250140899502423\n",
            "Final Test Recall: 0.1821654660554464\n",
            "Final Test F1 Score: 0.3007116903396294\n",
            "\n",
            "\n",
            "Testing cleaned_models/email_benchmarking/email_benchmarking_v2\n",
            "Loading ../data/Cleaned/amazon.jsonl\n",
            "20976 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 6/6 [00:17<00:00,  2.99s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[6915 3566]\n",
            " [6489 4006]]\n",
            "Final Test Accuracy: 0.5206426392067124\n",
            "Final Test Recall: 0.3817055740828966\n",
            "Final Test F1 Score: 0.4434604527591742\n",
            "Loading ../data/Cleaned/email_benchmarking.jsonl\n",
            "1534 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 1/1 [00:01<00:00,  1.35s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[903   8]\n",
            " [ 11 612]]\n",
            "Final Test Accuracy: 0.9876140808344198\n",
            "Final Test Recall: 0.9823434991974318\n",
            "Final Test F1 Score: 0.9847144006436042\n",
            "Loading ../data/Cleaned/job_scams.jsonl\n",
            "14343 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 4/4 [00:12<00:00,  3.01s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[ 329  279]\n",
            " [7814 5921]]\n",
            "Final Test Accuracy: 0.435752631945897\n",
            "Final Test Recall: 0.43108846013833274\n",
            "Final Test F1 Score: 0.5940305994482067\n",
            "Loading ../data/Cleaned/liar.jsonl\n",
            "12812 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 4/4 [00:03<00:00,  1.25it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[6461  697]\n",
            " [5235  419]]\n",
            "Final Test Accuracy: 0.5369965657196378\n",
            "Final Test Recall: 0.07410682702511497\n",
            "Final Test F1 Score: 0.12378138847858199\n",
            "Loading ../data/Cleaned/welfake.jsonl\n",
            "62101 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 17/17 [00:50<00:00,  2.99s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[34474   141]\n",
            " [27199   287]]\n",
            "Final Test Accuracy: 0.5597494404276904\n",
            "Final Test Recall: 0.010441679400422033\n",
            "Final Test F1 Score: 0.02056315827183492\n",
            "\n",
            "\n",
            "Testing cleaned_models/job_scams/job_scams_v2\n",
            "Loading ../data/Cleaned/amazon.jsonl\n",
            "20976 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 6/6 [00:17<00:00,  3.00s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[ 591 9890]\n",
            " [ 741 9754]]\n",
            "Final Test Accuracy: 0.4931826849733028\n",
            "Final Test Recall: 0.9293949499761791\n",
            "Final Test F1 Score: 0.6472676598427287\n",
            "Loading ../data/Cleaned/email_benchmarking.jsonl\n",
            "15336 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 5/5 [00:12<00:00,  2.58s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[  39 9163]\n",
            " [ 106 6028]]\n",
            "Final Test Accuracy: 0.3956051121544079\n",
            "Final Test Recall: 0.9827192696446039\n",
            "Final Test F1 Score: 0.565345838218054\n",
            "Loading ../data/Cleaned/job_scams.jsonl\n",
            "1435 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 1/1 [00:01<00:00,  1.62s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[  23   41]\n",
            " [   9 1362]]\n",
            "Final Test Accuracy: 0.9651567944250871\n",
            "Final Test Recall: 0.9934354485776805\n",
            "Final Test F1 Score: 0.9819754866618601\n",
            "Loading ../data/Cleaned/liar.jsonl\n",
            "12812 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 4/4 [00:02<00:00,  1.43it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[ 154 7004]\n",
            " [ 120 5534]]\n",
            "Final Test Accuracy: 0.4439587886356541\n",
            "Final Test Recall: 0.9787760877255041\n",
            "Final Test F1 Score: 0.6083992963940194\n",
            "Loading ../data/Cleaned/welfake.jsonl\n",
            "62101 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 17/17 [00:50<00:00,  2.99s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[    6 34609]\n",
            " [   23 27463]]\n",
            "Final Test Accuracy: 0.4423278208080385\n",
            "Final Test Recall: 0.9991632103616387\n",
            "Final Test F1 Score: 0.6133008776435382\n",
            "\n",
            "\n",
            "Testing cleaned_models/liar/liar_v2\n",
            "Loading ../data/Cleaned/amazon.jsonl\n",
            "20976 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 6/6 [00:18<00:00,  3.02s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[6680 3801]\n",
            " [6495 4000]]\n",
            "Final Test Accuracy: 0.5091533180778032\n",
            "Final Test Recall: 0.38113387327298714\n",
            "Final Test F1 Score: 0.43725404459991263\n",
            "Loading ../data/Cleaned/email_benchmarking.jsonl\n",
            "15336 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 5/5 [00:12<00:00,  2.52s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[2033 7169]\n",
            " [ 426 5708]]\n",
            "Final Test Accuracy: 0.5047600417318727\n",
            "Final Test Recall: 0.9305510270622759\n",
            "Final Test F1 Score: 0.6004944505812424\n",
            "Loading ../data/Cleaned/job_scams.jsonl\n",
            "14343 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 4/4 [00:12<00:00,  3.03s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[  480   128]\n",
            " [11532  2203]]\n",
            "Final Test Accuracy: 0.18705988984173463\n",
            "Final Test Recall: 0.16039315617036767\n",
            "Final Test F1 Score: 0.2742437445537159\n",
            "Loading ../data/Cleaned/liar.jsonl\n",
            "1282 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 1/1 [00:00<00:00,  1.55it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[482 249]\n",
            " [213 338]]\n",
            "Final Test Accuracy: 0.6396255850234009\n",
            "Final Test Recall: 0.6134301270417423\n",
            "Final Test F1 Score: 0.59402460456942\n",
            "Loading ../data/Cleaned/welfake.jsonl\n",
            "62101 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 17/17 [00:50<00:00,  3.00s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[25165  9450]\n",
            " [14812 12674]]\n",
            "Final Test Accuracy: 0.6093138596801984\n",
            "Final Test Recall: 0.46110747289529214\n",
            "Final Test F1 Score: 0.5109453739165492\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hsud7aFwzAIx",
        "outputId": "38ae2e6e-bc86-4e41-9e20-3aee7c7c4a86"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/deep learning\n",
            "\n",
            "\n",
            "Testing cleaned_models/welfake/welfake_v2\n",
            "Loading ../data/Cleaned/amazon.jsonl\n",
            "20976 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 6/6 [00:17<00:00,  2.99s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[  106 10375]\n",
            " [   50 10445]]\n",
            "Final Test Accuracy: 0.5030034324942791\n",
            "Final Test Recall: 0.9952358265840877\n",
            "Final Test F1 Score: 0.6670924477087659\n",
            "Loading ../data/Cleaned/email_benchmarking.jsonl\n",
            "15336 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 5/5 [00:12<00:00,  2.53s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[ 175 9027]\n",
            " [  15 6119]]\n",
            "Final Test Accuracy: 0.4104068857589984\n",
            "Final Test Recall: 0.9975546136289534\n",
            "Final Test F1 Score: 0.575093984962406\n",
            "Loading ../data/Cleaned/job_scams.jsonl\n",
            "14343 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 4/4 [00:12<00:00,  3.02s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[   17   591]\n",
            " [  471 13264]]\n",
            "Final Test Accuracy: 0.9259569127797532\n",
            "Final Test Recall: 0.9657080451401528\n",
            "Final Test F1 Score: 0.9615077926785066\n",
            "Loading ../data/Cleaned/liar.jsonl\n",
            "12812 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 4/4 [00:02<00:00,  1.59it/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[3560 3598]\n",
            " [2343 3311]]\n",
            "Final Test Accuracy: 0.5362940992819232\n",
            "Final Test Recall: 0.585603112840467\n",
            "Final Test F1 Score: 0.5271033988696967\n",
            "Loading ../data/Cleaned/welfake.jsonl\n",
            "6211 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 2/2 [00:10<00:00,  5.15s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[3500   16]\n",
            " [   1 2694]]\n",
            "Final Test Accuracy: 0.9972629206246981\n",
            "Final Test Recall: 0.9996289424860854\n",
            "Final Test F1 Score: 0.9968547641073081\n"
          ]
        }
      ],
      "source": [
        "print(os.getcwd())\n",
        "models = [\"cleaned_models/welfake/welfake_v2\"]\n",
        "cleaned_datasets = ['Cleaned/amazon.jsonl', 'Cleaned/email_benchmarking.jsonl', 'Cleaned/job_scams.jsonl', 'Cleaned/liar.jsonl', 'Cleaned/welfake.jsonl']\n",
        "for model in models:\n",
        "    print(f\"\\n\\nTesting {model}\")\n",
        "    test_xla_mp(model, cleaned_datasets)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "models = ['cleaned_models/combined/combined_roberta_v2']\n",
        "cleaned_datasets = ['Cleaned/amazon.jsonl', 'Cleaned/email_benchmarking.jsonl', 'Cleaned/job_scams.jsonl', 'Cleaned/liar.jsonl', 'Cleaned/welfake.jsonl']\n",
        "for model in models:\n",
        "    print(f\"\\n\\nTesting {model}\")\n",
        "    test_xla_mp(model, cleaned_datasets)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "729651fb31f44b5c91a6c4737af79426",
            "b5e6b25f3301400cbd57b7c3b6fefef8",
            "75029ed1b8ff4657b226bfa5a9a23cf2",
            "506494a8156c460e8919c52f10528a12",
            "a2c247d477334d0981a8cdd39f4fbe77",
            "d00039f4ee2040b99091f09172442934",
            "7998490fee6d4729b0848144f9b756f0",
            "b8298a47a27648faa5910bffaf1b3f33",
            "ca36ba6029c242dab6ee06f27ca6d33a",
            "fbca6f6dab8d469cab2b9579a58d57af",
            "0fac51f6302942409927e0750131fffc",
            "79fa48ada752479793b27e874ef13113",
            "5620eb9ab00c4685802aa0fd30c5d2c7",
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        "id": "IxtuGQ59kFoP",
        "outputId": "ac751cba-420e-4116-bc69-d4ebf2f61cd2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n",
            "Testing cleaned_models/combined/combined_roberta_v2\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "729651fb31f44b5c91a6c4737af79426",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
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            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "79fa48ada752479793b27e874ef13113",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "baf3846e4fb546409f9b80f80a7fa808",
              "version_minor": 0,
              "version_major": 2
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            "text/plain": [
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            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "7602ea0611114e4d896dac1018638408",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/481 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "091df7de6868482cba0bace23deb92e7",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/478M [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Loading ../data/Cleaned/amazon.jsonl\n",
            "2098 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 1/1 [00:02<00:00,  2.43s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[ 72 969]\n",
            " [ 60 997]]\n",
            "Final Test Accuracy: 0.509532888465205\n",
            "Final Test Recall: 0.9432355723746452\n",
            "Final Test F1 Score: 0.6596096592788621\n",
            "Loading ../data/Cleaned/email_benchmarking.jsonl\n",
            "1534 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 1/1 [00:05<00:00,  5.15s/it]\n",
            "Evaluating: 100%|██████████| 1/1 [00:05<00:00,  5.16s/it]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[ 12 922]\n",
            " [  7 593]]\n",
            "Final Test Accuracy: 0.394393741851369\n",
            "Final Test Recall: 0.9883333333333333\n",
            "Final Test F1 Score: 0.5607565011820331\n",
            "Loading ../data/Cleaned/job_scams.jsonl\n",
            "1435 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 1/1 [00:08<00:00,  8.21s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[   1   59]\n",
            " [  13 1362]]\n",
            "Final Test Accuracy: 0.9498257839721255\n",
            "Final Test Recall: 0.9905454545454545\n",
            "Final Test F1 Score: 0.9742489270386266\n",
            "Loading ../data/Cleaned/liar.jsonl\n",
            "1282 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 1/1 [00:10<00:00, 10.70s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[147 582]\n",
            " [ 79 474]]\n",
            "Final Test Accuracy: 0.484399375975039\n",
            "Final Test Recall: 0.8571428571428571\n",
            "Final Test F1 Score: 0.5891858297078931\n",
            "Loading ../data/Cleaned/welfake.jsonl\n",
            "6211 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 3/3 [00:14<00:00,  4.88s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[   4 3398]\n",
            " [  20 2789]]\n",
            "Final Test Accuracy: 0.44968604089518593\n",
            "Final Test Recall: 0.9928800284798861\n",
            "Final Test F1 Score: 0.6200533570475766\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "models = ['cleaned_models/combined/combined_bert_large_v2']\n",
        "cleaned_datasets = ['Cleaned/amazon.jsonl', 'Cleaned/email_benchmarking.jsonl', 'Cleaned/job_scams.jsonl', 'Cleaned/liar.jsonl', 'Cleaned/welfake.jsonl']\n",
        "for model in models:\n",
        "    print(f\"\\n\\nTesting {model}\")\n",
        "    test_xla_mp(model, cleaned_datasets, 128)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
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        "id": "DHETIle1kNr9",
        "outputId": "8ee58bc6-07b9-4087-d832-ac9d42231ddd"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n",
            "Testing cleaned_models/combined/combined_bert_large_v2\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "db1ddc34dc7549f3b232e7b30b307188",
              "version_minor": 0,
              "version_major": 2
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            "text/plain": [
              "Downloading:   0%|          | 0.00/226k [00:00<?, ?B/s]"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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              "version_minor": 0,
              "version_major": 2
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            "text/plain": [
              "Downloading:   0%|          | 0.00/455k [00:00<?, ?B/s]"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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        {
          "output_type": "display_data",
          "data": {
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              "version_major": 2
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            "text/plain": [
              "Downloading:   0%|          | 0.00/571 [00:00<?, ?B/s]"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "207e5793504f4804847af480d441bf43",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "Downloading:   0%|          | 0.00/1.25G [00:00<?, ?B/s]"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Loading ../data/Cleaned/amazon.jsonl\n",
            "2098 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 3/3 [00:16<00:00,  5.40s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[797 233]\n",
            " [444 624]]\n",
            "Final Test Accuracy: 0.6773117254528122\n",
            "Final Test Recall: 0.5842696629213483\n",
            "Final Test F1 Score: 0.6483116883116884\n",
            "Loading ../data/Cleaned/email_benchmarking.jsonl\n",
            "1534 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 2/2 [00:13<00:00,  6.59s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[917  20]\n",
            " [ 20 577]]\n",
            "Final Test Accuracy: 0.9739243807040417\n",
            "Final Test Recall: 0.966499162479062\n",
            "Final Test F1 Score: 0.966499162479062\n",
            "Loading ../data/Cleaned/job_scams.jsonl\n",
            "1435 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 2/2 [00:14<00:00,  7.37s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[  13   45]\n",
            " [   4 1373]]\n",
            "Final Test Accuracy: 0.9658536585365853\n",
            "Final Test Recall: 0.9970951343500363\n",
            "Final Test F1 Score: 0.9824686940966011\n",
            "Loading ../data/Cleaned/liar.jsonl\n",
            "1282 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 2/2 [00:33<00:00, 17.00s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[637  57]\n",
            " [493  95]]\n",
            "Final Test Accuracy: 0.5709828393135725\n",
            "Final Test Recall: 0.16156462585034015\n",
            "Final Test F1 Score: 0.2567567567567568\n",
            "Loading ../data/Cleaned/welfake.jsonl\n",
            "6211 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 7/7 [00:25<00:00,  3.60s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[3469   16]\n",
            " [  89 2637]]\n",
            "Final Test Accuracy: 0.9830945097407825\n",
            "Final Test Recall: 0.967351430667645\n",
            "Final Test F1 Score: 0.9804796430563302\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "models = ['cleaned_models/combined/combined_roberta_large_v2']\n",
        "cleaned_datasets = ['Cleaned/amazon.jsonl', 'Cleaned/email_benchmarking.jsonl', 'Cleaned/job_scams.jsonl', 'Cleaned/liar.jsonl', 'Cleaned/welfake.jsonl']\n",
        "for model in models:\n",
        "    print(f\"\\n\\nTesting {model}\")\n",
        "    test_xla_mp(model, cleaned_datasets, 128)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
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            "a4a2ea525e7547a1926fbf32af7e29ea",
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        "id": "lvYIVnHDkPGF",
        "outputId": "97f91e75-7bd6-42d7-d74c-be7a5437d4c8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n",
            "Testing cleaned_models/combined/combined_roberta_large_v2\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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              "model_id": "732feaa694d3486ba4d1464466073bee",
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          },
          "metadata": {}
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        {
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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          },
          "metadata": {}
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        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
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              "version_major": 2
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            "text/plain": [
              "Downloading:   0%|          | 0.00/482 [00:00<?, ?B/s]"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "abddf78829a74d7c805b6aee0dbe31c0",
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              "version_major": 2
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            "text/plain": [
              "Downloading:   0%|          | 0.00/1.33G [00:00<?, ?B/s]"
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          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Loading ../data/Cleaned/amazon.jsonl\n",
            "2098 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 3/3 [00:23<00:00,  7.82s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[   1 1025]\n",
            " [   0 1072]]\n",
            "Final Test Accuracy: 0.511439466158246\n",
            "Final Test Recall: 1.0\n",
            "Final Test F1 Score: 0.6765541180183023\n",
            "Loading ../data/Cleaned/email_benchmarking.jsonl\n",
            "1534 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 2/2 [00:13<00:00,  6.58s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[  0 889]\n",
            " [  1 644]]\n",
            "Final Test Accuracy: 0.4198174706649283\n",
            "Final Test Recall: 0.9984496124031008\n",
            "Final Test F1 Score: 0.591368227731864\n",
            "Loading ../data/Cleaned/job_scams.jsonl\n",
            "1435 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 2/2 [00:13<00:00,  6.64s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[   0   60]\n",
            " [   1 1374]]\n",
            "Final Test Accuracy: 0.9574912891986063\n",
            "Final Test Recall: 0.9992727272727273\n",
            "Final Test F1 Score: 0.9782840868636525\n",
            "Loading ../data/Cleaned/liar.jsonl\n",
            "1282 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 2/2 [00:33<00:00, 17.28s/it]\n",
            "Evaluating: 100%|██████████| 2/2 [00:33<00:00, 16.71s/it]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[ 11 698]\n",
            " [  5 568]]\n",
            "Final Test Accuracy: 0.4516380655226209\n",
            "Final Test Recall: 0.9912739965095986\n",
            "Final Test F1 Score: 0.6177270255573681\n",
            "Loading ../data/Cleaned/welfake.jsonl\n",
            "6211 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 7/7 [00:24<00:00,  3.43s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[   1 3462]\n",
            " [   3 2745]]\n",
            "Final Test Accuracy: 0.44211882144582193\n",
            "Final Test Recall: 0.9989082969432315\n",
            "Final Test F1 Score: 0.6130653266331658\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "models = ['cleaned_models/combined/combined_bert_v2']\n",
        "cleaned_datasets = ['Cleaned/amazon.jsonl', 'Cleaned/email_benchmarking.jsonl', 'Cleaned/job_scams.jsonl', 'Cleaned/liar.jsonl', 'Cleaned/welfake.jsonl']\n",
        "for model in models:\n",
        "    print(f\"\\n\\nTesting {model}\")\n",
        "    test_xla_mp(model, cleaned_datasets)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
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        "id": "zESRac2Wse8Y",
        "outputId": "fb442b36-c391-4a03-f734-9f4f985266f6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n",
            "Testing cleaned_models/combined/combined_bert_v2\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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              "Downloading:   0%|          | 0.00/226k [00:00<?, ?B/s]"
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          "metadata": {}
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              "Downloading:   0%|          | 0.00/455k [00:00<?, ?B/s]"
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          "metadata": {}
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        {
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              "Downloading:   0%|          | 0.00/570 [00:00<?, ?B/s]"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
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            "text/plain": [
              "Downloading:   0%|          | 0.00/420M [00:00<?, ?B/s]"
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          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Loading ../data/Cleaned/amazon.jsonl\n",
            "2098 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 1/1 [00:07<00:00,  7.61s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[740 299]\n",
            " [318 741]]\n",
            "Final Test Accuracy: 0.7059103908484271\n",
            "Final Test Recall: 0.6997167138810199\n",
            "Final Test F1 Score: 0.7060505002382087\n",
            "Loading ../data/Cleaned/email_benchmarking.jsonl\n",
            "1534 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 1/1 [00:06<00:00,  6.75s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[891  31]\n",
            " [ 10 602]]\n",
            "Final Test Accuracy: 0.9732724902216427\n",
            "Final Test Recall: 0.9836601307189542\n",
            "Final Test F1 Score: 0.9670682730923694\n",
            "Loading ../data/Cleaned/job_scams.jsonl\n",
            "1435 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 1/1 [00:06<00:00,  6.96s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[  22   43]\n",
            " [   6 1364]]\n",
            "Final Test Accuracy: 0.9658536585365853\n",
            "Final Test Recall: 0.9956204379562044\n",
            "Final Test F1 Score: 0.9823550594166366\n",
            "Loading ../data/Cleaned/liar.jsonl\n",
            "1282 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 1/1 [00:10<00:00, 10.29s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[492 216]\n",
            " [250 324]]\n",
            "Final Test Accuracy: 0.6365054602184087\n",
            "Final Test Recall: 0.5644599303135889\n",
            "Final Test F1 Score: 0.5816876122082586\n",
            "Loading ../data/Cleaned/welfake.jsonl\n",
            "6211 loaded\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Evaluating: 100%|██████████| 3/3 [00:14<00:00,  5.00s/it]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Test Confusion Matrix:\n",
            "[[3399   38]\n",
            " [  20 2754]]\n",
            "Final Test Accuracy: 0.9906617291901465\n",
            "Final Test Recall: 0.992790194664744\n",
            "Final Test F1 Score: 0.9895795903701041\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "10Ekr_afITUd",
        "outputId": "ceac2cc3-4b74-4240-add5-4e2cb7a868cd"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Metric: XrtAllocateFromTensor\n",
            "  TotalSamples: 6360\n",
            "  Accumulator: 09s271ms920.363us\n",
            "  Mean: 002ms560.101us\n",
            "  StdDev: 002ms925.566us\n",
            "  Rate: 4.04118 / second\n",
            "  Percentiles: 25%=608.095us; 50%=002ms676.370us; 80%=002ms345.670us; 90%=002ms499.865us; 95%=003ms677.954us; 99%=003ms183.716us\n",
            "Metric: XrtCompile\n",
            "  TotalSamples: 48\n",
            "  Accumulator: 47s942ms551.391us\n",
            "  Mean: 978ms948.987us\n",
            "  StdDev: 02s427ms313.692us\n",
            "  Rate: 0.038941 / second\n",
            "  Percentiles: 25%=011ms649.352us; 50%=011ms152.801us; 80%=013ms793.553us; 90%=05s240ms236.833us; 95%=08s748ms474.331us; 99%=10s729ms262.000us\n",
            "Metric: XrtExecute\n",
            "  TotalSamples: 480\n",
            "  Accumulator: 22m52s735ms545.832us\n",
            "  Mean: 03s733ms780.304us\n",
            "  StdDev: 492ms280.892us\n",
            "  Rate: 0.390143 / second\n",
            "  Percentiles: 25%=03s698ms829.149us; 50%=03s915ms196.655us; 80%=03s916ms745.864us; 90%=03s916ms105.616us; 95%=03s916ms469.962us; 99%=03s922ms512.284us\n",
            "Metric: XrtExecutorEvict\n",
            "  TotalSamples: 0\n",
            "  Accumulator: nanB\n",
            "  Mean: nanB\n",
            "  StdDev: nanB\n",
            "  Percentiles: \n",
            "Metric: XrtReadLiteral\n",
            "  TotalSamples: 480\n",
            "  Accumulator: 349ms209.008us\n",
            "  Mean: 727.519us\n",
            "  StdDev: 144.758us\n",
            "  Rate: 0.390144 / second\n",
            "  Percentiles: 25%=613.055us; 50%=726.563us; 80%=862.863us; 90%=920.537us; 95%=953.885us; 99%=001ms043.122us\n",
            "Metric: XrtReleaseAllocation\n",
            "  TotalSamples: 1544\n",
            "  Accumulator: 046ms822.052us\n",
            "  Mean: 028.271us\n",
            "  StdDev: 039.755us\n",
            "  Rate: 1.15223 / second\n",
            "  Percentiles: 25%=013.348us; 50%=021.385us; 80%=030.340us; 90%=038.501us; 95%=060.367us; 99%=244.983us\n",
            "\n"
          ]
        }
      ],
      "source": [
        "import torch_xla.debug.metrics as met\n",
        "\n",
        "print(met.metrics_report())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "5yWyhuhGNdiY"
      },
      "outputs": [],
      "source": [
        ""
      ]
    }
  ],
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      "name": "CrossDataset TPU.ipynb",
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