{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "1CRSm4OHVCmY" }, "source": [ "## Install Dependencies" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "vf4NyoemGKCx", "outputId": "0288e375-a0cb-4fec-e17a-156bf31c93cb" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Collecting datasets\n", " Downloading datasets-2.18.0-py3-none-any.whl (510 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m510.5/510.5 kB\u001b[0m \u001b[31m6.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from datasets) (3.13.3)\n", "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from datasets) (1.25.2)\n", "Requirement already satisfied: pyarrow>=12.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (14.0.2)\n", "Requirement already satisfied: pyarrow-hotfix in /usr/local/lib/python3.10/dist-packages (from datasets) (0.6)\n", "Collecting dill<0.3.9,>=0.3.0 (from datasets)\n", " Downloading dill-0.3.8-py3-none-any.whl (116 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m7.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets) (2.0.3)\n", "Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2.31.0)\n", "Requirement already satisfied: tqdm>=4.62.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (4.66.2)\n", "Collecting xxhash (from datasets)\n", " Downloading xxhash-3.4.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (194 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.1/194.1 kB\u001b[0m \u001b[31m5.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hCollecting multiprocess (from datasets)\n", " Downloading multiprocess-0.70.16-py310-none-any.whl (134 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m6.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: fsspec[http]<=2024.2.0,>=2023.1.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2023.6.0)\n", "Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets) (3.9.3)\n", "Requirement already satisfied: huggingface-hub>=0.19.4 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.20.3)\n", "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from datasets) (24.0)\n", "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (6.0.1)\n", "Requirement already 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python-dateutil>=2.8.2->pandas->datasets) (1.16.0)\n", "Installing collected packages: xxhash, dill, multiprocess, datasets\n", "Successfully installed datasets-2.18.0 dill-0.3.8 multiprocess-0.70.16 xxhash-3.4.1\n" ] } ], "source": [ "! pip install -U datasets" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "id": "hlQscfNrf-KA" }, "outputs": [], "source": [ "import pandas as pd\n", "from datasets import load_dataset, DatasetDict\n", "from huggingface_hub import notebook_login\n", "from sklearn.model_selection import train_test_split" ] }, { "cell_type": "markdown", "metadata": { "id": "30SGKgXKZ15V" }, "source": [ "## Preprocess data" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 206 }, "id": "0tyVQSMTGNy4", "outputId": "b4f194bd-6306-4ec6-e863-985b424dcc8e" }, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " text label\n", "0 If you decide to eat here, just be 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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "df" } }, "metadata": {}, "execution_count": 30 } ], "source": [ "df = pd.read_csv(\"cleaned_data.csv\", usecols=[\"text\", \"sentiment\"])\n", "df.rename(columns={\"sentiment\": \"label\"}, inplace=True)\n", "df.head()" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "jwVLtiqP3vrS", "outputId": "506f5844-7097-4087-8209-0cf3ab593b90" }, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "label\n", "Positive 101121\n", "Negative 36346\n", "Neutral 16846\n", "Name: count, dtype: int64" ] }, "metadata": {}, "execution_count": 31 } ], "source": [ "df[\"label\"].value_counts()" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "id": "Lhdmy3BO3vrS" }, "outputs": [], "source": [ "def sentiment_to_int(sentiment: str) -> int:\n", " if sentiment.lower() == \"negative\":\n", " return 0\n", " if sentiment.lower() == \"neutral\":\n", " return 1\n", " if sentiment.lower() == \"positive\":\n", " return 2\n", " raise Exception(f\"{sentiment} is not a valid value\")" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 206 }, "id": "BTY1KtYl3vrS", "outputId": "5cf0e602-4588-4544-8c7e-d77f934fa97e" }, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " text label\n", "0 If you decide to eat here, just be aware it is... 1\n", "1 I am a long term frequent customer of this est... 0\n", "2 Loved this tour! I grabbed a groupon and the p... 2\n", "3 Love going here for happy hour or dinner! Gre... 2\n", "4 Great staff always helps and always nice. Alwa... 2" ], "text/html": [ "\n", "
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "df" } }, "metadata": {}, "execution_count": 33 } ], "source": [ "df[\"label\"] = df[\"label\"].apply(sentiment_to_int)\n", "df.head()" ] }, { "cell_type": "code", "source": [ "df = df.sample(frac=1).reset_index(drop=True)" ], "metadata": { "id": "udk_Y9gvqmNn" }, "execution_count": 34, "outputs": [] }, { "cell_type": "code", "source": [ "train_df, test_eval_df = train_test_split(df, test_size=0.5)\n", "test_df, eval_df = train_test_split(test_eval_df, test_size=0.5)" ], "metadata": { "id": "RYM-JUI8qRRO" }, "execution_count": 35, "outputs": [] }, { "cell_type": "code", "source": [ "train_df.shape, test_df.shape, eval_df.shape" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "8l5nbLmHqa1O", "outputId": "d3c3c790-185f-44ba-e33d-30cea8959bc8" }, "execution_count": 36, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "((77156, 2), (38578, 2), (38579, 2))" ] }, "metadata": {}, "execution_count": 36 } ] }, { "cell_type": "code", "source": [ "train_df[\"label\"].value_counts(), test_df[\"label\"].value_counts(), eval_df[\n", " \"label\"\n", "].value_counts()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "ohOigPvgqyXN", "outputId": "7dc4ac20-5769-4207-d2c8-20c66f728774" }, "execution_count": 37, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "(label\n", " 2 50426\n", " 0 18120\n", " 1 8610\n", " Name: count, dtype: int64,\n", " label\n", " 2 25388\n", " 0 9096\n", " 1 4094\n", " Name: count, dtype: int64,\n", " label\n", " 2 25307\n", " 0 9130\n", " 1 4142\n", " Name: count, dtype: int64)" ] }, "metadata": {}, "execution_count": 37 } ] }, { "cell_type": "markdown", "metadata": { "id": "sl_JJkJfmPVL" }, "source": [ "## Save the data" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "id": "gUknwI7-gPoQ" }, "outputs": [], "source": [ "train_df.to_csv(\"train.csv\", index=False)\n", "test_df.to_csv(\"test.csv\", index=False)\n", "eval_df.to_csv(\"eval.csv\", index=False)" ] }, { "cell_type": "markdown", "metadata": { "id": "gCBX4XPSGct2" }, "source": [ "## Uploading to Hub" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 145, "referenced_widgets": [ "78e9287d5c5c41d7a64a1115f23ef077", "dce504c21ebe4df1a961a24d1b608b44", "9352a7c117b04d088927cdef99fe890c", "64fe56e1bb604efca6c878c8f48d34ae", "8257f70f39f447f2b5952e5de2674218", "ce5de2fd95ab471783f74b84b518d5f7", "0e1141197fd44011bfe44f4f4a23e316", "e259075acd4e4dc398794d12a2c58145", "1f88fbcdb05647949cb53511619a83e1", "4f5c8604cc5141d3a0b5c921ea09b499", "249edc37f11b4e51ae236d7ddb5d3247", "137a8645cd224a80823292489f40f28a", "a0fbb8bb56de4f3f995bca31b0aaab4e", "94d884d2c955423c92fc808800cf9740", "504956ff57bf41bb90ae6bc0bb9f0f12", "1faca7a75c6242c6b188d351687bf0d7", "e58ad226c0d1467daa011fa4843249b2", "9f336d57e8ea477e894e18301d719af3", "bf84631a06ff437792c13676f302e277", "b00e2dc433c1448e9569c4f32376b500", "5d73d7079de441fa82706e686750380e", "957f6a6a090144f7901d2271f6bdb43e", "ec0c6e952b824014909bdcd190f8045c", "dfc0c9d381334bb2a5782170b41a7d42", "a6e50c9997c841ec8e71a451a56943e8", "96a54ed78e97440196f7bb3e849e2fca", "69120ab5378e4d9f9b57639439a15b0c", "5a45e6c0e1274a51866ffb97084dc914", "c3b868f7748345aa96a8e5abfe2d90cc", "a02d693b66a240829bcb89117d5b9fac", "d555531128cc458c82ce0d4c79cc0b9d", "5a67df5df507456bb09718882027163a" ] }, "id": "D7Q4UcZpGct2", "outputId": "31ea1f34-224b-4921-f4ec-642a186dfd07" }, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "VBox(children=(HTML(value='
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