{ "cells": [ { "cell_type": "markdown", "metadata": { "id": "E9wXgZgXKBH1" }, "source": [ "## a. Introduction:" ] }, { "cell_type": "code", "execution_count": 69, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "WrxEs1UL2Ywr", "outputId": "916a7214-3b23-4f84-eff9-d2c48177c99f" }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n" ] } ], "source": [ "from google.colab import drive\n", "drive.mount('/content/drive')" ] }, { "cell_type": "markdown", "metadata": { "id": "XeMyIP55GZuB" }, "source": [ "Earlier, in the DATA CLEANING and EDA Notebook, we looked at how we can clean an NLP DATASET. Well in this section, we will be taking a look at how you can model such a dataset . We will be fine tuning two models:\n", "\n", "- RoBerTa\n", "- DistillBeRT from HuggingFace.\n", "\n", "Note all these models can be found on HuggingFace.\n", "\n", "Also, the dataset we will be using has already be cleaned. Therefore, you might have to check out the cleaning data set on hwo that was done" ] }, { "cell_type": "markdown", "metadata": { "id": "w7A21o4KGxRY" }, "source": [ "## b.Dependencies" ] }, { "cell_type": "markdown", "metadata": { "id": "mm3jgFitK02g" }, "source": [ "### i. Installations\n", "\n", "> Indented block\n", "\n" ] }, { "cell_type": "code", "execution_count": 70, "metadata": { "id": "K31MxohNKbgF" }, "outputs": [], "source": [ "%%capture\n", "!pip install transformers\n", "!pip install accelerate -U\n", "!pip install datasets\n", "!pip install huggingface_hub\n", "\n" ] }, { "cell_type": "markdown", "metadata": { "id": "h4vHoPUvK4Ap" }, "source": [ "### Dependencies Importations" ] }, { "cell_type": "code", "execution_count": 71, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "L3NIt5VvK-MH", "outputId": "6a9d8356-473e-4ee4-bc8a-d53e657c4e0b" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "[nltk_data] Downloading package punkt to /root/nltk_data...\n", "[nltk_data] Package punkt is already up-to-date!\n" ] } ], "source": [ "##for handling path of my datasets\n", "import os\n", "from google.colab import drive\n", "\n", "##for data handling:\n", "\n", "import pandas as pd\n", "import numpy as np\n", "\n", "##for visuals-- just in case\n", "\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "\n", "from transformers import AutoTokenizer, AutoModelForSequenceClassification\n", "import torch\n", "from transformers import TrainingArguments\n", "from scipy.special import softmax\n", "from torch import nn\n", "import torch\n", "from transformers import Trainer\n", "\n", "##modelling:\n", "\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.metrics import f1_score\n", "import transformers\n", "from transformers import pipeline\n", "from datasets import load_dataset\n", "import nltk\n", "nltk.download('punkt')\n", "##others\n", "import warnings\n", "warnings.filterwarnings(\"ignore\")\n", "import os\n", "os.environ[\"WANDB_DISABLED\"] = \"true\"\n", "pd.set_option(\"display.max_rows\", None)\n", "pd.set_option(\"display.max_columns\", None)" ] }, { "cell_type": "markdown", "metadata": { "id": "V7mSJF39LXxB" }, "source": [ "## c. Importing dataset from my Google Drive" ] }, { "cell_type": "code", "execution_count": 72, "metadata": { "id": "9ztLUrheMFB9" }, "outputs": [], "source": [ "data_path= '/content/drive/MyDrive/deep-learning/clean_copy.csv'" ] }, { "cell_type": "code", "execution_count": 73, "metadata": { "id": "k51AAeHrMF0E" }, "outputs": [], "source": [ "data= pd.read_csv(data_path)" ] }, { "cell_type": "code", "execution_count": 74, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 206 }, "id": "o4fP0f8sMi2d", "outputId": "f9553378-7ccc-4232-8d25-a090d47d42e1" }, "outputs": [ { "data": { "text/html": [ "\n", "\n", "
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StepTraining LossValidation LossF1
5000.8486000.9540000.613671
10000.7857000.7877080.667150
15000.7039000.7437520.703539
20000.6526000.7396280.710672
25000.5131000.7834820.717471

" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "TrainOutput(global_step=2991, training_loss=0.6683594280563043, metrics={'train_runtime': 1438.5413, 'train_samples_per_second': 16.634, 'train_steps_per_second': 2.079, 'total_flos': 3169736441782272.0, 'train_loss': 0.6683594280563043, 'epoch': 3.0})" ] }, "execution_count": 102, "metadata": {}, "output_type": "execute_result" } ], "source": [ "##training my model\n", "\n", "trainer.train()" ] }, { "cell_type": "markdown", "metadata": { "id": "WhG1QHCJ7ibC" }, "source": [ "### Plotting my Loss Graph:\n" ] }, { "cell_type": "code", "execution_count": 103, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 276, "referenced_widgets": [ "de9bfe683c27440e9dd58f25205c8dcc", "18eadc6a037643a28191c644c790869e", "f966c1d72cbc40249cf23a1e55e6d6a4", "97b05e9016864539a84cd9a325f3bc43", "bfdab876f9ce45d9b8ae1783309e2b52", "5c6d386b6ba44df3bae64c2bb3f5f9a7", "5d7d886760094a0fbaf4cfe4fc5b07c3", "c56b42c77b60462896737e00af5cdc39", "ddef0f6d6fbb49fbb0128877ea0aee80", "30ae7d3bfb7245ee99431abd0decd707", "2e6863201c5d4a0d8cd208df3dd3130a" ] }, "id": "dIMtlZCJ5lR9", "outputId": "8be6a8d4-3fde-4224-f7a0-7918e03bfbca" }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "de9bfe683c27440e9dd58f25205c8dcc", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Upload file runs/Jul29_19-42-30_f6c6f92035c3/events.out.tfevents.1690659755.f6c6f92035c3.778.0: 0%| …" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "To https://huggingface.co./gArthur98/Greg-DistilBert-classifier\n", " 3cf611d..04cc0a2 main -> main\n", "\n", "WARNING:huggingface_hub.repository:To https://huggingface.co./gArthur98/Greg-DistilBert-classifier\n", " 3cf611d..04cc0a2 main -> main\n", "\n", "To https://huggingface.co./gArthur98/Greg-DistilBert-classifier\n", " 04cc0a2..6fc3d33 main -> main\n", "\n", "WARNING:huggingface_hub.repository:To https://huggingface.co./gArthur98/Greg-DistilBert-classifier\n", " 04cc0a2..6fc3d33 main -> main\n", "\n" ] }, { "data": { "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" }, "text/plain": [ "'https://huggingface.co./gArthur98/Greg-DistilBert-classifier/commit/04cc0a26f51fda0cd9402e68ff987c0bfc0c8bcf'" ] }, "execution_count": 103, "metadata": {}, "output_type": "execute_result" } ], "source": [ "trainer.push_to_hub()" ] }, { "cell_type": "markdown", "metadata": { "id": "kcapmTtXRQ9p" }, "source": [ "## Plotting my validation loss curve\n", "\n" ] }, { "cell_type": "code", "execution_count": 109, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 607 }, "id": "eyhDrMxZSuls", "outputId": "c44f6524-2883-42de-e717-79825bd9fb0b" }, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "\n", "#\n", "steps = [500, 1000, 1500, 2000, 2500]\n", "train_loss = [0.848600, 0.785700, 0.703900, 0.652600, 0.513100]\n", "val_loss = [0.954000, 0.787708, 0.743752, 0.739628, 0.783482]\n", "f1_score = [0.613671, 0.667150, 0.703539, 0.710672, 0.717471]\n", "\n", "# Plotting my training and validation losses over steps/epochs\n", "\n", "plt.figure(figsize=(10, 6))\n", "\n", "##plotting my trianing and validation loss\n", "\n", "plt.subplot(2, 1, 1)\n", "plt.plot(steps, train_loss, label='Training Loss', marker='o')\n", "plt.plot(steps, val_loss, label='Validation Loss', marker='o')\n", "plt.xlabel('Steps/Epochs')\n", "plt.ylabel('Loss')\n", "plt.title('Training and Validation Losses')\n", "plt.legend()\n", "plt.grid(True)\n", "\n", "##plotting my f1-score performance\n", "\n", "plt.subplot(2, 1, 2)\n", "plt.plot(steps, f1_score, label='F1 Score', marker='o', color='green')\n", "plt.xlabel('Steps/Epochs')\n", "plt.ylabel('F1 Score')\n", "plt.title('F1 Score')\n", "plt.legend()\n", "plt.grid(True)\n", "\n", "plt.tight_layout()\n", "plt.show()\n", "\n", "\n", "\n", "\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "ayxVIRr_UlUs" }, "outputs": [], "source": [] } ], "metadata": { "accelerator": "GPU", "colab": { "gpuType": "T4", "provenance": [] }, "kernelspec": { "display_name": "Python 3", "name": "python3" }, "language_info": { "name": "python" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "03108fded5064fd5b06a36aaf2d09320": { "model_module": "@jupyter-widgets/controls", "model_module_version": "1.5.0", "model_name": "DescriptionStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, 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