diff --git "a/notebooks/Finetuning_Roberta_with_class_balance (1).ipynb" "b/notebooks/Finetuning_Roberta_with_class_balance (1).ipynb" new file mode 100644--- /dev/null +++ "b/notebooks/Finetuning_Roberta_with_class_balance (1).ipynb" @@ -0,0 +1,7066 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "oYlPR0XSizEg" + }, + "source": [ + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": { + "id": "7__AvAgHAa3K" + }, + "outputs": [], + "source": [ + "%%capture\n", + "\n", + "!pip install transformers\n", + "!pip install accelerate -U\n", + "!pip install datasets\n", + "!pip install huggingface_hub" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": { + "id": "BJMzRz4TAR1W" + }, + "outputs": [], + "source": [ + "%%capture\n", + "\n", + "import torch\n", + "from sklearn.metrics import f1_score\n", + "import pandas as pd\n", + "import numpy as np\n", + "\n", + "from transformers import AutoTokenizer, AutoModelForSequenceClassification\n", + "from sklearn.model_selection import train_test_split\n", + "from transformers import pipeline\n", + "from datasets import load_dataset\n", + "import nltk\n", + "nltk.download('punkt')\n", + "from torch import nn\n", + "from transformers import TrainingArguments\n", + "from transformers import Trainer\n", + "##others\n", + "import warnings\n", + "warnings.filterwarnings(\"ignore\")\n", + "import os\n", + "os.environ[\"WANDB_DISABLED\"] = \"true\"\n", + "\n", + "pd.set_option(\"display.max_rows\", 50)\n", + "pd.set_option(\"display.max_columns\", 50)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "PmH1UCQMAoKk", + "outputId": "b82d8624-8988-421c-ca7e-d803dc496cdc" + }, + "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": "ih2kju2UApCR" + }, + "source": [ + "## Importing Dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "id": "-KeLO8PGBamG" + }, + "outputs": [], + "source": [ + "data_path= '/content/drive/MyDrive/deep-learning/clean_copy.csv'" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "id": "HITU73PQBbDU" + }, + "outputs": [], + "source": [ + "data= pd.read_csv(data_path) ##reading my data set " + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 206 + }, + "id": "bJC0txIMDLGC", + "outputId": "cb807cca-eb59-4b45-d762-6f0ab7f90044" + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "
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StepTraining LossValidation LossF1
5000.8752000.8068040.641171
10000.8310000.8182500.642111
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"\n" + ] + }, + { + "data": { + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + }, + "text/plain": [ + "'https://huggingface.co./gArthur98/Finetuned-Roberta-Base-Sentiment-classifier/commit/91750a00c5f8f9bb9e5eb877bc8994eb45878ed7'" + ] + }, + "execution_count": 120, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "##pushing my trained model together with the results to hugginface \n", + "\n", + "trainer.push_to_hub()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "1tRZXbWPSDE9" + }, + "source": [ + "## handling imbalance" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "8RR1BkIEa27E", + "outputId": "04fc1d5f-e19e-4192-c438-1a13e4c66c83" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.89618857, 0.50992979, 0.59388164])" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "##setting my classweights, and giving my lower class(0) a higher weight \n", + "\n", + "class_weights= (1-(data[\"label\"].value_counts().sort_index() /len(data))).values\n", + "class_weights" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": { + "id": "71XVUm8cbtrq" + }, + "outputs": [], + "source": [ + "class_weights= torch.from_numpy(class_weights).float().to(\"cuda\") ##pusing the weight to my gpu" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": { + "id": "H2S7pxMabzJb" + }, + "outputs": [], + "source": [ + "##creating a custom class to enable the classweight \n", + "\n", + "class WeightedLossTrainer(Trainer):\n", + " def compute_loss(self, model, inputs, return_outputs=False):\n", + " labels = inputs[\"labels\"]\n", + " inputs.pop(\"labels\")\n", + " outputs = model(**inputs)\n", + " logits = outputs.logits.float()\n", + " labels = labels\n", + " loss_func = nn.CrossEntropyLoss(weight=class_weights)\n", + " loss = loss_func(logits, labels)\n", + " return (loss, outputs) if return_outputs else loss" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": { + "id": "QeUVxlIdb5rK" + }, + "outputs": [], + "source": [ + "##instantiating my training arguments\n", + "\n", + "weight_training_args = TrainingArguments(\n", + "\n", + " output_dir=\"Roberta-classweight-Sentiment-classifier\",\n", + " num_train_epochs=3, load_best_model_at_end=True, weight_decay=0.01, evaluation_strategy=\"steps\",save_strategy=\"steps\",push_to_hub=True\n", + "\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": { + "id": "wol7kiE2cFKo" + }, + "outputs": [], + "source": [ + "train_dataset= dataset['train_set'].shuffle(seed=12)\n", + "eval_dataset= dataset['eval_set'].shuffle(seed=12)\n", + "\n", + "##setting my seed to prevent randomization" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "AJb4eiHLcJfu", + "outputId": "b1251355-11bc-4b51-fb26-dc5e4330c451" + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:huggingface_hub.repository:Cloning https://huggingface.co./gArthur98/Roberta-classweight-Sentiment-classifier into local empty directory.\n" + ] + } + ], + "source": [ + "##instantiating my trainer \n", + "class_trainer = WeightedLossTrainer(\n", + " model= model,\n", + " args= weight_training_args,\n", + " train_dataset= train_dataset,\n", + " eval_dataset= eval_dataset,\n", + " tokenizer= tokenizer,\n", + " compute_metrics=compute_metrics )" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": { + "id": "divLFfn0o5Ll" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 343 + }, + "id": "qrID75WpcQtS", + "outputId": 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