From a22a5cef2c4838e533a06db1976ceef64c1eec66 Mon Sep 17 00:00:00 2001 From: Hope Ogbons Date: Fri, 31 Oct 2025 03:24:09 +0100 Subject: [PATCH] Add week 6 exercise notebook for banking intent classification This commit introduces a new Jupyter notebook, 'week6 EXERCISE.ipynb', which outlines the process for fine-tuning a model to classify banking customer queries. The notebook includes steps for data preparation, model training, and evaluation, utilizing the Banking77 dataset and OpenAI's API for fine-tuning. This addition enhances the project's capabilities in handling banking-related queries effectively. --- .../hopeogbons/week6 EXERCISE.ipynb | 855 ++++++++++++++++++ 1 file changed, 855 insertions(+) create mode 100644 week6/community-contributions/hopeogbons/week6 EXERCISE.ipynb diff --git a/week6/community-contributions/hopeogbons/week6 EXERCISE.ipynb b/week6/community-contributions/hopeogbons/week6 EXERCISE.ipynb new file mode 100644 index 0000000..bcbd0f4 --- /dev/null +++ b/week6/community-contributions/hopeogbons/week6 EXERCISE.ipynb @@ -0,0 +1,855 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "776935d0", + "metadata": {}, + "outputs": [], + "source": [ + "# Import required libraries for data handling, API connections, and model training\n", + "import os\n", + "import re\n", + "import math\n", + "import json\n", + "import random\n", + "from dotenv import load_dotenv\n", + "from huggingface_hub import login\n", + "import matplotlib.pyplot as plt\n", + "from datasets import load_dataset\n", + "import numpy as np\n", + "import pickle\n", + "from collections import Counter\n", + "from openai import OpenAI" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "04ef96aa", + "metadata": {}, + "outputs": [], + "source": [ + "# Load API keys from .env file\n", + "load_dotenv(override=True)\n", + "os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY', '####-####-####-####')\n", + "os.environ['HF_TOKEN'] = os.getenv('HF_TOKEN', '####-####-####-####')" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "8458f9e7", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Note: Environment variable`HF_TOKEN` is set and is the current active token independently from the token you've just configured.\n" + ] + } + ], + "source": [ + "# Initialize OpenAI client and login to HuggingFace\n", + "openai = OpenAI()\n", + "\n", + "hf_token = os.environ['HF_TOKEN']\n", + "login(hf_token, add_to_git_credential=True)" + ] + }, + { + "cell_type": "markdown", + "id": "0263f64b", + "metadata": {}, + "source": [ + "# Step 1\n", + "\n", + "### Prepare our data for fine-tuning in JSONL (JSON Lines) format and upload to OpenAI" + ] + }, + { + "cell_type": "markdown", + "id": "0302c73d", + "metadata": {}, + "source": [ + "### Load and Cache Dataset\n", + "Download banking77 dataset or load from cache (for slow internet)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "a85d7fbd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading from cached pickle files...\n", + "✓ Loaded 10003 train and 3080 test samples from cache\n" + ] + } + ], + "source": [ + "from data_cleaner import clean_dataset\n", + "\n", + "# Check if pickle files exist, otherwise download\n", + "if os.path.exists('train.pkl') and os.path.exists('test.pkl'):\n", + " print(\"Loading from cached pickle files...\")\n", + " with open('train.pkl', 'rb') as f:\n", + " train = pickle.load(f)\n", + " with open('test.pkl', 'rb') as f:\n", + " test = pickle.load(f)\n", + " print(f\"✓ Loaded {len(train)} train and {len(test)} test samples from cache\")\n", + "else:\n", + " print(\"✓ Downloading dataset from HuggingFace...\")\n", + " dataset = load_dataset(\"PolyAI/banking77\")\n", + " \n", + " # Clean the data\n", + " print(\"Cleaning dataset...\")\n", + " train = clean_dataset(dataset['train'], min_length=10, max_samples_per_intent=200)\n", + " test = clean_dataset(dataset['test'], min_length=10)\n", + " \n", + " # Save for next time\n", + " with open('train.pkl', 'wb') as f:\n", + " pickle.dump(train, f)\n", + " with open('test.pkl', 'wb') as f:\n", + " pickle.dump(test, f)\n", + " print(f\"✓ Cleaned and saved {len(train)} train and {len(test)} test samples\")" + ] + }, + { + "cell_type": "markdown", + "id": "df2d9c9d", + "metadata": {}, + "source": [ + "# Step 2\n", + "\n", + "### Create fine-tuning job on OpenAI and monitor training progress" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "9a608e40", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "✓ Created 200 train and 50 validation examples\n" + ] + } + ], + "source": [ + "# Convert to list format for easier handling\n", + "train_list = [{'text': train[i]['text'], 'label': train[i]['label']} for i in range(len(train))]\n", + "\n", + "# Create fine-tuning subsets\n", + "fine_tune_train = train_list[:200] #800\n", + "fine_tune_validation = train_list[200:250] #4,000\n", + "\n", + "print(f\"✓ Created {len(fine_tune_train)} train and {len(fine_tune_validation)} validation examples\")" + ] + }, + { + "cell_type": "markdown", + "id": "e878a4f0", + "metadata": {}, + "source": [ + "### Format Messages for OpenAI\n", + "Create training and inference message formats\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "e305e49e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'role': 'system',\n", + " 'content': 'You classify banking customer queries into intents. Reply only with the intent name, no explanation'},\n", + " {'role': 'user', 'content': 'I am still waiting on my card?'},\n", + " {'role': 'assistant', 'content': 'card_arrival'}]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from banking_intents import get_intent\n", + "\n", + "def messages_for_training(item):\n", + " \"\"\"Create messages for fine-tuning - includes the correct answer\"\"\"\n", + " system_message = \"You classify banking customer queries into intents. Reply only with the intent name, no explanation\"\n", + " return [\n", + " {\"role\": \"system\", \"content\": system_message},\n", + " {\"role\": \"user\", \"content\": item['text']},\n", + " {\"role\": \"assistant\", \"content\": get_intent(item['label'])}\n", + " ]\n", + "\n", + "def messages_for_inference(item):\n", + " \"\"\"Create messages for prediction - NO answer (model must predict)\"\"\"\n", + " system_message = \"You classify banking customer queries into intents. Reply only with the intent name, no explanation\"\n", + " return [\n", + " {\"role\": \"system\", \"content\": system_message},\n", + " {\"role\": \"user\", \"content\": item['text']}\n", + " ]\n", + "\n", + "# Test training format\n", + "messages_for_training(train[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "c3a27241", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\"messages\": [{\"role\": \"system\", \"content\": \"You classify banking customer queries into intents. Reply only with the intent name, no explanation\"}, {\"role\": \"user\", \"content\": \"I am still waiting on my card?\"}, {\"role\": \"assistant\", \"content\": \"card_arrival\"}]}\n", + "{\"messages\": [{\"role\": \"system\", \"content\": \"You classify banking customer queries into intents. Reply only with the intent name, no explanation\"}, {\"role\": \"user\", \"content\": \"What can I do if my card still hasn't arrived after 2 weeks?\"}, {\"role\": \"assistant\", \"content\": \"card_arrival\"}]}\n", + "{\"messages\": [{\"role\": \"system\", \"content\": \"You classify banking customer queries into intents. Reply only with the intent name, no explanation\"}, {\"role\": \"user\", \"content\": \"I have been waiting over a week. Is the card still coming?\"}, {\"role\": \"assistant\", \"content\": \"card_arrival\"}]}\n" + ] + } + ], + "source": [ + "def make_jsonl(data, start=0, end=None):\n", + " \"\"\"Convert data to JSONL format for training\"\"\"\n", + " result = \"\"\n", + " end = end or len(data)\n", + " \n", + " for i in range(start, end):\n", + " item = data[i]\n", + " messages = messages_for_training(item) # Use training format\n", + " messages_str = json.dumps(messages)\n", + " result += '{\"messages\": ' + messages_str +'}\\n'\n", + " \n", + " return result.strip()\n", + "\n", + "print(make_jsonl(train, start=0, end=3))" + ] + }, + { + "cell_type": "markdown", + "id": "bb0e75d6", + "metadata": {}, + "source": [ + "### Convert to JSONL and Upload\n", + "Prepare data in OpenAI format and upload to their servers\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "dd4affd3", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "# Write JSONL string to file\n", + "def write_jsonl(data, filename, start=0, end=None):\n", + " with open(filename, \"w\") as f:\n", + " jsonl = make_jsonl(data, start, end)\n", + " f.write(jsonl)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "8c5bf74c", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0. I am still waiting on my card? → Intent: 11\n", + "1. What can I do if my card still hasn't arrived after 2 weeks? → Intent: 11\n", + "2. I have been waiting over a week. Is the card still coming? → Intent: 11\n" + ] + } + ], + "source": [ + "# Verify data loaded correctly - show first 3 examples\n", + "for i in range(3):\n", + " print(f\"{i}. {train[i]['text']} → Intent: {train[i]['label']}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "8b3bc0a9", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "✓ Uploaded train: file-U84ceTSvNn833d6aPpWX4i\n", + "✓ Uploaded validation: file-ARVTnFJnHn2HpE9UAr9mr5\n" + ] + } + ], + "source": [ + "def prepare_and_upload(data, filename):\n", + " \"\"\"Write JSONL and upload to OpenAI\"\"\"\n", + " write_jsonl(data, filename)\n", + " with open(filename, \"rb\") as f:\n", + " return openai.files.create(file=f, purpose=\"fine-tune\")\n", + "\n", + "# Use it\n", + "train_file = prepare_and_upload(fine_tune_train, \"fine_tune_train.jsonl\")\n", + "validation_file = prepare_and_upload(fine_tune_validation, \"fine_tune_validation.jsonl\")\n", + "\n", + "print(f\"✓ Uploaded train: {train_file.id}\")\n", + "print(f\"✓ Uploaded validation: {validation_file.id}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "f6147112", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FineTuningJob(id='ftjob-FN3B5dQQOhuk4UVOZ5X4CqBU', created_at=1761873619, error=Error(code=None, message=None, param=None), fine_tuned_model=None, finished_at=None, hyperparameters=Hyperparameters(batch_size='auto', learning_rate_multiplier='auto', n_epochs=1), model='gpt-4o-mini-2024-07-18', object='fine_tuning.job', organization_id='org-OFfqVJ5fIDV1i5BqCwT86Px6', result_files=[], seed=42, status='validating_files', trained_tokens=None, training_file='file-U84ceTSvNn833d6aPpWX4i', validation_file='file-ARVTnFJnHn2HpE9UAr9mr5', estimated_finish=None, integrations=[], metadata=None, method=Method(type='supervised', dpo=None, reinforcement=None, supervised=SupervisedMethod(hyperparameters=SupervisedHyperparameters(batch_size='auto', learning_rate_multiplier='auto', n_epochs=1))), user_provided_suffix='banking_intent', usage_metrics=None, shared_with_openai=False, eval_id=None)" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Create fine-tuning job - training happens on OpenAI's servers\n", + "openai.fine_tuning.jobs.create(\n", + " training_file=train_file.id,\n", + " validation_file=validation_file.id,\n", + " model=\"gpt-4o-mini-2024-07-18\",\n", + " seed=42, # For reproducibility\n", + " hyperparameters={\"n_epochs\": 1}, # Training passes\n", + " suffix=\"banking_intent\" # Custom model name\n", + ")" + ] + }, + { + "cell_type": "markdown", + "id": "dd2fe11f", + "metadata": {}, + "source": [ + "### Monitor Training Progress\n", + "Check job status and view training events\n" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "bb98e266", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Status: ftjob-FN3B5dQQOhuk4UVOZ5X4CqBU\n", + "Status: succeeded\n" + ] + } + ], + "source": [ + "# List most recent fine-tuning job to check status\n", + "job = openai.fine_tuning.jobs.list(limit=1).data[0]\n", + "print(f\"Status: {job.id}\")\n", + "print(f\"Status: {job.status}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "a503b4f3", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "FineTuningJob(id='ftjob-FN3B5dQQOhuk4UVOZ5X4CqBU', created_at=1761873619, error=Error(code=None, message=None, param=None), fine_tuned_model='ft:gpt-4o-mini-2024-07-18:hope-ogbons:banking-intent:CWYGwKT5', finished_at=1761874273, hyperparameters=Hyperparameters(batch_size=1, learning_rate_multiplier=1.8, n_epochs=1), model='gpt-4o-mini-2024-07-18', object='fine_tuning.job', organization_id='org-OFfqVJ5fIDV1i5BqCwT86Px6', result_files=['file-N5eUNWYhwaxJt2KSYEjpBU'], seed=42, status='succeeded', trained_tokens=9105, training_file='file-U84ceTSvNn833d6aPpWX4i', validation_file='file-ARVTnFJnHn2HpE9UAr9mr5', estimated_finish=None, integrations=[], metadata=None, method=Method(type='supervised', dpo=None, reinforcement=None, supervised=SupervisedMethod(hyperparameters=SupervisedHyperparameters(batch_size=1, learning_rate_multiplier=1.8, n_epochs=1))), user_provided_suffix='banking_intent', usage_metrics=None, shared_with_openai=False, eval_id=None)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Get detailed information about the job\n", + "openai.fine_tuning.jobs.retrieve(job.id)" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "d7008bdd", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[FineTuningJobEvent(id='ftevent-nsKcQzrX5kAlH71815ndMGr4', created_at=1761875045, level='info', message='The job has successfully completed', object='fine_tuning.job.event', data={}, type='message'),\n", + " FineTuningJobEvent(id='ftevent-BWM8ClTEEWO3rVf1bn8WdszY', created_at=1761875039, level='info', message='Usage policy evaluations completed, model is now enabled for sampling', object='fine_tuning.job.event', data={}, type='message'),\n", + " FineTuningJobEvent(id='ftevent-yyxA2AU1GvpP5Ii3WbxlDktc', created_at=1761875039, level='info', message='Moderation checks for snapshot ft:gpt-4o-mini-2024-07-18:hope-ogbons:banking-intent:CWYGwKT5 passed.', object='fine_tuning.job.event', data={'blocked': False, 'results': [{'flagged': False, 'category': 'harassment/threatening', 'enforcement': 'blocking'}, {'flagged': False, 'category': 'sexual', 'enforcement': 'blocking'}, {'flagged': False, 'category': 'sexual/minors', 'enforcement': 'blocking'}, {'flagged': False, 'category': 'propaganda', 'enforcement': 'blocking'}, {'flagged': False, 'category': 'hate', 'enforcement': 'blocking'}, {'flagged': False, 'category': 'hate/threatening', 'enforcement': 'blocking'}, {'flagged': False, 'category': 'illicit', 'enforcement': 'blocking'}, {'flagged': False, 'category': 'violence', 'enforcement': 'blocking'}, {'flagged': False, 'category': 'advice', 'enforcement': 'blocking'}, {'flagged': False, 'category': 'self-harm/intent', 'enforcement': 'blocking'}, {'flagged': False, 'category': 'self-harm/instructions', 'enforcement': 'non_blocking'}, {'flagged': False, 'category': 'sensitive', 'enforcement': 'blocking'}, {'flagged': False, 'category': 'highly-sensitive', 'enforcement': 'blocking'}, {'flagged': False, 'category': 'biological threats', 'enforcement': 'blocking'}, {'flagged': False, 'category': 'cyber security threats', 'enforcement': 'blocking'}], 'finetuned_model_checkpoint_id': 'ft:gpt-4o-mini-2024-07-18:hope-ogbons:banking-intent:CWYGwKT5'}, type='moderation_checks'),\n", + " FineTuningJobEvent(id='ftevent-yojUh3akovLiyB1gX7NN4UCn', created_at=1761874276, level='info', message='Evaluating model against our usage policies', object='fine_tuning.job.event', data={}, type='message'),\n", + " FineTuningJobEvent(id='ftevent-tGdquF1ECX2kirD3YMFZ68H2', created_at=1761874276, level='info', message='New fine-tuned model created', object='fine_tuning.job.event', data={}, type='message'),\n", + " FineTuningJobEvent(id='ftevent-sMiUeWRPavauz8yO7SJfWA3U', created_at=1761874248, level='info', message='Step 200/200: training loss=0.00, validation loss=0.00, full validation loss=0.00', object='fine_tuning.job.event', data={'step': 200, 'train_loss': 0.00013084411330055445, 'valid_loss': 0.0001373291015625, 'total_steps': 200, 'full_valid_loss': 0.000696044921875, 'train_mean_token_accuracy': 1.0, 'valid_mean_token_accuracy': 1.0, 'full_valid_mean_token_accuracy': 1.0}, type='metrics'),\n", + " FineTuningJobEvent(id='ftevent-C6XLihn75vu22sJBkSbBDZ6L', created_at=1761874239, level='info', message='Step 199/200: training loss=0.00', object='fine_tuning.job.event', data={'step': 199, 'train_loss': 8.850097947288305e-05, 'total_steps': 200, 'train_mean_token_accuracy': 1.0}, type='metrics'),\n", + " FineTuningJobEvent(id='ftevent-LUGsXqTJjgAIw8fQQLjaTewj', created_at=1761874239, level='info', message='Step 198/200: training loss=0.00', object='fine_tuning.job.event', data={'step': 198, 'train_loss': 0.00010757446580100805, 'total_steps': 200, 'train_mean_token_accuracy': 1.0}, type='metrics'),\n", + " FineTuningJobEvent(id='ftevent-4peUk2wOGyP7Pe0COgCEMtI1', created_at=1761874239, level='info', message='Step 197/200: training loss=0.00', object='fine_tuning.job.event', data={'step': 197, 'train_loss': 0.00012130737013649195, 'total_steps': 200, 'train_mean_token_accuracy': 1.0}, type='metrics'),\n", + " FineTuningJobEvent(id='ftevent-SyIiUrcSzUzoYBZMAMfgH3zh', created_at=1761874234, level='info', message='Step 196/200: training loss=0.00', object='fine_tuning.job.event', data={'step': 196, 'train_loss': 9.689330909168348e-05, 'total_steps': 200, 'train_mean_token_accuracy': 1.0}, type='metrics')]" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# View training events log (last 10 events)\n", + "openai.fine_tuning.jobs.list_events(fine_tuning_job_id=job.id, limit=10).data" + ] + }, + { + "cell_type": "markdown", + "id": "cb837277", + "metadata": {}, + "source": [ + "# Step 3\n", + "\n", + "### Use the fine-tuned model to classify banking queries" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "d710b977", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'ft:gpt-4o-mini-2024-07-18:hope-ogbons:banking-intent:CWYGwKT5'" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Get the fine-tuned model ID (only works after training succeeds)\n", + "fine_tuned_model_name = openai.fine_tuning.jobs.retrieve(job.id).fine_tuned_model\n", + "fine_tuned_model_name" + ] + }, + { + "cell_type": "markdown", + "id": "e9518959", + "metadata": {}, + "source": [ + "### Use Fine-Tuned Model\n", + "Classify banking queries with the trained model\n" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "5afef0bb", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'card_arrival'" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "def gpt_fine_tuned(item):\n", + " \"\"\"Classify banking query using fine-tuned model\"\"\"\n", + " response = openai.chat.completions.create(\n", + " model=fine_tuned_model_name,\n", + " messages=messages_for_inference(item), # Use inference format (no label)\n", + " seed=42,\n", + " max_tokens=20\n", + " )\n", + " intent = response.choices[0].message.content.strip()\n", + " return intent\n", + "\n", + "gpt_fine_tuned(train[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "5198c5c5", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model name: ft:gpt-4o-mini-2024-07-18:hope-ogbons:banking-intent:CWYGwKT5\n", + "\n", + "Job ID: ftjob-FN3B5dQQOhuk4UVOZ5X4CqBU\n", + "Status: succeeded\n", + "Fine-tuned model: ft:gpt-4o-mini-2024-07-18:hope-ogbons:banking-intent:CWYGwKT5\n" + ] + } + ], + "source": [ + "# Verify training completed successfully\n", + "print(\"Model name:\", fine_tuned_model_name)\n", + "print()\n", + "\n", + "print(\"Job ID:\", job.id)\n", + "job_status = openai.fine_tuning.jobs.retrieve(job.id)\n", + "print(\"Status:\", job_status.status)\n", + "print(\"Fine-tuned model:\", job_status.fine_tuned_model)" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "33683c39", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Test example: {'text': 'How do I locate my card?', 'label': 11}\n", + "Predicted intent: card_arrival\n" + ] + } + ], + "source": [ + "# Test the fine-tuned model on a single example\n", + "print(\"Test example:\", test[0])\n", + "print(\"Predicted intent:\", gpt_fine_tuned(test[0]))" + ] + }, + { + "cell_type": "markdown", + "id": "216f3164", + "metadata": {}, + "source": [ + "### Evaluate Model Performance\n", + "Test on 100 examples and calculate accuracy\n" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "b500717d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "✓ Converted 3080 test examples to list format\n" + ] + } + ], + "source": [ + "# Convert test to list format\n", + "test_list = [{'text': test[i]['text'], 'label': test[i]['label']} for i in range(len(test))]\n", + "\n", + "print(f\"✓ Converted {len(test_list)} test examples to list format\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "f0787061", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Testing Gpt Fine Tuned on 100 examples...\n", + "\n", + "\u001b[92m✓ 1: How do I locate my card?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 2: I still have not received my new card, I ordered over a week...\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 3: I ordered a card but it has not arrived. Help please!\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 4: Is there a way to know when my card will arrive?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 5: My card has not arrived yet.\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 6: When will I get my card?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 7: Do you know if there is a tracking number for the new card y...\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 8: i have not received my card\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 9: still waiting on that card\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 10: Is it normal to have to wait over a week for my new card?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 11: How do I track my card?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 12: How long does a card delivery take?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 13: I still don't have my card after 2 weeks. What should I do?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 14: still waiting on my new card\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 15: I am still waiting for my card after 1 week. Is this ok?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 16: I have been waiting longer than expected for my bank card, c...\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 17: I've been waiting longer than expected for my card.\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 18: Why hasn't my card been delivered?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 19: Where is my new card? I have been waiting a week!\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 20: My card still hasn't arrived after 2 weeks. Is it lost?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 21: I did not get my card yet, is it lost?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 22: Status of the card I ordered.\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 23: How long should my new card take to arrive?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 24: I ordered my card 2 weeks ago and it still isn't here? What ...\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 25: My card has not arrived yet, where is it?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 26: What is the tracking number for my card that was mailed?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 27: I think something went wrong with my card delivery as I have...\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 28: I'm still waiting for delivery of my new card, why is it tak...\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 29: I ordered a card a week ago, and it's still not here. What d...\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 30: i want to track the card you sent\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 31: My card hasn't arrived yet.\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 32: I was expecting my new card and am wondering why I haven't r...\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 33: How do I know when my card will arrive?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 34: I'm still waiting on my card to be delivered.\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 35: Does the card you sent have a way to track to it?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 36: I ordered a card and I still haven't received it. It's been ...\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 37: I'm starting to think my card is lost because it still hasn'...\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 38: Is there tracking info available?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 39: What is the tracking number for the card you sent?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 40: Where is the tracking number for the card you sent me?\n", + " Predicted: card_arrival | Actual: card_arrival\u001b[0m\n", + "\u001b[92m✓ 41: Why won't my card show up on the app?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 42: I would like to reactivate my card.\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 43: Where do I link the new card?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 44: I have received my card, can you help me put it in the app?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 45: How do I link a card that I already have?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 46: I received my new card, but I don't see it in the app anywhe...\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 47: How do I re-add a card to the app?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 48: How do I add the card to my account?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 49: Can I put my old card back into the system? I just found it/\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 50: I have one of your cards already, how do I link it?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 51: How do I link a new card?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 52: Can I link an existing card?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 53: How do I link one your card if I have one already?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 54: How do I add a card to the app?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 55: Can I link my new card?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 56: Hello, I found the card I misplaced and I need to reactive i...\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 57: Can you tell me how to link one of your cards that I already...\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 58: How do I view the card I received in the app?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 59: Where on the website do I go to link my card?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 60: I found my card, can I add it to the app?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 61: How do I link to my credit card with you?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 62: I've received my card so now I need to know how to sync it t...\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 63: I found my card, I would like to reactivate it.\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 64: How do I link this new card?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 65: Can I reactivate my lost card that I found this morning in m...\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 66: how do I link an already existing card?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 67: The app doesn't show the card I received.\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 68: how do I link a card I already have?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 69: I would like to link my card. How do I do it?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 70: Can you please show me where I can find the location to link...\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 71: Where do I go if I want to link my new card?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 72: Is there a way to make my old card usable with the app?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 73: Can I reactivate a card I thought I lost?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 74: How do I link my card\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 75: Where do I need to go in the app to enter my card info?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 76: I have found my lost or stolen card. Is there a way I can li...\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 77: Could you help me reactivate my card? It was previously lost...\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 78: I already have one of your cards, how do I link them?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 79: How do I link my replacement card?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[92m✓ 80: Can I link another card to my account?\n", + " Predicted: card_linking | Actual: card_linking\u001b[0m\n", + "\u001b[91m✗ 81: I need to know your exchange rates.\n", + " Predicted: exchange_rates | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 82: What exchange rates do you offer?\n", + " Predicted: currency_exchange | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 83: How did you come up with your exchange rates?\n", + " Predicted: currency_conversion | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 84: Where do you guys acquire your exchange rate?\n", + " Predicted: foreign_exchange_rates | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 85: How do I find the exchange rate?\n", + " Predicted: exchange_rate_arrival | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 86: What are your international exchange rates?\n", + " Predicted: currency_exchange | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 87: How often do your exchange rates change\n", + " Predicted: exchange_rate_change | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 88: Please advise what is the exchange rate\n", + " Predicted: currency_exchange | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 89: How are exchange rates calculated?\n", + " Predicted: currency_conversion | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 90: what are exchange rates based on\n", + " Predicted: currency_conversion | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 91: what are exchange rates\n", + " Predicted: exchange_rate_arrival | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 92: What are the most current exchange rates?\n", + " Predicted: exchange_rates | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 93: Can you explain your exchange rate policy to me?\n", + " Predicted: currency_conversion | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 94: Is it a good time to exchange?\n", + " Predicted: currency_exchange | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 95: What is the exchange rate like on this app?\n", + " Predicted: currency_conversion | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 96: Do you have a list of exchange rates?\n", + " Predicted: foreign_exchange_rates | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 97: Can you tell me where you get your exchange rates?\n", + " Predicted: exchange_rate_arrival | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 98: Will I get a curreng foreign exchange rate?\n", + " Predicted: currency_exchange | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 99: What currencies is an exchange rate calculated in?\n", + " Predicted: foreign_exchange_rates | Actual: exchange_rate\u001b[0m\n", + "\u001b[91m✗ 100: Where do you get your exchange rates from?\n", + " Predicted: foreign_exchange_rates | Actual: exchange_rate\u001b[0m\n", + "\n", + "======================================================================\n", + "MODEL: Gpt Fine Tuned\n", + "TESTED: 100 examples\n", + "CORRECT: 80 (80.0%)\n", + "INCORRECT: 20\n", + "======================================================================\n", + "\n", + "Most Common Errors:\n", + " exchange_rate → currency_exchange: 5 times\n", + " exchange_rate → currency_conversion: 5 times\n", + " exchange_rate → foreign_exchange_rates: 4 times\n", + " exchange_rate → exchange_rate_arrival: 3 times\n", + " exchange_rate → exchange_rates: 2 times\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Run comprehensive evaluation on 100 test examples\n", + "from classifier_tester import ClassifierTester\n", + "\n", + "accuracy = ClassifierTester.test(gpt_fine_tuned, test_list, size=100)\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": ".venv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}