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"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"provenance": [],
"gpuType": "T4",
"mount_file_id": "1npJ_m9j344UPF9JAmHTQ-_k6aMVugCpk",
"authorship_tag": "ABX9TyM0uPiqoelXhWIVmGBY/QDu",
"include_colab_link": true
},
"kernelspec": {
"name": "python3",
"display_name": "Python 3"
},
"language_info": {
"name": "python"
},
"accelerator": "GPU"
},
"cells": [
{
"cell_type": "markdown",
"metadata": {
"id": "view-in-github",
"colab_type": "text"
},
"source": [
"<a href=\"https://colab.research.google.com/github/lloydakresi/toxic_comment_moderator_api/blob/main/Train_Notebook.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "R_OdgWC3J90I",
"outputId": "798bca08-f949-4c70-e6d2-cd28f020492b"
},
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"/content/drive/MyDrive\n"
]
}
],
"source": [
"%cd .."
]
},
{
"cell_type": "code",
"source": [
"!rm -rf toxic_comment_moderator_api"
],
"metadata": {
"id": "QUk1Q6CEi4HD"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"!git clone https://github.com/lloydakresi/toxic_comment_moderator_api.git"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "Sp0Up667g4Xy",
"outputId": "b21c7fd0-f539-42e1-992b-0ab8392a52ec"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Cloning into 'toxic_comment_moderator_api'...\n",
"remote: Enumerating objects: 49, done.\u001b[K\n",
"remote: Counting objects: 100% (49/49), done.\u001b[K\n",
"remote: Compressing objects: 100% (28/28), done.\u001b[K\n",
"remote: Total 49 (delta 23), reused 45 (delta 19), pack-reused 0 (from 0)\u001b[K\n",
"Receiving objects: 100% (49/49), 32.99 KiB | 3.67 MiB/s, done.\n",
"Resolving deltas: 100% (23/23), done.\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"%cd toxic_comment_moderator_api"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "XzFpM_OThNor",
"outputId": "e646206d-06b4-4bd5-c06d-059604892416"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"/content/drive/MyDrive/toxic_comment_moderator_api\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"!pip install transformers==5.12.1 datasets==5.0.0 evaluate==0.4.6 accelerate==1.14.0 scikit-learn==1.9.0 iterative-stratification==0.1.9 -q"
],
"metadata": {
"id": "GscPa1Bihx9H"
},
"execution_count": null,
"outputs": []
},
{
"cell_type": "code",
"source": [
"!python train.py"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "LBmM7I26imWc",
"outputId": "bd9c3a9f-d3f8-41f3-f09f-c0c0f9986293"
},
"execution_count": null,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"['id', 'comment_text', 'toxic', 'severe_toxic', 'obscene', 'threat', 'insult', 'identity_hate']\n",
"143613\n",
"Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n",
"Map: 100% 143613/143613 [00:43<00:00, 3280.74 examples/s]\n",
"Map: 100% 15958/15958 [00:05<00:00, 2756.07 examples/s]\n",
"Loading weights: 100% 100/100 [00:00<00:00, 5538.28it/s]\n",
"[transformers] \u001b[1mDistilBertForSequenceClassification LOAD REPORT\u001b[0m from: distilbert-base-uncased\n",
"Key | Status | \n",
"------------------------+------------+-\n",
"vocab_layer_norm.bias | \u001b[38;5;208mUNEXPECTED\u001b[0m | \n",
"vocab_transform.bias | \u001b[38;5;208mUNEXPECTED\u001b[0m | \n",
"vocab_transform.weight | \u001b[38;5;208mUNEXPECTED\u001b[0m | \n",
"vocab_projector.bias | \u001b[38;5;208mUNEXPECTED\u001b[0m | \n",
"vocab_layer_norm.weight | \u001b[38;5;208mUNEXPECTED\u001b[0m | \n",
"pre_classifier.bias | \u001b[31mMISSING\u001b[0m | \n",
"pre_classifier.weight | \u001b[31mMISSING\u001b[0m | \n",
"classifier.bias | \u001b[31mMISSING\u001b[0m | \n",
"classifier.weight | \u001b[31mMISSING\u001b[0m | \n",
"\n",
"Notes:\n",
"- \u001b[38;5;208mUNEXPECTED:\u001b[0m\t\u001b[3mcan be ignored when loading from different task/architecture; not ok if you expect identical arch.\u001b[0m\n",
"- \u001b[31mMISSING:\u001b[0m\t\u001b[3mthose params were newly initialized because missing from the checkpoint. Consider training on your downstream task.\u001b[0m\n",
"True\n",
"Tesla T4\n",
"Model device: cuda:0\n",
" 3% 391/11220 [19:08<8:13:13, 2.73s/it]"
]
}
]
}
]
} |