{ "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", "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)" ] }, { "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
15000.8590000.8008910.643050
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"'https://huggingface.co/gArthur98/Finetuned-Roberta-Base-Sentiment-classifier/commit/91750a00c5f8f9bb9e5eb877bc8994eb45878ed7'" ] }, "execution_count": 120, "metadata": {}, "output_type": "execute_result" } ], "source": [ "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": [ "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\")" ] }, { "cell_type": "code", "execution_count": 55, "metadata": { "id": "H2S7pxMabzJb" }, "outputs": [], "source": [ "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": [ "\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)" ] }, { "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": [ "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": [] }, { 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