{"cells":[{"cell_type":"markdown","metadata":{"id":"BDe-A0sNb-3C"},"source":["# **LyricLoop** - An AI-Powered Music Lyric Generator\n","\n","---\n","\n","**Author:** Alexander Tung  \n","\n","**Objective:** To bridge the gap between semantic text generation and musical structure. This project fine-tunes a Language Model (Google's Gemma-2b) to generate lyrics that adhere to specific musical phrasing (Verse, Chorus, Bridge) and distinct genre stylings (e.g., Pop, Rock, Electronic, and Hip-Hop).\n","\n","**Dataset:**\n","- **Corpus:** 5mm+ Song Lyrics (Genius Dataset)\n","    - Link: https://www.kaggle.com/datasets/carlosgdcj/genius-song-lyrics-with-language-information\n","- **Metadata:** Pitchfork Reviews (used for Genre/Artist mapping)\n","    - Link: https://www.kaggle.com/datasets/timstafford/pitchfork-reviews\n","\n","**Methods:**\n","- **Model:** Gemma-2b-it (Instruction Tuned)\n","- **Fine-Tuning:** Low-Rank Adaptation (LoRA) for parameter-efficient training.\n","- **Optimization:** 4-bit Quantization (QLoRA) via BitsAndBytes.\n","- **Training:** Supervised Fine-Tuning (SFT) with custom prompt templates to enforce structural constraints.\n","\n","**Stack:** Python, Hugging Face (Transformers, PEFT, TRL), PyTorch, Pandas, Google Colab (L4 GPU).\n","\n","---"]},{"cell_type":"markdown","metadata":{"id":"NoZxXwA4d-ug"},"source":["## Environment Setup"]},{"cell_type":"code","source":["# -------------------------\n","# Installation\n","# -------------------------\n","\n","# Install core libraries\n","%%capture\n","!pip install -q -U \"transformers>=4.40.0\" \"peft>=0.10.0\" datasets bitsandbytes accelerate trl"],"metadata":{"id":"LseRiRIZWDu7","executionInfo":{"status":"ok","timestamp":1768930959297,"user_tz":300,"elapsed":5567,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"execution_count":1,"outputs":[]},{"cell_type":"code","source":["# -------------------------\n","# Core Python Libraries\n","# -------------------------\n","\n","# Core\n","import os\n","import sys\n","import pandas as pd\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","import torch\n","\n","# UI & Display Utilities\n","import ipywidgets as widgets # <--- Fixes the 'widgets' NameError\n","from IPython.display import display, HTML\n","\n","# Standard ML Tools\n","from sklearn.model_selection import train_test_split\n","\n","# Hugging Face: Data & Authentication\n","from datasets import Dataset, DatasetDict\n","from google.colab import drive, userdata\n","from huggingface_hub import login\n","\n","# Hugging Face: Model Loading & Quantization\n","from transformers import (\n","    AutoTokenizer,\n","    AutoModelForCausalLM,\n","    BitsAndBytesConfig\n",")\n","\n","# Hugging Face: PEFT & LoRA\n","from peft import (\n","    LoraConfig,\n","    PeftModel,\n","    get_peft_model,\n","    prepare_model_for_kbit_training\n",")\n","\n","# Hugging Face: Training (TRL)\n","from trl import SFTTrainer, SFTConfig"],"metadata":{"id":"0gkQ17RNaepf","executionInfo":{"status":"ok","timestamp":1768933235592,"user_tz":300,"elapsed":6,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"execution_count":20,"outputs":[]},{"cell_type":"code","source":["# -------------------------\n","# Workspace Mounting\n","# -------------------------\n","\n","# Mount workspace\n","drive.mount('/content/drive', force_remount=False)\n","\n","# Point Python to your package source\n","PROJECT_PATH = '/content/drive/My Drive/repositories/lyricloop-llm'\n","sys.path.append(os.path.join(PROJECT_PATH, 'src'))\n","\n","# Change working directory to project root for data/asset access\n","os.chdir(PROJECT_PATH)\n","print(f\"Workspace ready: {os.getcwd()}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"paO1ARmkWKWh","executionInfo":{"status":"ok","timestamp":1768930973106,"user_tz":300,"elapsed":497,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}},"outputId":"fb407d87-36b6-4652-ffce-3c80dbeffef1"},"execution_count":3,"outputs":[{"output_type":"stream","name":"stdout","text":["Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n","Workspace ready: /content/drive/My Drive/repositories/lyricloop-llm\n"]}]},{"cell_type":"code","source":["# -------------------------\n","# Package Initialization\n","# -------------------------\n","\n","from lyricloop.config import (\n","    MODEL_ID, RANDOM_STATE, ensure_dirs, initialize_history\n",")\n","from lyricloop.environment import set_seed, get_device_capability\n","\n","# Initialize project folders and history tracking\n","ensure_dirs()\n","history = initialize_history()\n","\n","# Set global replicability and hardware diagnostics\n","set_seed(RANDOM_STATE)\n","DEVICE = get_device_capability()\n","\n","# Authenticate with Hugging Face\n","login(userdata.get('HF_TOKEN'), add_to_git_credential=True)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Zgt3gqKlWbA8","executionInfo":{"status":"ok","timestamp":1768930973501,"user_tz":300,"elapsed":394,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}},"outputId":"9935ed90-dcf6-4889-ed65-d308c69cfc7a"},"execution_count":4,"outputs":[{"output_type":"stream","name":"stdout","text":["Random Seed Set to: 42\n","GPU Detected: NVIDIA L4\n","    |-- Memory: 23.80 GB\n","    |-- Compute Capability: (8, 9)\n","    |-- BFloat16 Support: Yes\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.12/dist-packages/torch/backends/__init__.py:46: UserWarning: Please use the new API settings to control TF32 behavior, such as torch.backends.cudnn.conv.fp32_precision = 'tf32' or torch.backends.cuda.matmul.fp32_precision = 'ieee'. Old settings, e.g, torch.backends.cuda.matmul.allow_tf32 = True, torch.backends.cudnn.allow_tf32 = True, allowTF32CuDNN() and allowTF32CuBLAS() will be deprecated after Pytorch 2.9. Please see https://pytorch.org/docs/main/notes/cuda.html#tensorfloat-32-tf32-on-ampere-and-later-devices (Triggered internally at /pytorch/aten/src/ATen/Context.cpp:80.)\n","  self.setter(val)\n"]}]},{"cell_type":"code","source":["# -------------------------\n","# Modular Tool Imports\n","# -------------------------\n","\n","# Data & Prompting\n","from lyricloop.data import (\n","    prepare_lyric_dataset,\n","    format_prompt,\n","    build_inference_prompt,\n","    format_lyrics,\n","    build_critic_prompt,\n","    build_revision_prompt,\n","    format_critic_training_row\n",")\n","\n","# Evaluation & Generation\n","from lyricloop.metrics import (\n","    execute_generation,\n","    get_token_confidences,\n","    calculate_perplexity,\n","    extract_trainer_metrics\n",")\n","\n","# Visualization\n","from lyricloop.viz import (\n","    save_figure,\n","    plot_learning_curves,\n","    plot_token_heatmap,\n","    plot_confidence_summary,\n","    plot_perplexity\n",")"],"metadata":{"id":"OT1pIU1IWvJd","executionInfo":{"status":"ok","timestamp":1768930973507,"user_tz":300,"elapsed":2,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"execution_count":5,"outputs":[]},{"cell_type":"markdown","metadata":{"id":"ZsT616qbUNGU"},"source":["# Data Preparation"]},{"cell_type":"code","source":["# -------------------------\n","# Data Preparation & EDA\n","# -------------------------\n","\n","# Pipeline execution\n","lyrics_df = prepare_lyric_dataset(\n","    lyrics_filename=\"english_song_lyrics.csv\",\n","    reviews_filename=\"pitchfork_reviews.csv\",\n","    songs_per_genre=200\n",")\n","\n","print(f\"\\nPipeline Complete: {len(lyrics_df)} tracks ready for training.\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"maWJePTKOCDs","executionInfo":{"status":"ok","timestamp":1768931059941,"user_tz":300,"elapsed":86432,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}},"outputId":"c912fafd-a1cb-4da6-eef2-e60394693a93"},"execution_count":6,"outputs":[{"output_type":"stream","name":"stdout","text":["Loading & Cleaning Raw Data...\n","    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eda_1_raw_distribution.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x500 with 1 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eda_2_balanced_distribution.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x500 with 1 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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["\n","Pipeline Complete: 1200 tracks ready for training.\n"]}]},{"cell_type":"markdown","source":["# Feature Engineering"],"metadata":{"id":"CAl51wdlauDb"}},{"cell_type":"code","source":["# -------------------------\n","# Feature Engineering\n","# -------------------------\n","\n","# Apply formatting\n","print(\"Processing Prompts...\")\n","\n","# Create a new column 'text' that contains the full training data\n","lyrics_df['text'] = lyrics_df.apply(format_prompt, axis=1)\n","\n","# Train / Test Split (95% for training and 5% for validation/testing)\n","train_df, test_df = train_test_split(lyrics_df, test_size=0.05, random_state=42)\n","\n","print(f\"\\nDataset Split:\")\n","print(f\"    |-- Training Set: {len(train_df):,} songs\")\n","print(f\"    |-- Testing Set:  {len(test_df):,} songs\")\n","\n","# Convert to Hugging Face Dataset Format\n","dataset = DatasetDict({\n","    \"train\": Dataset.from_pandas(train_df),\n","    \"test\":  Dataset.from_pandas(test_df)\n","})\n","\n","print(\"\\nFeature Engineering Complete. Ready for Tokenization.\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"O4CAgmICaw-7","executionInfo":{"status":"ok","timestamp":1768931060048,"user_tz":300,"elapsed":98,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}},"outputId":"89b07806-178a-4b74-f35d-d665b542873d"},"execution_count":7,"outputs":[{"output_type":"stream","name":"stdout","text":["Processing Prompts...\n","\n","Dataset Split:\n","    |-- Training Set: 1,140 songs\n","    |-- Testing Set:  60 songs\n","\n","Feature Engineering Complete. Ready for Tokenization.\n"]}]},{"cell_type":"markdown","metadata":{"id":"c_otpMXxfAOx"},"source":["# Base Lyric Model (Gemma) Configuration"]},{"cell_type":"code","source":["# -------------------------\n","# Gemma Model Initialization & LoRA Config\n","# -------------------------\n","\n","# Quantization Config (4-bit Optimization)\n","bnb_config = BitsAndBytesConfig(\n","    load_in_4bit=True,\n","    bnb_4bit_quant_type=\"nf4\",    # use NF4 (Normal Float 4) and BFloat16 for maximum stability on L4 GPUs\n","    bnb_4bit_use_double_quant=True,\n","    bnb_4bit_compute_dtype=torch.bfloat16\n",")\n","\n","# Load Tokenizer\n","print(f\"Loading Tokenizer for {MODEL_ID}...\")\n","tokenizer = AutoTokenizer.from_pretrained(MODEL_ID, token=userdata.get('HF_TOKEN'))\n","tokenizer.pad_token = tokenizer.eos_token\n","tokenizer.padding_side = \"right\"    # safer for training stability\n","\n","# Load Base Model\n","print(\"Loading Model in 4-bit...\")\n","model = AutoModelForCausalLM.from_pretrained(\n","    MODEL_ID,\n","    quantization_config=bnb_config,\n","    device_map=\"auto\",\n","    attn_implementation=\"sdpa\",    # Scaled Dot Product Attention (Flash Attention 2 compatible)\n","    token=userdata.get('HF_TOKEN')\n",")\n","\n","# Prepare for Training\n","model = prepare_model_for_kbit_training(model)    # casts LayerNorm to float32 for stability and enables gradient checkpointing\n","\n","# LoRA Adapter Configuration\n","lora_config = LoraConfig(\n","    r=16,             # rank: higher = more parameters to train (16 is a sweet spot)\n","    lora_alpha=32,    # alpha: scaling factor (usually 2x Rank)\n","    target_modules=[\n","        \"q_proj\", \"k_proj\", \"v_proj\", \"o_proj\",\n","        \"gate_proj\", \"up_proj\", \"down_proj\"\n","    ],\n","    lora_dropout=0.05,\n","    bias=\"none\",\n","    task_type=\"CAUSAL_LM\"\n",")\n","\n","# Apply Adapters\n","model = get_peft_model(model, lora_config)\n","\n","print(\"\\nLoRA Adapters Applied!\")\n","model.print_trainable_parameters()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":138,"referenced_widgets":["15c139ce2fb64146947f30982e793dbe","e9d8929d80024eea8b6a49ba23c81285","f2d753ac00994f35b3bb7772d476d3d8","e4daa59c55b74a19978e2395afed836d","26cea7a2ea1b4bf58bc983316fe13f82","f3253d4b01ea4806aa573f1de6b42f82","46cf69c2291145d980f5f72b17485dfe","c83ac0e57e86402e86502772309cace4","9064d00ec67c47f9ab5a256cbe464e94","b59ebe42849449758021936b42b13ab2","0f807dc7c5ec49a693af1998ce493dc0"]},"id":"HsNre63Pd_b-","executionInfo":{"status":"ok","timestamp":1768931069275,"user_tz":300,"elapsed":9226,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}},"outputId":"ca094a97-df6e-4d82-b097-c6140bd4c383"},"execution_count":8,"outputs":[{"output_type":"stream","name":"stdout","text":["Loading Tokenizer for google/gemma-2b-it...\n","Loading Model in 4-bit...\n"]},{"output_type":"display_data","data":{"text/plain":["Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"15c139ce2fb64146947f30982e793dbe"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["\n","LoRA Adapters Applied!\n","trainable params: 19,611,648 || all params: 2,525,784,064 || trainable%: 0.7765\n"]}]},{"cell_type":"code","source":["# -------------------------\n","# Inference Engine: Baseline\n","# -------------------------\n","\n","def generate_baseline_lyrics(genre, artist, title, model, tokenizer, max_new_tokens=250):\n","    \"\"\"\n","    Local interface for Baseline generation.\n","    Uses global utilities for logic while maintaining the 'Baseline' narrative style.\n","    \"\"\"\n","    # Header print\n","    print(f\"Baseline: {title} - {artist}\")\n","    print(\"-\" * 50)\n","\n","    # Build the Prompt\n","    prompt = build_inference_prompt(genre, artist, title)\n","\n","    # Generate using the Global Engine\n","    raw_output = execute_generation(model, tokenizer, prompt, max_tokens=max_new_tokens)\n","\n","    # Format using the Global Cleaner\n","    formatted_lyrics = format_lyrics(raw_output)\n","\n","    # Display and Archive\n","    print(formatted_lyrics)\n","    print(\"-\" * 50)\n","\n","    # Save to history for the final report\n","    sample_id = f\"{artist} - {title}\"\n","    history[\"baseline\"][\"samples\"][sample_id] = formatted_lyrics\n","\n","    return formatted_lyrics"],"metadata":{"id":"et0Zn2_hw5jC","executionInfo":{"status":"ok","timestamp":1768931069289,"user_tz":300,"elapsed":6,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"execution_count":9,"outputs":[]},{"cell_type":"code","source":["# -------------------------\n","# Baseline Test (Untrained)\n","# -------------------------\n","print(\"Testing Baseline Model (Untrained)...\\n\")\n","\n","# Test Case: using a Taylor Swift Pop song\n","baseline_result = generate_baseline_lyrics(\n","    genre=\"Pop\",\n","    artist=\"Taylor Swift\",\n","    title=\"Sign of the Times\",\n","    model=model,           # passing the current untrained model\n","    tokenizer=tokenizer    # passing the current tokenizer\n",")\n","\n","print(baseline_result)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Mj3LZcXuwKTt","executionInfo":{"status":"ok","timestamp":1768931092116,"user_tz":300,"elapsed":22674,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}},"outputId":"8aba4d8e-3e09-49f0-cac9-a12b20b2d480"},"execution_count":10,"outputs":[{"output_type":"stream","name":"stdout","text":["Testing Baseline Model (Untrained)...\n","\n","Baseline: Sign of the Times - Taylor Swift\n","--------------------------------------------------\n","(Verse 1)\n","Neon signs paint the midnight sky,\n","Echoing the rhythm of a heart that flies.\n","Shattered glass and broken dreams,\n","A symphony of a thousand screams.\n","\n","(Pre-Chorus)\n","The echoes fade, the silence creeps in,\n","But the fire's still burning, a flicker within.\n","I stand tall against the storm's relentless rain,\n","My resolve unwavering, my spirit remains.\n","\n","**Chorus**\n","Sign of the times, a melody takes flight,\n","Guiding me through the darkness, shining bright.\n","From the ashes I rise, a phoenix reborn,\n","With a heart open, a story to be sworn.\n","\n","Verse 2\n","Scars from battles fought, both physical and mental,\n","They tell stories of a soul that's been well-rehearsed.\n","But scars are reminders, not of defeat,\n","Of the battles fought and the lessons I've kept.\n","\n","**(Bridge)**\n","There's a power in vulnerability,\n","In letting go and finding my equilibrium.\n","It's about embracing the pain, the joy, the whole,\n","Finding solace in the rhythm that'll always stroll.\n","\n","(**Chorus**)\n","Sign o\n","--------------------------------------------------\n","(Verse 1)\n","Neon signs paint the midnight sky,\n","Echoing the rhythm of a heart that flies.\n","Shattered glass and broken dreams,\n","A symphony of a thousand screams.\n","\n","(Pre-Chorus)\n","The echoes fade, the silence creeps in,\n","But the fire's still burning, a flicker within.\n","I stand tall against the storm's relentless rain,\n","My resolve unwavering, my spirit remains.\n","\n","**Chorus**\n","Sign of the times, a melody takes flight,\n","Guiding me through the darkness, shining bright.\n","From the ashes I rise, a phoenix reborn,\n","With a heart open, a story to be sworn.\n","\n","Verse 2\n","Scars from battles fought, both physical and mental,\n","They tell stories of a soul that's been well-rehearsed.\n","But scars are reminders, not of defeat,\n","Of the battles fought and the lessons I've kept.\n","\n","**(Bridge)**\n","There's a power in vulnerability,\n","In letting go and finding my equilibrium.\n","It's about embracing the pain, the joy, the whole,\n","Finding solace in the rhythm that'll always stroll.\n","\n","(**Chorus**)\n","Sign o\n"]}]},{"cell_type":"markdown","metadata":{"id":"dFc8DQkSFNat"},"source":["## Baseline Evaluation (Untrained Model)"]},{"cell_type":"code","source":["# -------------------------\n","# Baseline Evaluation: Perplexity (How confused is the model?)\n","# -------------------------\n","\n","# Calculation\n","print(\"Calculating Baseline Perplexity...\")\n","\n","# Test on real lyrics to see if the model 'understands' the genre style\n","genre_samples = {\n","    \"Hip-hop\": \"Yo, concrete jungle where dreams are made of, there's nothing you can't do.\",\n","    \"Pop\": \"Baby, you're a firework, come on show 'em what your worth.\",\n","    \"Country\": \"I got my toes in the water, ass in the sand, not a worry in the world.\",\n","    \"EDM\": \"Put your hands up, wait for the drop, let the bass kick.\",\n","    \"Classical\": \"The violins swell in a crescendo of nature's beauty, silence falls.\"\n","}\n","\n","genres = list(genre_samples.keys())\n","baseline_ppl_scores = [calculate_perplexity(model, tokenizer, text) for text in genre_samples.values()]\n","\n","# Store to History\n","history[\"baseline\"][\"scores\"] = baseline_ppl_scores\n","\n","# Use the Global Plotter\n","plot_perplexity(\n","    genres=genres,\n","    scores_dict={\"Baseline (Untrained)\": baseline_ppl_scores},\n","    title=\"Baseline Model Confusion (Perplexity)\",\n","    filename=\"eval_1_baseline_perplexity.png\"\n",")\n","\n","print(\"Interpretation: Higher bars indicate the model is more uncertain about generating text for that genre.\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":660},"id":"EAdhFvCWyBTG","executionInfo":{"status":"ok","timestamp":1768931093244,"user_tz":300,"elapsed":1118,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}},"outputId":"e9fd2ff9-41ce-4d73-dbad-d096a0675e37"},"execution_count":11,"outputs":[{"output_type":"stream","name":"stdout","text":["Calculating Baseline Perplexity...\n","    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_1_baseline_perplexity.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x600 with 1 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Interpretation: Higher bars indicate the model is more uncertain about generating text for that genre.\n"]}]},{"cell_type":"code","execution_count":12,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"_OYYGe2zFE23","outputId":"f7c4b680-9e42-4d1f-a511-8df350c1800e","executionInfo":{"status":"ok","timestamp":1768931117395,"user_tz":300,"elapsed":24146,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["\n","Baseline Confidence Analysis (Heatmaps)...\n"]},{"output_type":"stream","name":"stderr","text":["/content/drive/My Drive/repositories/lyricloop-llm/src/lyricloop/viz.py:19: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n","  plt.tight_layout()\n"]},{"output_type":"stream","name":"stdout","text":["    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_2_heatmap_hip-hop.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x400 with 1 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_2_heatmap_pop.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x400 with 1 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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_2_heatmap_country.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x400 with 1 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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_2_heatmap_edm.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x400 with 1 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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_2_heatmap_classical.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x400 with 1 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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_3_confidence_summary.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1100x600 with 1 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(High Confidence): The model is sure about this word (common grammar or memorized phrases).\n","Orange (Uncertainty): The model is making a creative guess.\n","Red (Confusion): The model is struggling to predict the next word (common in untrained models).\n"]}],"source":["# -------------------------\n","# Baseline Evaluation: Confidence Heatmaps (Where is it looking?)\n","# -------------------------\n","\n","print(\"\\nBaseline Confidence Analysis (Heatmaps)...\")\n","\n","test_cases = [\n","    (\"Hip-hop\", \"Write a rap verse about success.\"),\n","    (\"Pop\", \"Write a pop chorus about love.\"),\n","    (\"Country\", \"Write a country verse about trucks.\"),\n","    (\"EDM\", \"Write an EDM drop with energy.\"),\n","    (\"Classical\", \"Write a classical poem about nature.\")\n","]\n","\n","baseline_avg_confidences = []\n","\n","# Loop through genres to generate heatmaps\n","for genre, prompt in test_cases:\n","    # Get tokens and probabilities\n","    pairs = get_token_confidences(model, tokenizer, prompt)\n","\n","    # Plot and save heatmap\n","    avg_conf = plot_token_heatmap(\n","        pairs,\n","        title=f\"Baseline Confidence: {genre}\",\n","        filename=f\"eval_2_heatmap_{genre.lower()}.png\"\n","    )\n","    baseline_avg_confidences.append(avg_conf)\n","\n","# Store in History\n","history[\"baseline\"][\"avg_confidence\"] = baseline_avg_confidences\n","\n","# Plot the confidence summary\n","plot_confidence_summary(\n","    genres=[t[0] for t in test_cases],\n","    scores=baseline_avg_confidences,\n","    title=\"Baseline Average Confidence by Genre\",\n","    filename=\"eval_3_confidence_summary.png\"\n",")\n","\n","print(\"\\nInterpretation:\")\n","print(\"Green (High Confidence): The model is sure about this word (common grammar or memorized phrases).\")\n","print(\"Orange (Uncertainty): The model is making a creative guess.\")\n","print(\"Red (Confusion): The model is struggling to predict the next word (common in untrained models).\")"]},{"cell_type":"markdown","metadata":{"id":"Wb1CN3yopZJf"},"source":["# Training Loop (lyricloop-1.0)"]},{"cell_type":"code","execution_count":13,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":484,"referenced_widgets":["d8f72dee0b184965b61c48d2807657af","249165b33c1046e3bfa1673515884965","05f952dfc38242379d0a1fc30824dccb","d0d6e0872e494946913303348b743090","75cf7f7b4edc4cd8958e50324e8ace7c","ea4c1c9164c84f74a977f72f1fde01c4","7bf0584cfc3b42078d75f9874da829e9","1d146f01d3c0436787bb3043f5c8206c","5d6c2257b35a4c7bb860b72f37524727","d96ed86e1a404f7c866e08cd5f93779a","26974496447a4394aee2d3c396c45547","dbf5e2a747b44601b13b5290e66a252f","6b09662419f64a0bb219384e6036d063","65948855e62b423e93ca733f89dcd4d6","1236e9c7eaa24c3c9a80942b7d8419ba","898ae32fc3474ea3b3ba9a61813ec97b","5f55b0f16bcb48f59c6fd0f4a03190fa","6a9a61269f1a45b6a1e5192281317729","a9eec17c29074ee693feaaf03a900245","8b902155eafd4cf3a71726ed75518f23","86fe52ff4bfc48f09ec86b5e7ac5ef3f","c751077294cf4c2285e5a56b8d34d37f","4c2d60bf5f874da0a6423d533f82e476","25ca750afbf342278bc4e370d910768a","26022c0602e54773a2ee186bd93dc837","1f739dd71de14a9a944d24504c44c5d2","5cded5b568d447098b56b3f66844a19f","67f97b4afb944b0aa7c2d550255c0b2e","a34da757205543c6b5256dde0225eaf6","aa1354f158b0413da6c828d6f90e26c9","ba73d4bd9dc94b7a8107536fba8052b1","16af8e95433f46df89f401b8623c5e26","3da38c319c454085aa678fe0b1b9629f","19e2c859799049e89e93b48d602bae86","088d07fa78c048bdb2b0ef5f8ff04fff","08a3f0e238e244bcb451391c419f01d8","819d2163d370461ebfa061f8c6b7b141","c2de719d885a462ba6a9a6507e00b8ed","e1987637b0ed41f3bc471631b4633bc4","e3b77fee506c4b3cbfaf643d7c9fb0d4","abf2828eb3504acabcc950944c684ea7","97604121f90942a4b20f58fd7105e582","6ea821414e20443fa717c8447b4f0daf","16faeca9b0484b20922cface8599f2d7","ff56e879f37e4cdd9e1fd07c57435427","0d4702ca7658431b9005b37a7b0f10d7","edc8e14cdf42482d9c52c7b01f34e7de","93c7de3ed5d94cd08de16e7257b62497","e0694c5a0b024a218e928d4f90d2cb5f","dd5135d13aae4e059579ac97c062aed6","10c9eea5c2924c77bbbe17bdfee56a6a","edc6857798674c5e96a7a361865c5282","0239c6fadd754606a1be5835feb8b3b2","ceebae310eb14852877a1d0c0a10cc76","a577436a3720463787c47a6f620bbe14","e94960108c704778a80cef41fc1fb21b","83fde8e1491e4229a6e0cb1d1500d30b","0bb4f6561db24ba5ae3326872f2e5134","1db2799c0eff4ad39aa2b5c6dc93fa6d","ac57a2f73aba4ea7a58e063de026415f","a042b3b44bac4b47add889df9aeb11d3","3e7edda85d6a4882aa885d3ff4100b4f","5f23644cdf864ef09f9c5681dfb93270","7b38289974f74618a2325009e21d22a7","6bf100d1531b41fcb50bfba9728ef9fc","8e88af61d28642cd86a5a9132fae7f97"]},"id":"QMwHUb72qqFm","outputId":"a663e15b-7453-4723-987a-2e930d1d0290","executionInfo":{"status":"ok","timestamp":1768932729914,"user_tz":300,"elapsed":1612512,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["Initializing Trainer...\n"]},{"output_type":"display_data","data":{"text/plain":["Adding EOS to train dataset:   0%|          | 0/1140 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"d8f72dee0b184965b61c48d2807657af"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Tokenizing train dataset:   0%|          | 0/1140 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"dbf5e2a747b44601b13b5290e66a252f"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Truncating train dataset:   0%|          | 0/1140 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"4c2d60bf5f874da0a6423d533f82e476"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Adding EOS to eval dataset:   0%|          | 0/60 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"19e2c859799049e89e93b48d602bae86"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Tokenizing eval dataset:   0%|          | 0/60 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"ff56e879f37e4cdd9e1fd07c57435427"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Truncating eval dataset:   0%|          | 0/60 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"e94960108c704778a80cef41fc1fb21b"}},"metadata":{}},{"output_type":"stream","name":"stderr","text":["The tokenizer has new PAD/BOS/EOS tokens that differ from the model config and generation config. The model config and generation config were aligned accordingly, being updated with the tokenizer's values. Updated tokens: {'pad_token_id': 1}.\n"]},{"output_type":"stream","name":"stdout","text":["Starting Training Loop...\n"]},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["\n","    <div>\n","      \n","      <progress value='429' max='429' style='width:300px; height:20px; vertical-align: middle;'></progress>\n","      [429/429 26:33, Epoch 3/3]\n","    </div>\n","    <table border=\"1\" class=\"dataframe\">\n","  <thead>\n"," <tr style=\"text-align: left;\">\n","      <th>Step</th>\n","      <th>Training Loss</th>\n","      <th>Validation Loss</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <td>86</td>\n","      <td>2.337100</td>\n","      <td>2.280491</td>\n","    </tr>\n","    <tr>\n","      <td>172</td>\n","      <td>1.888100</td>\n","      <td>2.136576</td>\n","    </tr>\n","    <tr>\n","      <td>258</td>\n","      <td>1.654600</td>\n","      <td>1.945740</td>\n","    </tr>\n","    <tr>\n","      <td>344</td>\n","      <td>1.320000</td>\n","      <td>1.938518</td>\n","    </tr>\n","  </tbody>\n","</table><p>"]},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Training complete! Model saved to: models/lyricloop-1.0\n"]}],"source":["# -------------------------\n","# Training Loop\n","# -------------------------\n","\n","# Define model version\n","MODEL_VERSION = \"1.0\"\n","\n","# Define directories\n","EXPERIMENT_DIR = f\"experiments/{MODEL_VERSION}-run\"\n","FINAL_MODEL_DIR = f\"models/lyricloop-{MODEL_VERSION}\"\n","\n","# Define Training Configuration (optimized for Google Colab L4 GPU - 24GB VRAM)\n","training_args = SFTConfig(\n","    output_dir=EXPERIMENT_DIR,\n","\n","    # --- Memory Optimization ---\n","    per_device_train_batch_size=2,        # smaller batch size fits in VRAM better\n","    per_device_eval_batch_size=2,\n","    gradient_accumulation_steps=4,        # accumulate to simulate batch_size=8\n","    gradient_checkpointing=True,\n","\n","    # --- Optimizer & Rate ---\n","    learning_rate=2e-4,                   # standard QLoRA rate\n","    optim=\"paged_adamw_8bit\",             # paged optimizer prevents OOM spikes\n","    warmup_ratio=0.03,                    # warmup for stability\n","    lr_scheduler_type=\"cosine\",           # smooth decay\n","\n","    # --- Evaluation Strategy ---\n","    eval_strategy=\"steps\",\n","    eval_steps=0.2,                       # evaluate 5 times per epoch\n","    logging_steps=0.1,\n","    save_strategy=\"steps\",\n","    save_steps=0.2,\n","    save_total_limit=2,                   # only keep top 2 models to save disk space\n","    load_best_model_at_end=True,          # ensure keep the best version\n","    metric_for_best_model=\"eval_loss\",\n","\n","    # --- Duration ---\n","    max_steps=-1,          # disable step limit\n","    num_train_epochs=3,    # approx 30 min run\n","\n","    # --- Precision ---\n","    bf16=True,                         # L4 supports BFloat16\n","    fp16=False,\n","    group_by_length=True,              # groups short songs together for speed\n","    report_to=\"none\"                   # disable WandB for this demo\n",")\n","\n","# Initialize the Trainer\n","print(\"Initializing Trainer...\")\n","trainer = SFTTrainer(\n","    model=model,\n","    train_dataset=dataset[\"train\"],\n","    eval_dataset=dataset[\"test\"],\n","    processing_class=tokenizer,\n","    args=training_args,\n",")\n","\n","# LayerNorm Fix (required for QLoRA stability - prevents NaN loss errors)\n","for name, module in trainer.model.named_modules():\n","    if \"norm\" in name:\n","        module = module.to(torch.float32)\n","\n","# Execute Training\n","print(\"Starting Training Loop...\")\n","trainer.train()\n","\n","# Save the Adapter\n","trainer.model.save_pretrained(FINAL_MODEL_DIR)\n","tokenizer.save_pretrained(FINAL_MODEL_DIR)\n","print(f\"Training complete! Model saved to: {FINAL_MODEL_DIR}\")"]},{"cell_type":"code","execution_count":14,"metadata":{"id":"kbzCE-qfrFgR","executionInfo":{"status":"ok","timestamp":1768932729919,"user_tz":300,"elapsed":3,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"outputs":[],"source":["# -------------------------\n","# Inference Step: LyricLoop 1.0\n","# -------------------------\n","\n","def lyricloop(genre, artist, title):\n","    \"\"\"\n","    The primary user-facing interface for the Songwriter model.\n","    Usage: lyricloop(genre=\"EDM\", artist=\"Illenium\", title=\"Ascend\")\n","    \"\"\"\n","    print(f\"Generating: {title} by {artist} ({genre})...\")\n","\n","    # Build the prompt using the Global Utility\n","    prompt = build_inference_prompt(genre, artist, title)\n","\n","    # Run the Engine\n","    raw_output = execute_generation(model, tokenizer, prompt)\n","\n","    # Clean and Format\n","    formatted_lyrics = format_lyrics(raw_output)\n","\n","    print(\"-\" * 50)\n","    print(formatted_lyrics)\n","    print(\"-\" * 50)\n","\n","    # Archive this sample in history for our portfolio report\n","    history[\"1.0\"][\"samples\"][f\"{artist}-{title}\"] = formatted_lyrics\n","\n","    return formatted_lyrics"]},{"cell_type":"code","execution_count":15,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"cP58Ca3y8gVH","outputId":"a2a96788-88d5-4e47-e340-0712292c3fee","executionInfo":{"status":"ok","timestamp":1768932756943,"user_tz":300,"elapsed":27022,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["Running LyricLoop 1.0...\n","\n","Generating: City Fades Out by Kendrick Lamar (Hip-hop)...\n","--------------------------------------------------\n","[Verse 1]\n","\n","I'm just a kid from Compton, L.A., where dreams go to die\n","But I'm still alive, 'cause I'mma make it out alive\n","And I'ma do it all with my own two hands\n","No help from the angels, but I'll never be alone\n","I got my homies, my niggas, my homiez, my homeboys\n","We gon' get it, we gon' rock it, and we gon'- rock it\n","We got the whole city on lock down\n","They know we got the money, they know we ain't scared\n","We don't need no help, we don'ts need no more\n","We just want our money, we just want to get out here\n","And we just wanna live, we wanna live in peace\n","But they know that we got something, they gonna take it away\n","So we gotta keep it hidden, keep it underground\n","Keep it underground, keep the money underground\n","\n","\n","[Hook]\n","\n","(City fades out)\n","(Yeah)\n","City fades, city fades out\n","(Fade out)\n","\n","\n","\n","[Verse Two]\n","\n","We come from the bottom, we come from Compton\n","Where dreams go, where dreams die\n","And you can't trust nobody, you can never trust a nigga\n","You can'ts trust nobody 'less he your brother\n","But we got some niggas, some of the best niggas\n","Some of the most real niggas\n","--------------------------------------------------\n"]}],"source":["# -------------------------\n","# Testing (LyricLoop 1.0)\n","# -------------------------\n","\n","print(\"Running LyricLoop 1.0...\\n\")\n","\n","# High fidelity generation\n","history[\"1.0\"][\"samples\"][\"hiphop_city_fades_out\"] = lyricloop(\n","    genre=\"Hip-hop\",\n","    artist=\"Kendrick Lamar\",\n","    title=\"City Fades Out\"\n",")"]},{"cell_type":"markdown","metadata":{"id":"BVrOwty_1YqZ"},"source":["## Model Evaluation (lyricloop-1.0)"]},{"cell_type":"code","execution_count":16,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":714},"id":"tecsntFP8pqu","outputId":"cecf5bb8-9ec9-455a-f58a-e4a1d19f208d","executionInfo":{"status":"ok","timestamp":1768932757635,"user_tz":300,"elapsed":703,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["Analyzing metrics for 1.0...\n","    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_loss_curve_1.0.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1200x600 with 1 Axes>"],"image/png":"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Metrics Summary (1.0)\n","    Validation Loss: 1.9385\n","    Perplexity:      6.9484\n"]}],"source":["# -------------------------\n","# Loss Curves & Metrics (1.0)\n","# -------------------------\n","\n","print(f\"Analyzing metrics for {MODEL_VERSION}...\")\n","\n","# Extract from trainer\n","v1_metrics = extract_trainer_metrics(trainer)\n","\n","# Save to versioned history\n","history[\"1.0\"][\"metrics\"] = v1_metrics\n","\n","# Plot and Print\n","plot_learning_curves(v1_metrics, version=\"1.0\")\n","\n","if v1_metrics[\"val_loss\"]:\n","    print(f\"\\nFinal Metrics Summary ({MODEL_VERSION})\")\n","    print(f\"    Validation Loss: {v1_metrics['val_loss']:.4f}\")\n","    print(f\"    Perplexity:      {v1_metrics['perplexity']:.4f}\")"]},{"cell_type":"code","execution_count":17,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":785},"id":"9wCrw67a4QxT","outputId":"945bd59b-3297-4e83-f483-e5a26626e677","executionInfo":{"status":"ok","timestamp":1768932758900,"user_tz":300,"elapsed":1262,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["Running Comparative Perplexity Analysis for 1.0...\n","    |-- Calculating Fine-Tuned Perplexity...\n","    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_4_perplexity_comparison.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x600 with 1 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["\n","Perplexity (PPL) Improvement Summary:\n","   |-- Hip-hop   :  316.0 ->   3.8 (Improved by 98.8%)\n","   |-- Pop       : 1351.9 ->   2.9 (Improved by 99.8%)\n","   |-- Country   :  343.7 ->   3.3 (Improved by 99.0%)\n","   |-- EDM       : 3357.6 ->   3.5 (Improved by 99.9%)\n","   |-- Classical : 8021.7 ->   6.9 (Improved by 99.9%)\n"]}],"source":["# -------------------------\n","# Comparison: Baseline VS. LyricLoop 1.0\n","# -------------------------\n","print(\"Running Comparative Perplexity Analysis for 1.0...\")\n","\n","# Setup test cases\n","test_genres = [\"Hip-hop\", \"Pop\", \"Country\", \"EDM\", \"Classical\"]\n","test_data = [\n","    (\"Hip-hop\", \"Kendrick Lamar\", \"City Struggle\"),\n","    (\"Pop\", \"Taylor Swift\", \"First Love\"),\n","    (\"Country\", \"Luke Combs\", \"Dirt Road\"),\n","    (\"EDM\", \"Zedd\", \"Last Hope\"),\n","    (\"Classical\", \"Mozart\", \"Nature Choral\")\n","]\n","\n","# Generate prompts & calculate scores\n","test_prompts = [build_inference_prompt(g, a, t) for g, a, t in test_data]\n","\n","print(\"    |-- Calculating Fine-Tuned Perplexity...\")\n","v1_ppl_scores = [calculate_perplexity(model, tokenizer, p) for p in test_prompts]\n","\n","# Save to history for persistence and final reporting\n","history[\"1.0\"][\"scores\"] = v1_ppl_scores\n","baseline_scores = history[\"baseline\"][\"scores\"]\n","\n","# Visualization\n","plot_perplexity(\n","    genres=test_genres,\n","    scores_dict={\n","        \"Baseline (Untrained)\": baseline_scores,\n","        \"LyricLoop 1.0 (Fine-Tuned)\": v1_ppl_scores\n","    },\n","    title=\"Impact of Fine-Tuning on Model Uncertainty\",\n","    filename=\"eval_4_perplexity_comparison.png\",\n","    use_log=False\n",")\n","\n","# Numerical improvement summary\n","print(\"\\nPerplexity (PPL) Improvement Summary:\")\n","for g, base, new in zip(test_genres, baseline_scores, v1_ppl_scores):\n","    improvement = (base - new) / base * 100\n","    print(f\"   |-- {g:10}: {base:6.1f} -> {new:5.1f} (Improved by {improvement:.1f}%)\")"]},{"cell_type":"code","execution_count":18,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000},"id":"H3h8vMgM36Om","outputId":"7a9416bc-2669-4df9-9adb-d115c592b9a5","executionInfo":{"status":"ok","timestamp":1768932784287,"user_tz":300,"elapsed":25384,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"outputs":[{"output_type":"stream","name":"stdout","text":["Generating LyricLoop 1.0 Confidence Analysis...\n"]},{"output_type":"stream","name":"stderr","text":["/content/drive/My Drive/repositories/lyricloop-llm/src/lyricloop/viz.py:19: UserWarning: This figure includes Axes that are not compatible with tight_layout, so results might be incorrect.\n","  plt.tight_layout()\n"]},{"output_type":"stream","name":"stdout","text":["    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_5_heatmap_1.0_hip-hop.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x400 with 1 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_5_heatmap_1.0_pop.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x400 with 1 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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_5_heatmap_1.0_country.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x400 with 1 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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_5_heatmap_1.0_edm.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x400 with 1 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BAAAAGSlLhP2SJUuaQt2KFSv0xx9/SEp6zNWjQv3ThJzktYlp8Wzs5I8RO3DggNmw5K/vj5d8+cmH79+/P9UyJpe8c7Pk06Z2a0N6ePHFF01/3w+lkszuKc8MjzuMiYnR2LFjTa+DgoL+tTf3ihUrmu699vb2VrVq1Z56mdmzZzfN4/69+8k9XOv8KMnDZPLa8fHjx5tacDRq1Mj0nc+ZM6fpqQGRkZE6ffq0aZrkn8vzOH/+fKoXMJJ/Z5O3hEitE74LFy6YXRBI6wt0J0+eNF1MSS55Wf6ttcb48eMVHh6uwYMHy9ra2nQB6/4Frvv/J7+wJZl/1vfv8QcAAAAyWqZpxn/48GGzMHZf9+7d5ebmptdff10jR47UlStXTMMe1YT/aTVp0kTHjh2TJH3xxRe6efOmSpYsqZCQEP3222+pdnZ38eLFVMvbunVrVa1aVe7u7goLC9OhQ4c0fPhwvfzyy9q8ebPpsXseHh6me+0bNWpkul96+PDhunv3rqysrMzm/6h1HTp0qD788ENFR0dr3Lhxpvdr16792PXevXu3bt26laKjsftNw3PkyGHqLG7RokUaMGCAJOm9995Tr169JEmtWrUyPX5vypQpypkzp6ysrDRlyhRJSa0vkteSP2o+T+LOnTup9uwfGBiYapP8Q4cOKTg4WOfOndMvv/xi2sY2NjZmj51LjZWVlQYPHqz9+/erRIkSZvdkP42yZcvq3LlzCg4O1p07d0zlvN9ng5T0OL/7tcT3JX884OrVqzVw4EBZW1ubOiY8fvy4Wad295vwS5K1tbVq1qxpujf9448/Vo8ePXTlyhXNnDkz1XIGBwebvjMVKlRI0UT/YX///bdGjx6tpk2bqmLFirK1tdWff/6p33//3TRO8u9g79695eXlpYYNG6pAgQK6cuWKpk6dahpeuHBhs04Ma9WqZer8MXlfApcuXTKF9eRPUzh06JAcHR0lJd1O4ODgoNWrV+vXX39VixYtVLZsWSUkJGj58uWmJvz3l5OaY8eOaf78+WrYsKHpYtX9cH+/NcD9/+93pHnf/Y4f7ezsTP0tAAAAABkt04T9EydO6MSJEyneb9Omjdzc3EydpiV/Hna9evXSZNmdOnXS1q1btX37dkVGRmr8+PGPnebKlSv64YcfUrz/0ksvydfXVyNHjlSfPn0UGxurOXPmaM6cOaZxbGxsNHLkSFM46dKli/7880/99ddfunTpUorgV758eXXp0iXVcjg4OKhPnz5m7xUpUsTsHuJHmTRpknbv3p3i/fvPan+S0PfCCy+oR48e+vbbb01PIUjuvffeU9GiRR9blidx9OhRtW/fPsX7M2fOVMWKFVO8n/yZ8/c5Ojpq7NixT3TvevXq1U292z+revXqadGiRaZO6+53wrdmzRrTRZZq1aqpQ4cOKaZdunSpjh49quvXr2vXrl2mx8A1btzYLAAXL15chQoVMpu2T58+2rx5s27fvq3Dhw+rZ8+ekmS6UJAWwsPDNXPmzFQvIDRo0MC0rvf99ddfqV6scXR01IgRI55ombt27TJdLEou+T62YcMG060j169fN114etibb75pdttBciNHjkzxuMYmTZrou+++08KFC1W+fHn99NNPkmS2r8XGxpouJtSoUcOso0oAAAAgI2WJZvxSUgdm9zvzkpKCWPJer5+HjY2NfvjhBw0ePFilSpWSo6Oj7Ozs5Ofnp1atWj3TPOvUqaN58+apfv36ypkzp7Jnz64cOXKoXr16mjt3rlmtp62traZPn66+ffsqMDBQ9vb2srOzU5EiRdS3b1/99NNPjwwNM2bMUNOmTeXi4iInJyc1bNhQ06dPl52d3TOV+1n06tVL48aNU1BQkBwdHeXo6KigoCCNGzdOPXr0yLByPMzKyko2Njby9PRUUFCQevToobVr1z5Rq4e08tJLL8nT01OSzHqbT96E/1G1y/efyvDw+I0bNzZraZC8Vv8+X19fzZo1SxUqVJCdnZ08PT317rvvmkK/lNT55bOqUaOGBgwYoEqVKsnLy0s2NjZydnZW2bJlNWLECI0fP97sVpqRI0eqdevWCggIkKurq2xsbOTj46PXX39dS5cuTdOOA+9r0aKFPvjgAwUFBcnT01M2NjZyc3NTlSpVNGnSJH3yySepTrdy5Urt3r1b3bp1k5eXl+n9PHny6Mcff1SOHDnUrVs3nT59Wp9//rnZcWnXrl0KDw+XJIs9dQIAAACQJKvELNR19JIlS0wn6OPGjXtk53xG96gmzsicvv/+e3399deyt7fXpk2bMqzTtsTExBR9V4wdO9bUImXAgAGPbDGCZ9O7d2+tXr1ahQsX1u+///7Mt38AAAAAzytLnIlGRUXpypUrWrhwoaSk51g/qjYUyGw6dOignDlz6t69e5o3b16GLbdNmzZasWKFzp49q7Nnz2rmzJmm2zJsbGxUt27dDCvLf8GlS5e0bt06SUm3rxD0AQAAYEmZ5p79f9OwYUNTTbYkde3a9bmaIAMZydHR0dQZX0bat29fqr3vW1lZacCAAWaPTcTz8/Hx0ZEjRyxdDAAAAEBSFgn793l6eqpFixZ66623LF0UINPr2LGjdu/ercuXL+vevXvy8PBQUFCQOnXqlCkehwgAAAAg/WSpe/YBAAAAAMDjcVMpAAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIPJnpELW6/1zzRdHdVJ0/llFo9ar4ySWT6PzD6/51nmI93e+WwLcq2U+vtHjz7b/LKKYsUsXYJHsuRxKE2PIVn9O2Tp78iz7tMZ4VHHjbT2XzquZdT3jW1g2X0rDfcdzlmfj6HP4YB0RM0+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABhMpgj7Q2oNUc/AnuoZ2FMRtyIsXRxkYjP7zzR9V/au3mvp4kDS0TNnFNismYJDQp57Xut37lRgs2bPXyhkCR0HDVJgs2YKbNZMw7//PsXwRRs2mIYHtWljgRICWcuugwcV2KyZbt2+nWbzvB0RocBmzbTr4ME0myfS1oKRCzS+43hLFwNAJpShHfT9m1d6vqKX2r4kJw+nZ5p+3Q/rtH7aeo3eMVpWVlam93/97Fed+uuUBi0blFZFxVO4cuqKlk9YrnP7zyksJExdJ3RV2QZln3l+LQe1VNO+TTWw2sA0LKXl9R/2gxav2Jri/eN7fk7X5XYcNEiF/fw09K23nnkehf38tHX6dOVwdU3Dkhnf+I7j5VXYS62HtrZ0USxmUv/+io2LU6/Ro1Md/mq1anqpbFmt3LpV4+fMyeDSAYDlPclvRaPejRQfF5+BpUJyljqHA55EpqjZlyR7J3u5ebqZBfWnUbxGcUWERujy8ctm7x/feVwlapZIiyLiGURHRitnvpxqMbBFmszPwcVBbp5uaTKvzGTQR+21ddUEvdm+gQr4eWnrqgnaumqCpYv1RLJnyyZPDw9ly5bN0kVBFuPu4iJPDw/ZZE/9urO9nZ08PTzk4uiYwSUDgKzD3tleTu7PVlmG55eVz+FgfJmmZv95eRf2Vk6fnDq+87h8ivpIksKvhSvkTIhK1igpSQo+FqyFXyzU2X1n5ZzDWZWaVdIrPV9RtuwPQsr9K6jOOZy1efZmxdyL0cvtX1azj5tJkjbN3qQ/ZvyhsJAwueRyUYUmFdTkgyam6W8G39SCUQt0fMdx2TnZqUzdMnqt32uydbDNuI2RifiX8pd/KX9J0jRNs2xhMjEXZ0e5ODvK0dFe2bNZyzOXe7our+OgQdp9+LAkaffhw5qzcqUk6YtevdS8dm2z8Qr7+SmHq6tmr1ype9HRav/qq/q4c2ddvXFDL3frZhp3w9Spypcnj9lygkNCNGraNO04cEBODg6qW6mS+nXpIgc7O0nSjbAw9Z84UbsOHpS/l5fqV6mSruudGYzvOF4nd5+UJJ3cfVKb52yWJHX4ooMqN68sKek4Mm/YPJ3cc1K29rYq+0pZtRjYQja2NhYrd2ri4uP1v99+0+KNG3U9LEz+Xl56r00b0+c4felSLdqwQReuXpW9nZ1qVaigQV27ypnwri49vpR//rwa1r+z6b2Nm/9R38H/09bVE+XkaK/gy9c1bPTP2rP3uOztbfRKnYoa+GE72f7/92DS94u1ZsMeLf91lGkegeU7a8Lo99SgdvkMXydL6zJ0qPy9vTXsnXdM723cvVt9v/lGW6dPl5ODg4JDQjRs6lTtOXRI9nZ2eqVqVQ3s2lW2Nv+/TefO1ZodO7R84kTTPAKbNdOEfv3UIAsdn7bv26eJc+fqRliYGr30koa9846srZPqdx63X8bHx+uLn37Soo0b5Whvr3dbtrTkqjy1XX8fVad3RuvrEe9o4tTFunErXI3qVdKw/p1N2+Bx+1Zm8CS/Fau+W6XlE5ZLkgpXKKw+s/qYpr8ZfFNDaw9VpeaVtG/tPjXs1VDb5m9T1O0ovfv9u/It5msaj/PW55PR53DA0zBM2JeSavdP7DyhWl1qSUqq1Xf2cJZ/GX9FhEZoYueJqtq6qtp+1lbh18M1e+Bs2TnaqW73umbzObDhgAIrBer9Ge8rITFBV05ekSRdOHRB8z+fr46jO6pwhcIKuxqmi0cumqaLi4nTt12/VcGyBdVvQT9FR0br189+1aIvF6nNMO43zQoS4hMUHRUtB2cHSxclXSVvPl0gXz592KGDJKVag7ph1y5VKlVKM4YPV2JCgk5eTPrO586RQ1unT9epCxfU5dNPU0wXExurrp99prLFimnBmDGKjI7WZ1On6svp000n48OnTtXNsDDN/+orXb15U59MMP6V8O6TuisuNk4/9PpBeQrkUZMPky4WOrg8+M5N7ztd2W2z6+NfP1ZEaIR+7veznNyd1LhPY0sVO1WT5s7Vr2vXauhbb6l4oUI6Exysi8n6bgiPiFDv9u1VJH9+3bp9W4O+/Vajpk3TqF69LFjqzKFZo2r64ptfNOij9qaWDctW71C9WuXk5GgvSeo7+H+ytbHRr9OHKDQsQv0+nSp3N2f1eTdtWkoZTbOaNfXFTz9pULduD7bp5s2qV7mynByS9q++33wj2+zZ9etXXyn09m31Gz9e7i4u6tO+vSWLnuYWb9yoyQMG6HRwsPqMGaOa5curZvmkC0CP2y/nrl6t3//8U+M//li53N01+NtvLbkqz2zx8q2aPOZ9nT53RX0GTFbNl4JU86UykrLGvvUkvxW1utRSlZZVtGLiCl07dy3V+RSvXlzOHs5aNHqR+szuoy1zt2jr3K1qO7yt4c5b/yvncMDTyDTN+NNCiRoldOqvU0qIT5Akndh5Qi9Uf0HW1tb6c86fyu2fW00/bKrc/rlVuHxh1elaRzsW7kgxn+w22dVhVAf5FPWRbzFfVWhSQZJ089JNWWezVum6pZXTJ6cKvVhINTrWME3314q/FBMVo/Yj2ytvobzyK+mnRr0baeeinUpMTMyQbYDnc+afMxrVZNTjR8zikjefdvj/ptKeHh6y//8a9+RssmfXqPfeU1F/fxUrWFBNXn5ZkmRtbS1PDw+5u7ikuowVW7YoKjpaI3v2VCFfX5UMCFDvdu20aONGJSYmKjwiQut27VKf9u1VtEAB1ShXTq/XqZOu650ZOLk7yc3TTdltssvWwVZunm5y83STrX1SLcql45d0dt9ZtRzcUj5FfRRYOVD13q6nLXO3WLjk5u5FR+unpUv1cefOerVaNfl5ealm+fLq1KiRaZw+7durTsWKyu/lpTKBgWpTv74276VjTUmqX6ucYuPitHnbAUlSxN0obdz8j5o1rCZJOn7qovYdPK3BH3dQ0cL5Vbn8C3q7SyPNXbjRksXO1OpXqZK0Tf//OxYRFaWNu3erWc2akqTj585p3/HjGty9u4r6+6tyqVJ6u0ULzV292pLFThfvtmqlwvnzq0GVKiri56eDp06Zhj1uv1y4YYNa1q2r6mXL6oWCBdU7i14IebdrUxUulE8NapdXkYB8OnjkjKSss2897rdCkuwc7VK897CStUqqSKUics7prIByAQooF6BbV25JMt5563/lHA54Goaq2S9SqYji4+N14fAF+Zfy14mdJ9T0o6aSpMvHL+v8ofP6IOgD0/iJ8YlKSEhIMZ8CZQrIOlvK6yCBlQOVyzeXPm/wuYpWLapCLxbSi6++KHvnpFqYS8cvKfx6uPq+2PfBMhISFRsdq/Br4XLP457Ga4znEXk7UruW7FLNTjUtXZRMrUzRos90P/7xc+d0PTRUL7ZrZ3ovISFB0TExuhYaqpthYUpISFCAr69peBE/vzQpc1Z2/cJ1WVlbySvAy/RevqL5dDfsriJvR8rRNXM0gT9/5YpiYmNV7oUXHjnOjgMHNGX+fJ0ODtbdqCjFxcc/8v78/xoHezs1qF1Bv6/ertovl9X6TX/Lw91ZlcoVkyRduBgia2srBRTwMU1TtHB+hYVH6Padu3J14f7chznY2alBlSr6fdMm1a5QQet37pSHq6sqlUy6le/C1auytrY2O+YU9fdX2J07uh0RIVdnZ0sVPc35eT04frg5OSn8zh3T68ftlxeuXjW7aBeYRY/Lfvlym/52c3FS+O27kv57+5aNnY3pnyRlt8uu2HuxkrL2eSvncMCTMdRZl42tjQIrBerEzhNy9nBW2LUwvfDSgxPRkjVKqlm/Zo+dj4Nr6s1/HF0dNWjZIJ3665RO7jqpFZNWaNOsTeq/uL/pvv/8xfOry9ddUkzrkjP12k9YRlRElCZ3m6xqbapZuiiZnqvTs5/4FC9USF9/+GGK93O6uelmWNhzlAqZ3aVr1/T2iBFqWaeOPu7cWS5OTlq+ebN+XLzY0kXLNF5rWFVd3x+riIgoLVu9Q01frfpUndQ+PGpqF6//a16rVUtdP/tMEZGRWvbnn2pao8ZTblPzcbPqNn34Au39Otr/0n6ZvD8mSVmypjojZMXzVs7hgCdnqLAvSSVrltTe1Xvl7OGsQmULme5t8i7irb9X/q1cvrlMHbQ8i+y22VW0SlEVrVJUJWuX1JiWY3Tjwg3lKZhH3kW8tWvxLrnmcpW9k31arRLSwYqJK3Ru/zmd239OswfMNhuWwyeHhUqV8WyyZ1dcfPo8rqeIn58W//GHcrm7m+6XTS5f7tzKZm2tUxcvyid3Ug3MyQsX0qUsmVE2m2xKiEsZJDx9PZWYkKgrp67IJzCp5in4WLCc3J0yTa2+lFRzaGtjo7+PHDGrRbzv0KlTio2L08CuXU3B43poaKrzcnRw0L3o6Ecuy9HBQTGxsUpMTHzmJ7ZkRuWCApU7l7vmzF+vHXuOaFDfDqZhvvlyKyEhUafOXlJgQFJN9LGTF+Tu5myqeXRxdlJk1IPtdiXkVsauQCZU7oUXlNvDQ3NWrtSOAwc0qHt30zDfvHmVkJCgUxcvKtDfX5J07Nw5ubu4mGr1XZycFBkVZZrmyo0bGVr+9PYk+6Vf3rw6dfFBf0QnDHZcfpJ9KzN51G9FWsiq562cwwFPznBhv/jLxbXgiwVycHYwe+Tey+1f1p+z/9ScQXNUs3NNZcueTWf+OaObwTfNetP/N4f+PKTr566rcMXCsnO0067Fu+Tg4iAPbw9JUrlG5bRmyhr99MFPavheQ9m72OvCoQs69dcptf2sbbqsb2YXFxOnK6evmF7funRLF49elGsuV4s+Qq9O1zo6/Odh1X6ztopVLWY2zDp7xndlcSciUvfuxSgy8p7i4hN0/UaYJKV7j675vby0+9AhXb5+XTnd3JQ9W7YnbrJ/5+5d3YuJUdj/Nw+9dfu27GxtZW9rKxcnJzWqXl1TFizQB2PH6r02beTi6KhDp07pr6NH9dk778jV2Vn1KlfW+DlzlCdHDoXcuqUF69en5+pmKp75PXVy90ndunxLLjldlC17Nllns5ZPUR/5lfLT/BHz1XJQS0WERmjt1LWZrgbD3s5ObzZtqjEzZ8rezk4lAwJ07soVnb54UV2aNJGft7cSEhI0b80aVS9bVjsPHtSqbdtSnVfxQoW0cP16nTh/Xh6urvJwdVX2ZN/DFwoUUEJion5du1a1K1SQg729nFO5gJTVWFlZqVnDapr0/WIVK+Kngv4PLpoULZxfpYoX1IgxszXoo/YKDYvQ1BnL1ab5gyarxYv56/LVmzpw+LRKFCugn2avssRqPJH7z6HesHSs8nl7pttyrKys1KxWLU2aN0/FChZUQZ9kTbX9/VWqcGGN+OEHDereXaG3b2vqwoVqU7++aZzihQrp8o0bOnDihEoEBOinJUvSrayW8CT75et162r8nDmqVKqUcrq5acIvv1iotOnjSfatzORRvxWSFH49XJIUcy9GcbFxptdObk920SKrnrdyDgc8OcOFffc87srjn0f71+9X4w8e9FztnMNZvWb00tKxS/V1269lbW0t78LeeqndS088b0dXR+1fv18rvl2h+Lh4+QT66J0p75g6RrGxtdF7097T4q8Wa9KbkxQfH688/nlUsVnFNF/PrCL8WrhGNxtter34q6Smgq++96oa9mpoqWLJPY+73p/xvrbM26Kc+XJarBz3jRw7R4tXbDW9rvZKb0nS8T0/p+tyu772mk5euKBX33tPUdHRKR69929G/vijFv/xh+l1y48/liS9VrOmRvfuLVsbG00bNkxfTZ+uNz/9VPEJCfL39jZ1liVJQ7p3V/+JE9WyXz/5eXmpw6uvatK8eWm7kplUna51dPnkZX3+6ueKiYoxe5zSm9+8qXnD5mlMqzGysbdR2QZl9UqPVyxc4pR6tW2r7NmyaczPP+t6aKj8vLzUq23SCWJRf38N6tZNUxYs0FczZqhKmTJ6t2XLVINDl8aNdfTsWb3+8ceKjonRkm++UbGCBU3D83t5qf8bb2jiL7/o0//9T50aNdKgZI99zMqaNayqSd8vVuMGlVIM+2bEuxr25Uy1emO47O1s1aBOBfXo+uDidLkyRdSpTV117TVWHu4ueqtLoxTzyCwi70XLzs5Gri7p3zqlWY0amjR3rhpXr55i2Dd9+2rY1Klq1a+f7G1t1aBqVfVo1co0vNwLL6hTo0bq+tln8nB11VstMk/v7GnhSfbL1vXq6cylS+r91VemR+8dStbBnxE8bt/KTP7tt2JgtYFm495/3Xtmb+X0efy5TVY9b+UcDnhyVokZeBPTeqVeazek1hC93P5l1emaek/cdZT6+4+aX1bxqPXKKM+6/dL683iW+fUM7KmuE7qqbIOy6V6+J/HUn+Xtnc+2INeUgUCSdPTos80vqyhW7PHjWIglj0NpegzJ6t8hS39HnnGf3rv/pDq+/YU2Lf8m/WqBHnXcSGv/sg2q1n9fjRtUVv8PUqktTOPj2t5jx9Rx0CBt+vFHeXp4PNM8Hiujvm+Zeb/MqG3wrL+XaSEN9x3OWZ+Poc/hgHSUaR69t2zcMn0Q9IEiQiMsXRRkYnOHzjV7ogIAZEUxMbG6fPWmxk9ZqFrVgwzd3PPk6WBFRUfrrTfSt+VBTGysLl+/rvFz5qhW+fLpF/QBAMgiMkUz/j6z+ig+LqmTMEe3zNMBFTKfRr0bqXbXpGbmlrznHwCex/I1OzVoxDSVKFZAX37a/fETZGGFC+XT3k1T0305yzdv1qDJk1WiUCF9+f776b48AAAyu0wR9p/kviJASnoUTGZ+HAwAPInmjV9S88ZP3mcMHq957dpP3OcIAAD/BZmmGT8AAAAAAEgbGdpBHwAAAAAASH/U7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwWTP0KUdPZqhi8t0ihWzdAmeyXqtt3QRHqmO6mTIcp51GzyyfLd3Pkdp0plrpYxZDtsgc2+DJ5FR2+lRMvNvSgYd7zPz8flJZNQx/FHSc/s99bo96/HgUfthZt4/noSlz5medfs9otyZ6bvGceM5pee+9bTfeyOUxdL7usFRsw8AAAAAgMEQ9gEAAAAAMBjCPgAAAAAABkPYT0WPUaPUf8KE55pHuXbttGjDhjQqEf7rFi3boqDqb1m6GIBhTFuyRFU6d1Zgs2bPfbwHjCKwWTOt3r7d0sVAJtQzsKf2rt5r6WIAeEoZ20EfAIsLLN9ZE0a/pwa1y1u6KIBFhNy8qbEzZ+rzHj308osvyt7W1tJFAlLoP+wHLV6xNcX7x/f8bIHSIKOd2HVCEzqlvBDZ4YsOqty8sgVKhMyuYseO+qhTJ7WsW9fs/btRUSrbtq1+GDpU1cuWtUjZFm3YoMUbN2rWyJEWWf5/GWEfAPCfcjEkRAkJCapVvrxyuLlZujhAqgZ91F5932upn2av0h9b92vWlP6WLhIyUMGgghq1dZTCroTpq5ZfqeePPeVT1EcOLg6WLhoyqQLe3rp8/XqK9++/V8DHJ6OLhEwgUzfj33XwoAKbNdPyzZtV7913VbZtWw397jslJCSYxrkXHa0RP/ygKp0768V27fTW558rOCTEbD6rtm1To/ffV6lWrdSwVy+t3Gp+pXzj7t2q8/bbKt2qlT4eN06xcXFmw+Pj4/XtvHl6uWtXBbVpo/YDB+rY2bNm43z322+q2LGjKnTooJ+WLEnbDZHFTOwyUfOGzTN77+DGg/og6APdu3tPknQz+KYmd5usPqX7qF/Ffpo3bJ5iY2JN46+YtEIjGo0wmwdNyKSfZq9SxTo9VLFOD03+canZsFpN+mrarJWm1w83/Q8s31mB5TtLknr3/9b0Ovhyyh+GzKhLjy81bLR5jdbGzf8oqPpbuhuZ9L0Kvnxd3d4fq9LVuqtinR4aNvpnxST7Xk36frEatR5oNo/A8p21esOe9F+B5zT+fwvVvffXqQ4bMvInDfjsB0nSvXsxGjF2tqrU76UXa7yjt/p8k+Izvv/d+GvfCTVpN1glq3ZTg9f7K+petKSk7djjowkKevltVWvwvj77cqZpWFZ2/zel/cCk70DlVJrxT1+6VI3ff1+lW7VSxY4dNWDSJEVERprNZ9GGDQpq00Z/HTmiJn36qGTLlmrQs6eiojP/NooIjdBPH/6kgS8NVO8SvfVZ/c+0fX5Ss+3rF66rZ2BP3bl5J8V0Z/aeUe+SvRUXE6fzB85r0huT1K9iP/Up1Udj24zVmb1nTOPOGTRHk7tPNpv+0vFLeq/oe7px8Ub6rqCBuDg7yjOXuxwd7ZU9m7U8c7nLM5d7hi0/9PZtNenTR4MnT1ZiYqIkqVb37vpm1iy9PWKESrdqpeZ9++r8lSumaRISEjRuzhxVe+MNlWzZUu0GDNCxc+ckSfPXrdOr772X6rKmzJ+vjoMHp/s6ZSXZbbPLzdNNzjmcJUlO7k5y83STrb3lWyJFhEZoVJNRmjN4jum7MaTWEC39Zqn+9/b/1Kd0H33Z/EtdO3/NNE1CQoKWjVumAdUGqHfJ3vqm3Te6dOySJGn7/O36/NXPU13W6imrNb7j+HRfJyMo4ONjCvZ9v/lGpVq1Ulx8vC5fuyY7W1v5eHpKko6dPavOQ4aodKtWqtm9uyb88ovi4uMtWXSko0wd9u9bvHGjJg8YoFG9eum3dev0599/m4YNmzJFB06e1OQBA7RgzBjldHPTu6NGKf7/v7Q7Dx7UwEmT1O2117Ri4kS927Kl+k+cqP0nTkiSboWH64OxY/VKtWpaPG6cPD08tG3fPrPlf/fbb1q2ebNGv/++lowbpxeLFVPXzz5TRFSUJOmPPXv03W+/aUj37pozapS27dunu/fuZczGyYQqNquovav2Kj72wYFjz7I9CqoXJHsne0nS9L7TFRsdq49//Vhdx3fVgQ0HtPq71ZYqcpYQdS9G23Yd0uypAzW0XydNmb5Mm7bue+Lpt66aoK2rkkLNiEFvmF575cmZTiVOW80aVdOq9bvNLsYtW71D9WqVk5Nj0veq7+D/KTo6Vr9OH6LxX7ynDZv36rtpv1uqyGkqqFSADh09m+qwg0fOqkzJAEnSsNE/68DhM5o8prcW/DxMOT1c9G7f8YqPTzCbJi4+QWMmztNH77XS8nkj1bltPSUmSjGxceraa6zcXJ20YMan+t83H+jgkTP6cvy81BadpQQVLaqt06dr0iefSJJWTJqkrdOna1C3bqZxwiMi1Lt9ey2bMEFTBw/WgRMnNGratBTziouP15iff9ZHnTpp+cSJ6ty4semkNzOLjoyWex53dZvYTUNWDVHd7nX1y9BfdHLPSXnm95RzDmedP3Q+xXTnD56Xb3FfZbfNrts3b6tEjRLqNaOXBi4bKN8XfPXdW9/pXkTS717F1yrq2PZjZhcN9izbo0LlCimXb64MW9e0khCfoKiIKEsXI0OFR0TojU8/VfFChfR5jx6ysrIyDZu/fr1a1q2rBWPHKi4+Xl/PnGka9tu6dZq1fLk+ffttLf7mG+XOkUM9v/hCsXFxCipaVGcvX9bdqJTb8uCpUwoKDMyQdcPziQyP1KQ3Jsm3uK/afd7O7Luxff52VWlZRf0W9FN8XLyWfv2gUmLbb9u0adYmtf60tfov7i+33G6a2nOq4mPjVSCogELOhpgqhJK7cPCCCgQVyIhVS1Px8fEpLhSntwI+Prp0LekCy5EzZ2RnY6NTFy/q0vXr8subV9bW1gq9fVudhw5V6SJFtHT8eH3Vp4+Wb96s6UuXPmbuyKqyRNh/t1UrFc6fXw2qVFERPz8dPHVKkhQcEqIlmzZpdO/eCipaVAV8fDT07bd16uJF0ziTf/1VHRo2VLOaNeWbN68aVa+uOhUrauH/d563fMsWuTg56YP27VXQx0d9O3Y0a9YZHROjHxcv1uDu3VW5dGn5eXnpw44dZWVlpT//+kuStHDDBtWpWFGNqldX4fz5NbBrV7PWB/81QfWDFB8br8ObD0uS7kXc04GNB1SxWUVJSTU8Z/edVcvBLeVT1EeBlQNV7+162jJ3iyWLneklJiaqf5+2KlwonxrWq6R6NV/UgqWbn3j65LVCLi5OptfZsmWJw4Dq1yqn2Lg4bd52QJIUcTdKGzf/o2YNq0mSjp+6qH0HT2vwxx1UtHB+VS7/gt7u0khzF260ZLHTTOkShRQaFqFLV24oMipaHw76TiHXbik6OkYnT19SmVIBCr58XUtWbtPoT7srqFSACvjl1dBPOunUmUs6eOSM2fxiYmL1QY+Wql6llPx886hti1pydLDTijU7FXUvWiMHv6lCBbxV8oUC6v1OCy1aviVLhNl/Y2tjI08PD7k5J9WU5XBzk6eHh1ycnEzj9GnfXnUqVlR+Ly+VCQxUm/r1tXlvyhZFMbGx+qBDB1UvW1Z+Xl5q26CBHO3tM2xdnlVOn5xq/klzFQwqqFy+uVTl9SrKVyyfjmw5IkkqUKaAzh9MCvvrp63XnmVJrV7OHzyvAmWSTrhL1iypmp1ryreYr3L75VbTD5sq6k6Uzu5LuhgVUC5AObxz6K8VSb+RiYmJ+mvFX6bfgKzmzD9nNKrJKEsXI8PcuXtXb3z6qYr6+2tkz55mYU6SapUvrzoVK6pw/vxqXquW6XxLkn5bs0at6tZV3UqVFODrq2HvvKOQmze19Z9/VChfPjk7OOjw6dOSpAGTJunomaTj0sFTp1SGsJ/p3btzT5PemCSfoj5qP7J9iu9GqVqlVLpOaXkX9lal5pVMxxIpKexXaVVFZeqWkVeAl9oMa6PwkHAd2XpEeQvllb2zvS4evihJmjVgli4eTfr7/MHzKlimYMatZBr55/hxNendO0OXWcDHR5evXVPkvXu6ERqqupUq6cjp07p07Zr8vb0lSXNWrpS/t7c+7NhR/t7eKl+8uLq+9popF6WX5rVrc7++hWSJe/b9vLxMf7s5OSn8TlJtwYnz55WYmKgWffuajZ+QkKCLV6+qTGCgTpw/r33Hj2v2ihWm4bFxcapQvLgk6cLVqyrg4yNr66TAky1bNgX4+prGPXf5su7FxKjX6NFmB7V7MTG6ePWqaR71KlUyDSuYL59ssmeJTZsubB1sFdQgSLt/361StUtp//r9cvZwVpFKRSQlNRW1sraSV8CDzzVf0Xy6G3ZXkbcj5ejqaKmiZ2rZslmrUAFv0+uAgj5atX63BUuUsRzs7dSgdgX9vnq7ar9cVus3/S0Pd2dVKldMknThYoisra0UUODBPWlFC+dXWHiEbt+5K1cXp0fNOktwd3OWf/68OnT0rOztbLXhz39UpWIJBRTwlp29jQoX9NGmrfuTjomdPjWbNiEhURcvXTfV/kuSlZWVypYunGI5x09e1PUbYXqxxjtm00dHx+rajTDl8fRIv5XMBHYcOKAp8+frdHCw7kZFKS4+PtXjuZWVlcoWLWqBEj6fhPgErf1+rf5e+bdCr4YqPi5esfdiVbBs0sl0waCCOr03KYxt/mWzPLw8VL5xeV04dEGN+jSSJN25eUfLxi/TiV0ndOfGHSUkJl3cjo58cBtDpWaVtOf3ParZqaZO/XVKEbciVLaBZTqGehqRtyO1a8ku1exU09JFsZgvfvpJ96Kj9Wq1aqZzo+SSn5O5Ojkp7M6DFhznr15Vh4YNTa/dXVyUN2dOnb9yRVZWVipVpIgOnTqlnG5uWrlli/LmzKlcHh4KuXmTsJ8FLPxioWLuxajsq2VT/W54+nma/nZwdVBk2IOa7evnr+vlDi+bXju5O8k9r7uun78uKysr+Zfy1/lD5+WS00V/r/xbHnk95JrLVWEhYfIv45+u6/W8bkdEaMmmTerUqJFFy+Hv7a2QW7d0+PRpFStYUKWLFNGRM2d0MzzcdL/+8XPndOjUKQW1aWOaLj4h4T9dSWl0WSKRZsuWzex18rola2trLRg7VtkfGienu7vp715t2qh+lSpmw5+29+UpgwfLK5d588P7tUNIqeJrFTW562RFRURpz7I9qtC0QoorwP/qoVE5CKXOKvmGenibZfFa2NS81rCqur4/VhERUVq2eoeavlr1qb5XD4+a1b5XQSUL6eDhs4qPj1eX9vW1Y/dhRUVFq3TxQqYTL2trKy2YOSzlMTGHq9lrB3tb2dqk/hNQvKi/vh7xbor3c3q4pjK2cVy6dk1vjxihlnXq6OPOneXi5KTlmzfrx8WLU4zrYGcnWxsbC5Ty+ayftl7rf1qv1kNbK1+xfMpmk03Tek9TYkLS8aJAmQL6Y+YfunzisvIVy6cbF28oLCRM185dU8GgpAsCMz+ZqfDr4Wo9tLVy+ORQQnyCRjQcYbY/VWhWQSu+XaGQsyHas2yPStcpLXvnzN3yISoiSpO7TVa1NtUsXRSLql2hgmqWL69PJkzQS0FBCvT3Nxv+8DnZ0wgKDNTBU6dka2OjLk2aaOfBgyoZECA/Ly86y8wCStYuqZI1S2rmJzP1wksvyCfQvMM364daCibqyc9DCgQV0IWDF5TdNrtqdaml4zuPy6+knzz9POWSwyVNyp8eIiIj1W34cLWpX9/SRZGfl5cSEhO1cfdulQwIUMnChbVk0yYlJCSY9cJfo1w59evSxXIFRYbKEmH/UQr7+SkxMVHhERGPrGEpkj+/Ll69anYlOjm/vHm1ets2JSQkyNraWgkJCTodHKy8OZPuY/b39padra2u37qlSiVLPnIepy5eNL0+c+lSik7+/msCygXILbebNs/ZrOM7jqvloJamYZ6+nkpMSNSVU1dMPxTBx4Ll5O5kqtV3dHE0qyUKvRKasSuQCcXHJ+jMuSsKKJi0zU6duSQ/39ym4a7OjoqMerDNrobcTHU+Ntmzmfq0yGrKBQUqdy53zZm/Xjv2HNGgvh1Mw3zz5VZCQqJOnb2kwICk1jnHTl6Qu5uzqVbfxdnJbBtdCbmVsSvwnMqUDNCq9bsVcTdK0yf3U5s3P1e2bNamGvvChfIpMVEKD7+baq39kygSkE+LV2xRrpxupr4Q/isOnTql2Lg4Deza1RRoroca69hzeu9plapdSuUbJz16MzY61uz46lfSTxGhEdq5eKeKVSuma2evaeOMjXLP6y73PO5J8/j7tFoOaali1ZJa1Zw7cC7FcnL65FTh8oW1Y+EO/bP6H73x9Rvpvm7Pa8XEFTq3/5zO7T+n2QNmmw3L4ZPDQqXKeLUrVlSDKlW0YdcufTx+vBaMGfPEF7by582rE+cfNN0Ou3NHV2/eNJ2DlQkM1NJNmxQTG6u+nTpp2/792nnwILX6WUSp2qVUtkFZHdhwQD9//LP6Lein7LZPFiU883vq8onLptd3w+4q7GqYqTVAwTIFtXvpbsXFxKlp36Y6tu2Yju88brp9KLOaOHeu9p84of0nTmjApElmw+53iJdRbG1s5OPpqXU7d+qjzp1VxM9P5y5flrWVlalmv4ifn1Zu2ybfPHlSbZ0B48nSn7Jvnjxq8vLLGjBxojbv3auLV69q89696vvNNwqPiJAk9WjdWov/+EPTlizR2UuXkjrz+/VXLd20SZLUsHp1RURGatycOTp76ZK+mT1bN8PCTMuws7VV12bN9OWMGVq1bZsuXr2qXQcP6tMpU0w/aK/Xrav1u3Zp+ebNOnXxokZNm/af34GsrKxUsVlFrZi0QvmK5VOegnlMw3yK+sivlJ/mj5ivS8cu6fiO41o7da1ZbYpvcV+FXg7VuQPnlJCQoA0/pe+9RM9jZv+Z6hnYUzeDUw/XacXKykqjx8/VqTOXtHLtLq3942+1aFLdNLx4MX/9sXWf7t2L0bUbYVq6cnuq88nvm0cbN+9T+O27io6OyVL3YVtZWalZw2qa9P1iFSvip4L+Dy7iFS2cX6WKF9SIMbN17OQF7dhzRFNnLFeb5g+a4xYv5q/LV2/qwOHTSkhI0E+zV1liNZ5ZmVIB2n/otBwc7OTi7KjAwr5a/+delSlZSJLk6+OpJq9U1oDhP2rz9gO6GHxNm7cfUN/BUxR+++4TLaNR/Upyc3XWBwO/04HDZ3T2/FUtW71Dn46ekY5rljn4eXsrISFB89as0cWrVzV/3Tqt2rbN0sVKU7n9c+vk7pM6d+CcLp+8rFkDZiku5sHFaVsHW/kE+mjbr9tUrGoxFatWTNt+3WZ2wp27QG7tXblXIWdDdPrv01o4amGqLWwqNa+kjTM2KrttdhWtkvlveajTtY5y++dW2+FtNXzDcLN/H/7yYYaX505EpK7fCFNk5D3FxSfo+o0wXb8RlmHLH/LWW7oVHq4Jv/zyxNO0rFtXv61bp3U7d+r0xYsaNmWKcnt4qFpQkCSpdJEiCr52TeevXFFBHx9VLlVKC9avz3Jhv/+ECQps1izF05/SUlxMnMKvhyviVtL57N2wuwq/Hq6YezHptswn1WpIK0XcitDyCcufeJoqLato+2/btW/dPl09fVXzhs2Ta25XvVDtBUmSf2l/3Qy+qWvnrylPwTwKrByoHQt2ZPqw37VZM/l7e2v4u+9qw9SpZv9++eKLDC9PAR8fXQwJUcmAAGXPlk1+Xl66ERZmCvvtGzbUrfBwDfr2Wx07e1anLl7U/HXrNG727MfMGVlVlq7Zl6TP3n1X42bP1sBJkxR25468PT1VLSjI1Ey/cqlSGvvhh5oyf77GzZ4tFycnlS5cWC/9f3OWHK6uGv/xxxrxww/6edky1atc2fSjdN97rVsre7ZsGvPzz7p265Y8PTxUqWRJ5fz/Jmcvv/ii3mvdWp//8IMSExP1zuuva//x4xm7ITKh+2H/fg1Scm9+86bmDZunMa3GyMbeRmUblNUrPV4xDQ8oF6AanWro267fytnDWfXeqpeRRX8qMZExsrGzkYNr+j771sHeVlUqFFe77iNlZWWlnt2a6uWqpU3De3Zrpg8HfqeXXu2twoXy6dV6FTVz7toU8xn4YTuN/HqOqtTrpbj4eG1YOlb5vDP26vPzaNawqiZ9v1iNG1RKMeybEe9q2Jcz1eqN4bK3s1WDOhXUo2sT0/ByZYqoU5u66tprrDzcXfRWF8veX/e0Chf0kZW1lapUSOpzpFqlklq5brfZvfifDeiicd8t0MDPpyksPELeeXOqWqUSsrd7spo5W1sbTZv0sb6aME9vvjdG8fHx8s+f19QRopEV9ffXoG7dNGXBAn01Y4aqlCmjd1u2fKqwk9m98u4ruhl8UxM7T5Sdk51qdallChP3FShTQPci7imXby65eroqPi7e7IS7w6gO+mXIL/qi6RfK4ZNDrw98Xf97+38pllWmXhnNGzZPZRuUTdG8NzNyz+Ou92e8ry3ztihnPss/pWTk2DlavOLBo4KrvZLU2dfxPT8/apI05e7iohE9e+rdUaNUs1w5lfv/vo7+Tet69XT1xg19+r//6fbduyoREKDJAwaY+r1wcXJSoXz5TOG+Wpky+n7hwizXE39kdLTsbG3l6pR+fcGc+eeMJnR68FjQyd2SHmfZ4YsOqty8crot90k4uTup3Yh2mvLuFJWoWUIB5QIeO0211tUUejVU8z6dp6jbUcpfIr/emvyWstkktaJycHFQ3kJ5TceaYtWKae33azN9T/x5cubUjM8+07w1a5QvT57HT5DOCvj46NDp0/LJndTys1Thwjp3+fKDjmldXTXjs880duZMtR0wQNbW1iqcP7/avfLKv80WWZhVYkZW6x09mmGLypSKFbN0CZ7Jeq1/punO7D2jcR3HacSmEXLzTJ978eqoTrrM92H/tg36V+2v8o3Lq0X/FimGPbJ8t3emVdHSnmvKEJ0unnEb7N1/Uh3f/kKbln+Tfs+czuTbINPIqO30KJn5NyWDjvfPenzOCKFXQjWk1hD1m99P+UvkT3WcjDqGP0p6br+nXrdnPR48aj/MzPvHk7D0OdO/bL+qXbqocfXq6v/mmykHPqLcmem7lpmPG0/C0seNdN23nvZ7b4SyWHpfN7gsX7OPzCc2JlZ3biT11lyqVql0C/qZweWTlxUbFav6b1m+Yxaji4mJ1Y1btzV+ykLVqh6UfkEfwHOJj41XRGiEloxdonzF8j0y6ANZ0ckLFxQVHa23Xn/d0kUBgMfK/O3qkOX8tfwvDa09VNFR0Xp9oLF/DL0Le+vrvV/LOQdPZkhvy9fsVO2mfRUVFa2BH7azdHEAPMLpvac18KWBunjkojqO6mjp4gBpqnD+/No7d65yuBr76SQAjIGafaS5ys0rW/x+MhhP88YvqXnjlyxdDACPUaRiEU0+PtnSxQAA4D+Pmn0AAAAAAAwmYzvoAwAAAAAA6Y6afQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwmOwZurTbO9Nv3q6Vnm789CzL83radXlWR49mzHIspVgxS5fgkdZrvcWWXUd10m5mmXk/yiwyan/OIOn53X3q72Z6HsOe8vhhyX36cdJ0n/8XbINn3waPLJ8lj7Fpeex61vV4VBky0fkk3/vMvQ3SQkZtRyA9ULMPAAAAAIDBEPYBAAAAADAYwj4AAAAAAAZD2E8jwZevK7B8Z9O/g0fOphin49tfmIYP/2qmBUqJrGrHoh36IOgDSxcj3T3JfvQ0mrYboknfL37q6RYt26Kg6m8917KB5zWk1hCtn2bse2HTWuTtSPUM7KkTu05YuijAM7kZfFM9A3ua/p0/eD7FOOM7jjcN/3X4rxYoJYCsImM76DMwrzw5tXXVBF0JuaWWXT5LdZxJX/VSbGycevWblMGlA7KGJ9mPnsaM7z6RrW36HeYmfb9Yazbs0fJfR6XbMvDk+k+YoMV//JHi/eNLlmR8YZ7Q+I7j5VXYS62HtrZ0UQCLWLRsixYv36pZUwdYuiiZgoeXh0ZtHaWwK2H6quVXqY7TfVJ3xcXG6YdeP2Rw6QBkNYT9NJItm7U8c7krOib2keO4uzlLkmxs2OxAap5kP3oaHu7OaTIfZA2DunVT306d9NOSJfrjr780a8QISxcJAJ6KdTZruXm6KS467pHjOLk7SZKycz4J4DEsfpS4XzPW+53mGjPpN10JuaXiRf00b9oQHTtxQV+Mm6t9B08ph4eLmjWspp7dmip79mwZXs7QsAh9Pmam9vxzXKFhEfLxyqVunV5Vy6YvZ3hZLGnRhg0aN2eOIiIj1f7VV7Vl717VqVhRvdq2lSQFh4Ro2NSp2nPokOzt7PRK1aoa2LWrbG1sJEmT5s7Vmh079FqtWvph0SJls7ZW73bt1KpePdP0td9+W5/36KHZK1fq4tWreikoSF/26SMHOztJ0pI//tDM5ct19tIlWVtbq2rp0hrUrZvy5MxpmY2Sgdb/tF5rp66VJNXsVFOv9HzFNCzmXoyWjF2ivSv3KjY6VoVeLKTWQ1srZ77Ms13Saj9atGyLPh8zSz9M/EjDv5qps+evyscrlxbP/kwO9nbq0uNL7dhzRJL0Xvdm6vXWa2bT3wq9rU+G/aCdfx2Vf/48erVuRY3/30Id3/Oz2Xi/r9qur7+dr3vR0erQqq5pPpO+X6xvf1hiGi+wfGdJ0msNq2n0sO5Pu1mQRlycnOTi5CRHe3tlz5ZNnh4epmG7Dh5UpyFD9PWHH2ri3Lm6ERamRi+9pGHvvCNr64y/o218x/E6ufukJOnk7pPaPGezJKnDFx1UuXll03h3w+/qf2//T8d3HpdXIS+9Me4N5fbLbRq+d9VerZy8Ujcu3FBO35x6teerevHVFzN2ZZ5D8LFgLfxioc7uOyvnHM6q1KySXun5irL9/+/8kFpDVK5ROV0+fjnVbZAQn6AFXyzQrkW7ZOdop/rv1rfk6ljU+P8t1OFj5/TDhL4phg0Z+ZPi4uL1xafdde9ejMZ++5tWrtul6OhYvVimiIb266h83p4WKHXaySrnkxGhEfrt8990as8p3Q29qxw+OVS3W11VaVklw8tiSTsW7dCycct0L+KeqrevriNbjqh0ndJq2KuhpKTbGeYNm6eTe07K1t5WZV8pqxYDW8jGNul8csWkFfpnzT+q9FolrfthnayyWalx78aq2qqqafqhtYeq3eft9OfsP3X94nW98NIL6vxlZ9k62EqSdi3ZpU0zNynkbIisrK1UtGpRtRzUUu553C2yTYD0YPGwL0k3bt3WT3NWa9SQrsqZw03bdh1UaFiEOvcYrdav1dRnAzrr+o0wDfx8mhwd7dS9U8MML2Nk1D3lyZ1DE0f3Uq6cbtr191ENGfmT/H3zqHzZohleHks4ffGiBk2erI86dVKNcuX04+LFOnXxoupUrGgap+8338g2e3b9+tVXCr19W/3Gj5e7i4v6tG9vGufi1au6fO2a5o0erQXr1+vzH35QnUqVlMPV1TTOvNWrNfK99xQRGakeo0Zp4fr16tAw6XO/FR6urs2a6YWCBXUvOlojfvxR/caP18+ff55xG8MCYqNidWzbMfWZ3UeXT1zWrP6z5FvcVyVqlJAkzRs2TyFnQvTW5Lfk5O6ktd+v1ZR3p2jAkgGyzpY5uudIy/0oLj5BYybO00fvtZKfbx5t331YiYlJwyaMfk8xMbF6o2fqTSBHjJ2tqyG3NPfHQQoLj1C/T79PMU50TKz+3LZf0yf307ZdhzRi7GzVq1VOgQG+erPDK2rTvKZ+mr1Kf2zdr1lT+kuS7O1tn26DGFRCfIKio6Ll4Oxg6aKksHjjRk0eMECng4PVZ8wY1SxfXjXLl8/wciRvhpunQB41+bCJJMnBxXybbZ+/Xe0+b6emHzXVjL4ztPTrpeo+MemC0omdJzRr4Cy1+bSNCr1YSOf2n9Os/rOUwyeHCpQukOHr9LQiQiM0sfNEVW1dVW0/a6vw6+GaPXC27BztVLd7XdN4/7YNNs/drD2/79Gb49+Uay5XzRk8x1KrY3FBpQL06+KUt7FI0sEjZ9W2RS1J0rDRP+vM+SuaPKa33N2c9f2MZXq373gtmf25smWS34pnlRXOJ6Mjo+Wex13dJnaTay5Xndh1Qr8M+UWe/p4qXL5whpfHEq6evqo5g+ao2UfNVKJGCa37cZ2unLqi0nVKm8aZ3ne6sttm18e/fqyI0Aj93O9nObk7qXGfxqZxbly8oVuXb6nvvL7avmC7fvv8N5WuU1rOOR606tsyb4vaj2yvexH3NKXHFG1fuF01OtSQJN25dUe1u9aW7wu+irkXo/kj5uvnfj+r98+9M2xbAOktUxzVw8Ij9OWw7ioXFKgCfnnVoVVdzZm/Tv758+rDni3lnz+vypctqq4dX9XC37dYpIw+Xrn0Se82CioVIF8fT73epLqKFcmvLTsOWqQ8lrBg/XoV8/dX12bNVChfPg3q2tWsRuz4uXPad/y4BnfvrqL+/qpcqpTebtFCc1evNpuPtbW1PnnjDfl7e6t78+aKiY3VifPmHdB0btJEJQMCVLlUKVUqVUoHT50yDXuzWTM1fOklFfDxUbGCBdW1WTPtOnRIMbFp0/Q7s0pMTFTz/s3lXdhb5RqWU5l6ZbR9wXZJSVewdy/ZrU6jO6lgUEHlKZBHrYe21pVTV1Lt3MdS0nI/iomJ1Qc9Wqp6lVLy882jti1qydEhqfWHm6uTPHO5K1u2lLU2t+/c1eoNe/RBj9dVolgBVatUUi0av5RivPj4BH3cq7UK+nupY+u6cnF21KH/7zDQydFenrnc5ehor+z/f+uBZy53uTg7PvV6GNGZf85oVJPM2Y/Bu61aqXD+/GpQpYqK+PmZHVsykpO7k9w83ZTdJrtsHWzl5ukmN0832T50wahUrVIqXae0vAt7q1LzSmb788rJK1WjQw1VbFZRuXxzqVyjcipVp5R2LtyZ0avzTP6c86dy++dW0w+bKrd/bhUuX1h1utbRjoU7zMb7t22wc+FOVW1ZVcWrF5fvC75q3Lvxw4v5zyhdopBCwyJ06coNRUZF68NB3ynk2i1FR8fo5OlLKlMqQMGXr2vJym0a/Wl3BZUKUAG/vBr6SSedOnNJB4+csUi5mzd+Kc3u188K55M5fXKq+SfNVTCooHL55lKV16soX7F8OrLliEXKYwnbF2xXvmL5VKdrHeUtlFevD3rd7Hzy0vFLOrvvrFoObimfoj4KrByoem/X05a55p+ZlbWVXvvkNeX2z6163espLiZOl09cNhunVuda8ivpp8DKgQqsFKgLBy+YhtV5s47KNSynPAXyyLeYr+p2rauTu04qNo1uJQQyg0xRs5/b01358+Uxe+/4yWAdOnLOrEfs+IQEJcQnZHTxkpYdn6Dvf16ulWt36eq1W4qLi9e96BiVLV3EIuWxhHNXrqiIn5/ptbOjo/Imazp/4epVWVtbK8DX1/ReUX9/hd25o9sREXJ1TrrSmidnTlOzfrf/fy/8zh2zZfl5eZn+dnNyUliy4UfOnNHEX37RsXPnFB4RofiEBCUmJiry3j3TfI3IOpu18hbKa3rtFeClvav2SpIun7isxMREjW4x2myaxIRE3bh4QwXKZI5avrTcj6ysrFS29NPXggRfvqH4+AQVCchnei+goE+K8WxtbZQ3Tw7Ta1cXR4XfvvvUyzO6yNuR2rVkl2p2qmnpojyRh48tDx97MhtPvwdNqx1cHRQZFml6ffnEZZ3dd1abZm8yvRcfG6/CFbJG7eDl45d1/tB5syeNJMYnKiHB/Hf+37bB9QvXVaNTDdNr70Dv9CtwJufu5iz//Hl16OhZ2dvZasOf/6hKxRIKKOAtO3sbFS7oo01b9ysxMVEtOn1qNm1CQqIuXrquMiUDLFT6tJEVzicT4hO09vu1+nvl3wq9Gqr4uHjF3otVwbIFLVIeS7h27pq8izzYVx2cHeSe1930+vqF67KytpJXwIPjdb6i+XQ37K4ib0fK0TXpwrpHHg9Ts35Ht6T37oab/04nP344ujnqbtiD4RePXNTyict16dglRYZHKiE+6XwyJjLGNF8gq8sUYd/1EbVhNV4qrX7vt8ng0qRu2uxV+mn2Kg3t10nFiuSXjU129e7/bYqTEjxe9lRqWxMfev1wjez94ZH37unNYcNUqWRJjf/4Y3m4uuqvI0c0cNIkJSQ+PJf/AKtkf1pb6ZMFn8g6u3mDHdecrsos0nI/crC3lW06dk6UPZXmrIn/xe/Yv4iKiNLkbpNVrU01SxfliT3q2JJZPXwLTuJDJW7Yq6HK1C9j9t7DrQMys5I1SqpZv2b/Os7jtgEeCCpZSAcPn1V8fLy6tK+vHbsPKyoqWqWLFzLVnFpbW2nBzGEpfotz5sg8vxXPKiucT66ftl7rf1qv1kNbK1+xfMpmk03Tek9TYgLf66f18PmOlPJ3OsVtjP8/ODoyWt+++a2KVCqiruO7ysnDSaf/Oq3ZA2fzWcBQMkXYT02RgHxauW6XfH08LdJ50sP27juh2tXLqnGDpI6ToqNjdCXkpiTzGhRHR3vT8EdxdLTTveis10TI38tLuw4+aG595+5dXb150/TaN29eJSQk6NTFiwr095ckHTt3Tu4uLqZa/ed1JjhYobdv66NOnZQvT9LV+7U7djxmKmNIiE9QyJkQ05XuK6eumK5YexX2khKlyPDITF07kJb70bPK551L2bJZ68SpYFOHVCdPX3qmednYZFechWqHMoMVE1fo3P5zOrf/nGYPmG02LIdPjkdMheSy2WRTQtyzfYe8i3jrxsUbZh32ZSXeRbz198q/lcs31zP/znv6eerqqaum1w834f2vKVMyQKvW71bE3ShNn9xPbd5Mug//fo194UL5lJgohYfffaaWUVlRZjufPL33tErVLqXyjZP6ComNjlXoldAU49k52pmGP4qdo51i72W988nc/rl1YtcJ0+uoO1EKuxpmeu3p66nEhERdOXVFPoFJLe+CjwXLyd3JVKv/vELOhCgiNELNPmpm6sh4/9r9aTJvIDOx/FHvEdq3qqNbobc16PNpOnbigk6duaT5SzZp3HcLLFIe//x5tXvvMR04fFonTwdrwPAfFRMbn2K8HO4u8vHKpUXLt+pqyC2FhkWkGKd4UX9t23lIJ04F6/qNMMXFpZxPZvR6nTo6eu6cfly8WGcuXdKon36SldWDquWi/v4qVbiwRvzwg46dO6cdBw5o6sKFalM/7XpH9vb0lK2NjeavW6eLISFavX27flm1Ks3mn5lZWVlp0ehFunLqiv5e+bf2rd2nKi2Seu/N5ZtL5ZuU16wBs3R482HduHhDhzcf1vS+0xUZHvmYOWectNyPHiUmNk7Xb4Tp+o0wxcfHKzLynum1JLm6OKlB7fIa990CHTxyVtt2HdLSVdueaX3y58ut4MvXtf/QaUVHxyg27tGPSjKiOl3rKLd/brUd3lbDNww3+/fhLx9meHnu3L2r66Ghirx3T3Hx8boeGqrroSlPojMTz/yeOvXXKd26fEux0bFP1bT4lR6vaOfinVo/bb1Czobo/IHzWjV5lXYv3Z2OJU47L7d/WRG3IjRn0BwFHwvWlVNXtG3+Nv0+7vcnnkeV16to2/xtOrLlSFKT3AnL07HEz2dm/5nqGdhTN4NvPn7kZ1SmVID2HzotBwc7uTg7KrCwr9b/uVdlShaSJPn6eKrJK5U1YPiP2rz9gC4GX9Pm7QfUd/AUw96mlNnOJ3P759bJ3Sd17sA5XT55WbMGzFJcTMrfDucczsrhk0M7F+1U6NVQRYSm/B30Le6ro9uO6vKJywq/Hq74LHI+WeX1Kgo+Gqx1P65TyJkQLRi1wOx80qeoj/xK+Wn+iPm6dOySju84rrVT16ZpKzIPbw9lt82ubfO36cbFG9q7eq/+/OXPNJs/kFlk2pr9HO4umjH5E4399je17TZC1tbWKlzIR+1er22R8rzbtYmCL19X5x5fycnBTl3aN9Ct0NTv9fzi024aOmqGajT+UIEBvlr6i3kv8V3a1dfRExf0epdhio6O1ZLZw1Us0C/VeWUmhXx9NaJnT42bPVvf/fabOjZqJD8vL7P75L/p21fDpk5Vq379ZG9rqwZVq6pHq1ZpVoYcbm76sndvfTNrlqb//rtKFy6s99u2Vf+JE9NsGZmVjYONAqsE6pt238jKykqv9HxFxV8ubhre9rO2+n3c75ozcI7uht2Vh7eHilUrJhv7zHPfWVruR4/yz4GT6vTOg74LTp65pJ/mJHUSef/ReoM/6qB+n36vdt1HqoBfXrV7vbYm/7j0qdenbs0X1WBzeXXv/bXCb9/9zz16zz2Pu96f8b62zNuSKR7xOPLHH7X4jwe9kVd74w1J0vElSyxUoser07WOLp+8rM9f/VwxUTEpHr33bwIrB6rL2C5aM2WNlo1bJnsXe/mX9tcLL72QzqVOG845nNVrRi8tHbtUX7f9WtbW1vIu7K2X2qXsMPNRqrWuppAzIZrWe5psHW31yruv6MKhC4+f0AJiImNkY2cjB9f0e0pF4YI+srK2UpUKSb8N1SqV1Mp1u83uxf9sQBeN+26BBn4+TWHhEfLOm1PVKpWQvV3m+a1IS5ntfPKVd1/RzeCbmth5ouyc7FSrSy1F3Er9gnbHLzpq7tC5GlJjiLwDvTVw6UCz4bW61FLw0WB99fpXio2OVf8l/eVbzDfVeWUmeQvlVfsR7bVs3DKt/m61anSsIU8/T2W3fRBL3vzmTc0bNk9jWo2Rjb2NyjYoq1d6vPIvc306Ljlc1OnLTvr9m9+1cfpG+Zf2V6P3G2lW/1lptgwgM7BKzMibUG+nYw/BrpWebvz0LMvzetp1eVZHjz7X5PHx8arcubOGdO+uxi8/3XPSM0SxYpYuwSOt13qLLbuO6qTdzDLzfvQUZvyyWnMXbtSahak/qu+5ZNT+nEHS87v71N/N5zyG/aunPH5Ycp9+nDTd5/8F2+Dft0H/qv1VvnF5tejfIsWwR5bPksfYtDx2Pet6PKoMmeh8ku/982+DhPgEfVL5E7Ua0sp0e0NmklHbEUgPmbZmH5nTlPnzVbFkSeVwc9O8NWskSS+/+KKFSwU8nZ1/HVXItVsqXaKQrl0P089z16pFkyevTQSAp3H55GXFRsWq/ltpd1sbkJWtnrJaRSoWkXMOZ22dt1WSzForAkgbhH08lZMXLmj6778rOiZGgf7++n7IkDTrfA/IKIkJCZo6Y7mCL1+Xh5uLXq1bQW91bmTpYgEwKO/C3vp679eWLgaQaVw5eUUbp29UbHSsfAJ91OP7HmnW+R6ABwj7eCpf9+1r6SIAz61yheJa+dsXli4GAAD/SW98/YaliwD8J2Ta3vgBAAAAAMCzydgO+gAAAAAAQLqjZh8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBgCPsAAAAAABgMYR8AAAAAAIMh7AMAAAAAYDCEfQAAAAAADIawDwAAAACAwRD2AQAAAAAwGMI+AAAAAAAGQ9gHAAAAAMBg/g+dxEipFcBwwQAAAABJRU5ErkJggg==\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_5_heatmap_1.0_classical.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x400 with 1 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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_6_confidence_comparison.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1100x600 with 1 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\n"},"metadata":{}}],"source":["# -------------------------\n","# Evaluation: Attention/Confidence (LyricLoop 1.0)\n","# -------------------------\n","\n","print(\"Generating LyricLoop 1.0 Confidence Analysis...\")\n","\n","# Ensure baseline data exists\n","if not history[\"baseline\"][\"avg_confidence\"]:\n","    print(\"Baseline data missing from history. Re-calculating or using defaults...\")\n","\n","test_cases = [\n","    (\"Hip-hop\", \"Kendrick Lamar\", \"City Struggle\"),\n","    (\"Pop\", \"Taylor Swift\", \"First Love\"),\n","    (\"Country\", \"Luke Combs\", \"Dirt Road\"),\n","    (\"EDM\", \"Zedd\", \"Last Hope\"),\n","    (\"Classical\", \"Mozart\", \"Nature Choral\")\n","]\n","\n","v1_avg_confidences = []\n","\n","for genre, artist, title in test_cases:\n","    # Build prompt exactly as the model was trained\n","    prompt = build_inference_prompt(genre, artist, title)\n","\n","    # Extract confidences using global utility\n","    token_pairs = get_token_confidences(model, tokenizer, prompt)\n","\n","    # Render and save the heatmap\n","    avg_conf = plot_token_heatmap(\n","        token_pairs,\n","        title=f\"LyricLoop 1.0: {genre}\",\n","        filename=f\"eval_5_heatmap_1.0_{genre.lower()}.png\"\n","    )\n","    v1_avg_confidences.append(avg_conf)\n","\n","# Storage\n","history[\"1.0\"][\"avg_confidence\"] = v1_avg_confidences\n","\n","# Final comparison visualization\n","plot_confidence_summary(\n","    genres=[t[0] for t in test_cases],\n","    scores={\n","        \"Baseline (Untrained)\": history[\"baseline\"][\"avg_confidence\"],\n","        \"LyricLoop 1.0 (Fine-Tuned)\": history[\"1.0\"][\"avg_confidence\"]\n","    },\n","    title=\"Confidence Boost: Baseline vs. LyricLoop 1.0\",\n","    filename=\"eval_6_confidence_comparison.png\"\n",")"]},{"cell_type":"markdown","source":["# User Interface for LyricLoop 1.0"],"metadata":{"id":"fikE4SP3VUij"}},{"cell_type":"code","source":["# -------------------------\n","# User Interface: LyricLoop Studio\n","# -------------------------\n","\n","# Widget definitions & styling\n","style = {'description_width': 'initial'}\n","layout = widgets.Layout(width='400px')\n","\n","genre_widget = widgets.Dropdown(\n","    options=[\"Pop\", \"Hip-hop\", \"Country\", \"EDM\", \"R&B\"],\n","    value=\"Pop\",\n","    description=\"Genre:\",\n","    style=style,\n","    layout=layout\n",")\n","\n","artist_widget = widgets.Text(\n","    placeholder=\"e.g. Taylor Swift\",\n","    description=\"Artist Style:\",\n","    style=style,\n","    layout=layout\n",")\n","\n","title_widget = widgets.Text(\n","    placeholder=\"e.g. Midnight Rain\",\n","    description=\"Song Title:\",\n","    style=style,\n","    layout=layout\n",")\n","\n","generate_btn = widgets.Button(\n","    description=\"Generate Lyrics\",\n","    button_style='primary',\n","    layout=widgets.Layout(width='200px', margin='10px 0 10px 105px')\n",")\n","\n","output_area = widgets.Output()\n","\n","# Unified Event Handler\n","def on_click_generate(b):\n","    output_area.clear_output()\n","\n","    # Input Validation\n","    if not artist_widget.value or not title_widget.value:\n","        with output_area:\n","            print(\"Error: Please enter both an Artist and a Title.\")\n","        return\n","\n","    with output_area:\n","        # Call the existing 'lyricloop' interface function.\n","        # This function handles building the prompt, the engine execution,\n","        # the text formatting, and the history logging automatically.\n","        lyricloop(\n","            genre=genre_widget.value,\n","            artist=artist_widget.value,\n","            title=title_widget.value\n","        )\n","\n","generate_btn.on_click(on_click_generate)\n","\n","# Display Layout\n","ui_box = widgets.VBox([\n","    widgets.HTML(\"<h2>LyricLoop v1.0</h2>\"),\n","    widgets.HTML(\"<p style='color: gray;'>Configure your song details below:</p>\"),\n","    genre_widget,\n","    artist_widget,\n","    title_widget,\n","    generate_btn,\n","    widgets.HTML(\"<hr>\"),\n","    output_area\n","])\n","\n","display(ui_box)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":276,"referenced_widgets":["157346aadfed417a887c98ff79b1e334","d318f0c0b2ea417c88aa5b1717514b0a","a1512b7b1e804ff8b39424109d67317a","d7ccc12a2768408bbb558ef961d64bf7","d0c26128b171400a8227f7e367efbb0c","ab9c04641e354818b700a7aa01886434","ba67611accd44f4abffd7b8bcab53334","dc065d88abbb47c0b8d8329b6fa2e496","fa9cfdbb3d8b49b7bbde3e4c41acfc81","302810ca84de49c19f6dffa2da06fcb8","adc66a6442ab49e994b599c0dfc8d1d5","7cec349167dd4536aede955d85dcd8f1","1f1a6197ae434f329234fb07dfdb529c","7cd803ca1ce04c56aa59919cc917ff50","8ed28a5fc993405288c55b604ce4b535","65552a2ea2584154a55d6a4cd5a89697","4e9050bc96c645b082bd4b2d29e01ac9","4292e52be612444085be1c5edea316da","ea71240c342f49ebb2840be60e737d9f","c518198fd06a4f17895339384b2e22f8","c2118d41fd4442ffb5ca5d2d60adbabc","9d20807c730e499fa1139f85819ec354","2f5426311e9248d5adec02bd4de3bb9b"]},"id":"2aqsc35XH_TF","outputId":"f09bd48f-670f-4741-e1a0-13587e2089b5","executionInfo":{"status":"ok","timestamp":1768933242711,"user_tz":300,"elapsed":23,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"execution_count":21,"outputs":[{"output_type":"display_data","data":{"text/plain":["VBox(children=(HTML(value='<h2>LyricLoop v1.0</h2>'), HTML(value=\"<p style='color: gray;'>Configure your song …"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"157346aadfed417a887c98ff79b1e334"}},"metadata":{}}]},{"cell_type":"markdown","source":["# Base Critique Model (Gemma)"],"metadata":{"id":"vVSyO7FcSt5d"}},{"cell_type":"code","source":["# -------------------------\n","# Critic Model Configuration (Gemma)\n","# -------------------------\n","\n","# Clear VRAM from the 1.0 Training\n","torch.cuda.empty_cache()\n","torch.cuda.ipc_collect()\n","\n","# Load specialized tokenizer\n","evaluator_tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)\n","if evaluator_tokenizer.pad_token is None:\n","    evaluator_tokenizer.pad_token = evaluator_tokenizer.eos_token\n","\n","# Load base model with 4-bit quantization\n","evaluator_base = AutoModelForCausalLM.from_pretrained(\n","    MODEL_ID,\n","    quantization_config=bnb_config,\n","    device_map=\"auto\",\n","    dtype=torch.float16,\n","    attn_implementation=\"sdpa\",\n",")\n","\n","evaluator_model = get_peft_model(prepare_model_for_kbit_training(evaluator_base), lora_config)\n","print(\"Critic Model Loaded!\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":67,"referenced_widgets":["13eb98663a4445aaae71df9654f66099","1d9683171de24a3c9b72f5cfcf28a77c","3fa87408cc3b4b4db30b7f89c6f3b448","fceef46ac3b14fbbb6d53bc1242712fa","2e27f5cbcd194d2cae80489743ec36d2","9da83822adc1491b939831f8f45a95b6","66a7e1056a8f403bba3421adaf0c2ce4","53746a6b93a248feaf14a73fd6da1e98","88909c6db2fc4a668c9371f78a886062","c94af9d6af954d2a87c5b4b47e0bff6b","8bc0d39c9ec64184bd88b714c05916f0"]},"id":"-EDdIhU78q3e","executionInfo":{"status":"ok","timestamp":1768933250458,"user_tz":300,"elapsed":5621,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}},"outputId":"7094613e-6f0a-4dfb-e2f6-a445a43fa76f"},"execution_count":22,"outputs":[{"output_type":"display_data","data":{"text/plain":["Loading checkpoint shards:   0%|          | 0/2 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"13eb98663a4445aaae71df9654f66099"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Critic Model Loaded!\n"]}]},{"cell_type":"code","source":["# -------------------------\n","# Inference Step: Critic Model\n","# -------------------------\n","\n","def lyric_critic(genre, artist, title, lyrics):\n","    \"\"\"\n","    Local interface for the Critic.\n","    Uses the global build_critic_prompt and execute_generation.\n","    \"\"\"\n","    prompt = build_critic_prompt(genre, artist, title, lyrics)\n","\n","    # Want consistent, objective feedback, not creative variations\n","    feedback = execute_generation(\n","        evaluator_model,\n","        evaluator_tokenizer,\n","        prompt,\n","        max_tokens=200\n","    )\n","\n","    return feedback"],"metadata":{"id":"o_tUPij383-5","executionInfo":{"status":"ok","timestamp":1768933250473,"user_tz":300,"elapsed":7,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"execution_count":23,"outputs":[]},{"cell_type":"code","source":["# -------------------------\n","# Testing: Critic Model\n","# -------------------------\n","\n","# Sample a song\n","sample_row = lyrics_df.groupby(\"tag\").sample(1, random_state=RANDOM_STATE).iloc[0]\n","\n","# Run Critique\n","print(f\"Evaluating: '{sample_row.title}' by {sample_row.artist} ({sample_row.tag})\\n\")\n","\n","critique = lyric_critic(\n","    genre=sample_row.tag,\n","    artist=sample_row.artist,\n","    title=sample_row.title,\n","    lyrics=sample_row.lyrics\n",")\n","\n","print(critique)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"mIjfENz4-NDP","executionInfo":{"status":"ok","timestamp":1768933268550,"user_tz":300,"elapsed":18076,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}},"outputId":"ba2f6c51-e182-47ce-8d57-c3fd2a2d58e4"},"execution_count":24,"outputs":[{"output_type":"stream","name":"stdout","text":["Evaluating: 'Turtles All the Way Down' by Sturgill Simpson (country)\n","\n","## Feedback on \"Turtles All theWayDown\" (Country, Sturgil Simpson)\n","\n","**Strengths:**\n","\n","* **Lyrical depth:** The lyrics explore themes of faith, doubt, and self-discovery through a country lens. They are relatable and evoke strong emotions.\n","* **Strong imagery:** The use of imagery like flames, lions, and Buddha creates vivid mental images and enhances the emotional impact.\n"," * **Character development:** The speaker's journey from initial skepticism to genuine belief is well-articulated.\n","\n","**Areas for Improvement:**\n","\n","**Verse 1:**\n","\n","While the imagery is impactful, the lyrics could be more concise and impactful. Consider cutting out unnecessary repetition or redundancy.\n","\n","> \"I'm burnin' down the cross / Burnin' out the pain / Burned out by the cross\"\n","\n","**Chorus:**\n","\n","The chorus is the heart of the song. While it effectively captures the essence of the theme, it could be strengthened by adding a\n"]}]},{"cell_type":"markdown","source":["## Model Evaluation (Base Critique Model)"],"metadata":{"id":"H6pBDneK8NFr"}},{"cell_type":"code","source":["# -------------------------\n","# Evaluation: Base Critique Model (Untrained)\n","# -------------------------\n","\n","print(\"Establishing Base Critique Performance Baseline...\")\n","\n","# Data selection\n","critique_lyrics_df = lyrics_df.groupby(\"tag\", group_keys=False).sample(\n","    n=1,\n","    replace=False,\n","    random_state=RANDOM_STATE\n",")\n","\n","# Generate critique prompts\n","critique_prompts = [\n","    build_critic_prompt(row.tag, row.artist, row.title, row.lyrics)\n","    for row in critique_lyrics_df.itertuples()\n","]\n","\n","# Calculate perplexity\n","baseline_critique_ppl = [\n","    calculate_perplexity(evaluator_model, evaluator_tokenizer, p)\n","    for p in critique_prompts\n","]\n","\n","# Metric persistence\n","history[\"baseline\"][\"critique_ppl\"] = baseline_critique_ppl\n","\n","# Standardized visualization\n","plot_perplexity(\n","    genres=critique_lyrics_df[\"tag\"].to_list(),\n","    scores_dict={\"Base Critique (Untrained)\": baseline_critique_ppl},\n","    title=\"Base Critique Model Confusion (Perplexity)\",\n","    filename=\"eval_7_base_critique_perplexity.png\"\n",")\n","\n","print(\"Base Critique Evaluation Complete.\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":660},"id":"II_kH1VkmNWo","outputId":"951b2202-0e42-4804-f56c-e6eb78664134","executionInfo":{"status":"ok","timestamp":1768933269773,"user_tz":300,"elapsed":1221,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"execution_count":25,"outputs":[{"output_type":"stream","name":"stdout","text":["Establishing Base Critique Performance Baseline...\n","    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_7_base_critique_perplexity.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x600 with 1 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Base Critique Evaluation Complete.\n"]}]},{"cell_type":"markdown","source":["# SFT Critique Model (lyricloop-2.0)"],"metadata":{"id":"ogCbR9HHmHTt"}},{"cell_type":"code","source":["# -------------------------\n","# LyricLoop 2.0: The Refinement Loop (Draft -> Critique -> Revision)\n","# -------------------------\n","\n","def generate_with_refinement(genre, artist, title):\n","    \"\"\"\n","    Executes a three-step agentic workflow and displays each stage:\n","    1. Draft: Initial generation from the Songwriter (1.0).\n","    2. Critique: Evaluation and feedback from the Critic (2.0).\n","    3. Revision: Finalized lyrics incorporating the feedback.\n","\n","    Returns:\n","        tuple: (draft_lyrics, critique_feedback, finalized_lyrics)\n","    \"\"\"\n","    print(f\"Initializing Refinement Loop for: {title}\")\n","    print(\"-\"*50)\n","\n","    # Draft: generate initial lyrics using the songwriter (1.0)\n","    draft_prompt = build_inference_prompt(genre, artist, title)\n","    draft = execute_generation(model, tokenizer, draft_prompt, do_sample=True)\n","    print(\"--- Step 1: Draft ---\")\n","    print(draft)\n","    print(\"\\n\" + \"=\"*50 + \"\\n\")\n","\n","    # Critique: evaluated by the critic\n","    critique = lyric_critic(genre, artist, title, draft)\n","    print(\"--- Step 2: Critique ---\")\n","    print(critique)\n","    print(\"\\n\" + \"=\"*50 + \"\\n\")\n","\n","    # Revision: final polish by the Ssngwriter (1.0)\n","    revision_prompt = build_revision_prompt(genre, artist, title, draft, critique)\n","    final_version = execute_generation(model, tokenizer, revision_prompt, do_sample=True)\n","\n","    print(\"--- Step 3: Revised ---\")\n","    print(f\"Title: {title}\")\n","    print(\"-\" * 50)\n","    print(final_version)\n","    print(\"=\"*50)\n","\n","    return draft, critique, final_version"],"metadata":{"id":"Lxq7XkHhFFUg","executionInfo":{"status":"ok","timestamp":1768933269794,"user_tz":300,"elapsed":7,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"execution_count":26,"outputs":[]},{"cell_type":"code","source":["# -------------------------\n","# Execution: LyricLoop 2.0 (Pre-Training Test)\n","# -------------------------\n","\n","# Run the full loop\n","draft, critique, revised = generate_with_refinement(\n","    genre=\"Pop\",\n","    artist=\"Taylor Swift\",\n","    title=\"A Romance in New York City\"\n",")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"axXTEEsYFcRZ","executionInfo":{"status":"ok","timestamp":1768933325384,"user_tz":300,"elapsed":55587,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}},"outputId":"fed47b3a-35e7-423a-bdfe-add0ee3e1355"},"execution_count":27,"outputs":[{"output_type":"stream","name":"stdout","text":["Initializing Refinement Loop for: A Romance in New York City\n","--------------------------------------------------\n","--- Step 1: Draft ---\n","[Verse 1]\n","Every time I think about you,\n","I'm picturing that taxi scene.\n","The way you were looking down at me\n","Through your tinted windows, window, window.\n","\n","The way I could see you\n","In the seat next to me.\n","It's a romantic city for two,\n","New York City for two.\n","\n","[Pre-Chorus]\n","You said, \"Will you still be my baby?\"\n","On the subway, just the two of us,\n","Waiting for the Brooklyn Bridge to close\n","After midnight, just you and me.\n","\n","And I said,\n","\"I'll always be your baby\"\n","[Hook]\n","Just some random people walking down the street\n","A little romance in the summer evening\n","Walking down the streets with you, baby\n","Do you remember how it was?\n","My mind's made up of the moments we spent here\n","The love so strong, the moment rare.\n","We can move to a place with no cell phone signal\n","So we can spend our money\n","And walk all over the city\n","With no plans, just staying here.\n","\n","Just you and I, darling\n","Doing the things we've done before,\n","Holding hands in Central Park,\n","Putting our love into words,\n","Let's walk forever like we used to,\n","In this moment.\n","\n","Verse 2\n","We went shopping at some place on Madison,\n","Where we could hide and glance at\n","\n","==================================================\n","\n","--- Step 2: Critique ---\n","## Feedback on A Romance In New York CITY by Taylor Swift\n","\n","**Strengths:**\n","\n","* The lyrics effectively capture the essence of a romantic evening in NewYork City.\n","* They paint a vivid picture in the listener's mind through descriptive imagery and emotional language.\n","    * Lines like \"the way you was looking down\" and \"it's romantic city\" are powerful and evocative.\n","     * The repetition of \"you\" emphasizes the central relationship between the speaker and the person they're describing.\n","\n","**Areas for Improvement:**\n","\n","**1. Lack of depth:** While the lyrics are beautifully written, they lack the depth and complexity found in other pop songs. \n","\n","* Consider exploring themes of love, longing, or bittersweet memories associated with a romantic past.\n","   * This could involve delving into the emotional impact of the city on the couple.\n","\n"," **2. Limited use of figurative language:** Although the lyrics mention \"romantic city,\" they don't utilize many figurative\n","\n","==================================================\n","\n","--- Step 3: Revised ---\n","Title: A Romance in New York City\n","--------------------------------------------------\n","Everytime I think abour you, \n","I am picturing a taxi scene,\n","Theway you were looing down at\n","me through your tinted window,\n","Window,window.\n","\n","Walking down those streets\n","With you, we'd find a spot\n","To sit down, close our eyes,\n","Lean into each other,\n","Take in the sights, the sounds,\n","This is a romantic\n","City for two\n","\n","[Outro]\n","So will I, I'll still be your\n","baby, right now.\n","Right now.\n","==================================================\n"]}]},{"cell_type":"code","source":["# -------------------------\n","# Data Preparation: LyricLoop 2.0 (The Critic)\n","# -------------------------\n","\n","# Create the training and evaluation subsets sampling 100 rows for a quicker training run\n","train_review_df = lyrics_df.sample(1000, random_state=RANDOM_STATE)\n","eval_review_df = lyrics_df.drop(train_review_df.index).sample(200, random_state=RANDOM_STATE)\n","\n","# Map to the format the trainer expects\n","train_review_dataset = Dataset.from_pandas(train_review_df)\n","train_review_dataset = train_review_dataset.map(\n","    lambda x: {\"text\": format_critic_training_row(pd.Series(x))}\n",")\n","\n","eval_review_dataset = Dataset.from_pandas(eval_review_df)\n","eval_review_dataset = eval_review_dataset.map(\n","    lambda x: {\"text\": format_critic_training_row(pd.Series(x))}\n",")\n","\n","print(f\"Critic Datasets Prepared: {len(train_review_dataset)} train, {len(eval_review_dataset)} eval\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":99,"referenced_widgets":["7aaf556ebd69452ba722a16fb5e299b6","2f49d4e038594455966eaf4dab74685b","3c58a1e89a8c4e4c9b3aab8bf7f78fb1","6cecb07120d942d18849d9db8936ec18","1f4dececfaa0432bbc9d2039856b1b42","0831d0de34b243ef9e717da12a89e789","5fb2df5e3d3d4ee99913f376b54b8460","8dd6c93fce904f6199165a68b2f1fa3e","05b174d9f2a2441685e4ec4408a2d830","93b27c26180446238f51feee029cd435","ce9ed49998554796abfeb2b0894789ba","5bd11d1d83804e328aec91fda5315b7b","44ff18f0878041898d0d82571a180658","e1232ce72fec4756b8469e7131db4257","3f9c988229264e1fac5ecc4f49e2b963","5e20e25736e24363a26e1dbf45e996a5","616562fbc0e24129813fbc9967f99122","8abfdc1a7cb846ecbe9bd090096344ec","f7085bd69fa2460989febd81e1f53a05","3d8ebfaf365d4ae7be93f9c950c9b9b5","da56e4fc184940a3aa273974e3406ccf","70c63e08a47c4d0eba3cd6e3168bb8e6"]},"id":"hABOW5VxJqDs","executionInfo":{"status":"ok","timestamp":1768933326042,"user_tz":300,"elapsed":652,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}},"outputId":"e7087518-d0ca-48f2-9b0e-bfe3ec36a7b1"},"execution_count":28,"outputs":[{"output_type":"display_data","data":{"text/plain":["Map:   0%|          | 0/1000 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"7aaf556ebd69452ba722a16fb5e299b6"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Map:   0%|          | 0/200 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"5bd11d1d83804e328aec91fda5315b7b"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Critic Datasets Prepared: 1000 train, 200 eval\n"]}]},{"cell_type":"code","source":["# -------------------------\n","# Training: LyricLoop 2.0 (The Critic)\n","# -------------------------\n","\n","# Define new 2.0 model version\n","MODEL_VERSION = \"2.0\"\n","\n","# Redefine 2.0 directories\n","EXPERIMENT_DIR = f\"experiments/{MODEL_VERSION}-run\"\n","FINAL_MODEL_DIR = f\"models/lyricloop-{MODEL_VERSION}\"\n","\n","# Define training configuration (SFTConfig)\n","# Optimized for L4 VRAM (24GB) to ensure stability during instruction tuning\n","training_review_args = SFTConfig(\n","    output_dir=EXPERIMENT_DIR,\n","    per_device_train_batch_size=4,\n","    per_device_eval_batch_size=4,\n","    gradient_accumulation_steps=8,\n","\n","    learning_rate=2e-4,\n","    optim=\"paged_adamw_8bit\",\n","\n","    # Precision & Memory Safety\n","    bf16=True,\n","    fp16=False,\n","    gradient_checkpointing=True,\n","\n","    # Evaluation & Logging Strategy\n","    logging_steps=5,\n","    eval_strategy=\"steps\",\n","    eval_steps=20,\n","    save_strategy=\"steps\",\n","    save_steps=20,\n","    warmup_steps=10,\n","\n","    # Experiment Tracking\n","    report_to=\"wandb\",\n","    run_name=\"lyricloop-v2\",\n","\n","    # Persistence\n","    save_total_limit=2,\n","    load_best_model_at_end=True,\n","    metric_for_best_model=\"eval_loss\",\n","\n","    # Training Duration\n","    num_train_epochs=3,    # execution time around 15 min\n","    max_length=512,\n","    dataset_text_field=\"text\",\n","    packing=False\n",")\n","\n","# Initialize the SFTTrainer to target the 'evaluator_model' specifically\n","print(\"Initializing Critic Trainer...\")\n","review_trainer = SFTTrainer(\n","    model=evaluator_model,\n","    train_dataset=train_review_dataset,\n","    eval_dataset=eval_review_dataset,\n","    args=training_review_args,\n","    processing_class=evaluator_tokenizer\n",")\n","\n","# Execution\n","print(\"Starting Critic Training (LyricLoop 2.0)...\")\n","review_trainer.train()\n","\n","# Persistence\n","review_adapter_path = FINAL_MODEL_DIR\n","review_trainer.model.save_pretrained(review_adapter_path)\n","print(f\"Training complete! Critic Adapter saved to: {review_adapter_path}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":766,"referenced_widgets":["ea6a98c956da4e52b90c886c253e35f4","08468a325fe2440ca2e6888f5a03095a","afd2b03040c54568ab97a10a4f266931","e0de0d0924be4f419516e7c622a76ea2","a66c897d66b6447b88e7f3f057d81665","ffa24b4bc6bb422aad8fdfe5715c9b6f","751a53769fa94edd8e21ecee44753b5b","49f145f286a2465387e5c3a6178ff62c","9e54be149bee4e6f810f9ac43fd0680b","ea373a932744450da07847bc441b6837","1cc821efe4e743149a1d912cae4ed1b7","6e3d130f7c874d56a6cd8eb80eac944a","4c263def2e4a42fe9fa2eea9e20542a5","fa7d25c193734350b2e42ec7762b66f0","7b373ecda9b9499eabcd4626a6960d0a","78742564c34244139151ed089842303c","86174e2262be4a329cce6f1f829d5dd0","e57f0c45f3ea48c3b3a77d2cdf96159e","87da6a2c13604c259edb80726d211b77","d2287d1964d44aa5b78ba7806365b26d","31fc017590b745908649caff6cac659a","bf06c0f37ccd404fb981ca8072886a53","6b9fddf494474920b37d14c9ba8cd4c3","15d925e7ffb6403490fa29452a9cca26","c9723f6d2b5448748e21b9813f82063a","f3084601cedd43c48785be9abaa4e415","d3f278fce7ca496fb16d377f429e8d6c","69f1fc1b978e4f6cbe4228fc43f95b61","b3ac8e8125fc4814af2a36b626629da8","5014bca598934db99b8aa110ba6473e5","567fd1a71d194fc387ba855d9ba258a6","18dbf1a5bd494a318eacdb19139082ad","5a900e35a5bf4815a373060ae5f62074","276069a11b5a4e17bb11042d58b4bfc8","5ffaa25e9b374a39b17260d70f630050","2e4d62b1b26b4e858e2140147a373b5a","8bfbe98147b24e8094cd705c14588aa2","4bc926452768408bb41ba1fa913cde4f","97ccdc7509e345409f72befeaef8b858","a554c0a3871a4a1e8db42c197b1f2a76","c66f3622a0f844bf939713cf147aa467","fcf48c79c6144bc298df9e21c750beb9","683a256bcd874665b19f23ed100301f8","9de256a3cf584795b70587c567c43d53","c1bea45a9fd74f09a589e9552cf35058","0b9daeaa93f646e490828957a106ffd1","9e42aa23939343c69d597c12969f2655","2ee750b7cd9f4821bf760212956365d7","5381bf7ed9664ad49e8ee15aa74a9b36","0c059db4bb904b2c94e6b23614f9a2ff","dae6972c209d4930a81981a2bfab3674","15eb3184660d4d119d6cf1c0df479644","383177938bb14d4cbee41df3e247845e","a0c3f4c7790749c7acf097e64c37d9b6","83cc8c63fc17443d91febcce63ff0a97","2f59ad2c46d240c7af2d6df46977c7e1","dd29f6f442c9436ea9554e7ad22825da","7b39455b430949acbde13b2a1458d920","ff2ef0279e0549d5a8212b0694443daa","d425431bd19b463dbe6bbd1c409a7624","261d5c9346fa48768d383576aeca6329","06fc7e30dc60468f9b9f4b0d8b8a776d","cfc4b28398ad4cfe8b6b88cd952b9f90","19c50fe3987b405ea4b167d7b6952f9c","c8632e4cfa8849789e64aeb5330e0fb0","ce17f3528311473fb4a350ababf82800"]},"id":"FIsMR4XURPSf","outputId":"89644f1a-3aa7-4536-d76c-988c97ad7dac","executionInfo":{"status":"ok","timestamp":1768934253713,"user_tz":300,"elapsed":927657,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"execution_count":29,"outputs":[{"output_type":"stream","name":"stdout","text":["Initializing Critic Trainer...\n"]},{"output_type":"display_data","data":{"text/plain":["Adding EOS to train dataset:   0%|          | 0/1000 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"ea6a98c956da4e52b90c886c253e35f4"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Tokenizing train dataset:   0%|          | 0/1000 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"6e3d130f7c874d56a6cd8eb80eac944a"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Truncating train dataset:   0%|          | 0/1000 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"6b9fddf494474920b37d14c9ba8cd4c3"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Adding EOS to eval dataset:   0%|          | 0/200 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"276069a11b5a4e17bb11042d58b4bfc8"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Tokenizing eval dataset:   0%|          | 0/200 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"c1bea45a9fd74f09a589e9552cf35058"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["Truncating eval dataset:   0%|          | 0/200 [00:00<?, ? examples/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"2f59ad2c46d240c7af2d6df46977c7e1"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Starting Critic Training (LyricLoop 2.0)...\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.12/dist-packages/notebook/notebookapp.py:191: SyntaxWarning: invalid escape sequence '\\/'\n","  | |_| | '_ \\/ _` / _` |  _/ -_)\n","\u001b[34m\u001b[1mwandb\u001b[0m: (1) Create a W&B account\n","\u001b[34m\u001b[1mwandb\u001b[0m: (2) Use an existing W&B account\n","\u001b[34m\u001b[1mwandb\u001b[0m: (3) Don't visualize my results\n","\u001b[34m\u001b[1mwandb\u001b[0m: Enter your choice:"]},{"name":"stdout","output_type":"stream","text":[" 2\n"]},{"output_type":"stream","name":"stderr","text":["\u001b[34m\u001b[1mwandb\u001b[0m: You chose 'Use an existing W&B account'\n","\u001b[34m\u001b[1mwandb\u001b[0m: Logging into https://api.wandb.ai. (Learn how to deploy a W&B server locally: https://wandb.me/wandb-server)\n","\u001b[34m\u001b[1mwandb\u001b[0m: Find your API key here: https://wandb.ai/authorize?ref=models\n","\u001b[34m\u001b[1mwandb\u001b[0m: Paste an API key from your profile and hit enter:"]},{"name":"stdout","output_type":"stream","text":[" ··········\n"]},{"output_type":"stream","name":"stderr","text":["\u001b[34m\u001b[1mwandb\u001b[0m: No netrc file found, creating one.\n","\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n","\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mlxtung95\u001b[0m (\u001b[33mlxntung95\u001b[0m) to \u001b[32mhttps://api.wandb.ai\u001b[0m. Use \u001b[1m`wandb login --relogin`\u001b[0m to force relogin\n"]},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":[]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["Tracking run with wandb version 0.23.1"]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["Run data is saved locally in <code>/content/drive/My Drive/repositories/lyricloop-llm/wandb/run-20260120_182456-l8sbkal6</code>"]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["Syncing run <strong><a href='https://wandb.ai/lxntung95/huggingface/runs/l8sbkal6' target=\"_blank\">lyricloop-v2</a></strong> to <a href='https://wandb.ai/lxntung95/huggingface' target=\"_blank\">Weights & Biases</a> (<a href='https://wandb.me/developer-guide' target=\"_blank\">docs</a>)<br>"]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":[" View project at <a href='https://wandb.ai/lxntung95/huggingface' target=\"_blank\">https://wandb.ai/lxntung95/huggingface</a>"]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":[" View run at <a href='https://wandb.ai/lxntung95/huggingface/runs/l8sbkal6' target=\"_blank\">https://wandb.ai/lxntung95/huggingface/runs/l8sbkal6</a>"]},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["\n","    <div>\n","      \n","      <progress value='96' max='96' style='width:300px; height:20px; vertical-align: middle;'></progress>\n","      [96/96 12:22, Epoch 3/3]\n","    </div>\n","    <table border=\"1\" class=\"dataframe\">\n","  <thead>\n"," <tr style=\"text-align: left;\">\n","      <th>Step</th>\n","      <th>Training Loss</th>\n","      <th>Validation Loss</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <td>20</td>\n","      <td>1.754300</td>\n","      <td>1.700993</td>\n","    </tr>\n","    <tr>\n","      <td>40</td>\n","      <td>1.378400</td>\n","      <td>1.418855</td>\n","    </tr>\n","    <tr>\n","      <td>60</td>\n","      <td>1.282700</td>\n","      <td>1.320495</td>\n","    </tr>\n","    <tr>\n","      <td>80</td>\n","      <td>1.051500</td>\n","      <td>1.296229</td>\n","    </tr>\n","  </tbody>\n","</table><p>"]},"metadata":{}},{"output_type":"stream","name":"stdout","text":["Training complete! Critic Adapter saved to: models/lyricloop-2.0\n"]}]},{"cell_type":"code","source":["# -------------------------\n","# Evaluation: LyricLoop 2.0 (Post-Training Test)\n","# -------------------------\n","\n","print(\"Generating trained critique results...\")\n","print(\"This test demonstrates the model's performance after critic-specific fine-tuning.\")\n","print(\"-\"*50 + \"\\n\")\n","\n","# Use the exact same test case to see the 'Before vs After' improvement\n","draft_2, critique_2, revised_2 = generate_with_refinement(\n","    genre=\"Pop\",\n","    artist=\"Taylor Swift\",\n","    title=\"A Romance in New York City\"\n",")\n","\n","# Store the 'After' results for your final project summary\n","history[\"2.0\"][\"sample_critique\"] = critique_2"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"EVNj-xI1bbvQ","outputId":"01faa501-3420-4b9f-cdf1-a3c2eee26cfb","executionInfo":{"status":"ok","timestamp":1768934310605,"user_tz":300,"elapsed":56876,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"execution_count":30,"outputs":[{"output_type":"stream","name":"stdout","text":["Generating trained critique results...\n","This test demonstrates the model's performance after critic-specific fine-tuning.\n","--------------------------------------------------\n","\n","Initializing Refinement Loop for: A Romance in New York City\n","--------------------------------------------------\n","--- Step 1: Draft ---\n","[Verse 1]\n","Well, we came from money\n","And our mama's in nursing school\n","My brother's studying engineering\n","Our small town ain't so bad\n","\n","[Pre-Chorus 1: Swift]\n","I remember driving downtown at night, just two kids in a blue car\n","Waiting on Broadway, just wanting to get swept up in the stars\n","\n","[Chorus: Swift, Swift]\n","\n","I think it's great that we're not stuck up in a lot, just a little bit of romance\n","In a concrete jungle 'cause we know that success is after all the hard work\n","If you catch us out at any kind of fancy place, don't walk up and start talking fast\n","We might just be taking orders at the bar\n","\n","[Bridge: Swift/Swift]\n","You must be new around here, this is a classic spot\n","A coffee shop, people come and go\n","But how could you not fall in love\n","With the atmosphere we've built here?\n","\n","[Verse Two]\n","Some of our friends got jobs in finance\n","They got stock options and a penthouse apartment\n","So we went to a bar at the Top of the Rock\n","For our anniversary - we took on the world together\n","\n","[Interlude 1 - Swift] It's been a while since we were just\n","Couple college kids sneaking out\n","To the point that we haven't been sleeping over at each other's places\n","Now we'\n","\n","==================================================\n","\n","--- Step 2: Critique ---\n","Genre Fit: The pop style is well-maintained.\n","Artist Style: Matches the Taylor Swift aesthetic.\n","Improvements: Consider refining the rhythmic flow in the second verse.\n","\n","==================================================\n","\n","--- Step 3: Revised ---\n","Title: A Romance in New York City\n","--------------------------------------------------\n","I'm glad you're now seeing where we'll be tonight\n","I gotta say, with the way things turned out\n","It doesn't scare me anymore\n","We can make the most of what we got\n","I know, this isn't just a fling\n","I think these things will last\n","I can already see the future, yeah\n","\n","[Refrain]\n","And I don' t-t-think it matters\n","If there's no one else by my side\n","But I-i-know you won't try\n","As much as I tried to find a way to leave you\n","\n","[Post-Chorus - Swift, Swiftui]\n","So come on, baby\n","Let's go watch the sunrise\n","Come on, I can't wait for the weekend\n","So I can take your hand again\n","\n","[Intro 1 Swiftu]\n","It's amazing how life takes us\n","Where nobody ever expected us\n","Would put us\n","Together\n","Here in this moment\n","\n","[Refused Duet - Swif Bluffs, Swift]\n","Baby, what took so long?\n","I wish I had known then\n","That we could make it last\n","We could have made it last, last\n","\n","[Outro - Swift:]\n","Last\n","Oh\n","The sun comes up on another day\n","Another day\n","It fades away\n","Another night, another day, another city\n","Another city\n","She's walking down the street\n","Just another day in this town\n","==================================================\n"]}]},{"cell_type":"markdown","source":["## Model Evaluation (lyricloop-2.0)"],"metadata":{"id":"_hJyTimPEkgW"}},{"cell_type":"code","source":["# -------------------------\n","# Evaluation: LyricLoop 2.0 Loss Curves\n","# -------------------------\n","\n","# Visualize the training performance of the Critic model\n","print(\"Generating Loss Curves for LyricLoop 2.0 (The Critic)...\")\n","\n","# Extract the step-by-step history using your global utility\n","critic_metrics = extract_trainer_metrics(review_trainer)\n","\n","# Visualize the performance\n","plot_learning_curves(critic_metrics, version=\"2.0\")\n","\n","# Log the final values to your global history for the final report\n","if review_trainer.state.log_history:\n","    # Use the extracted metrics for consistency\n","    history[\"2.0\"][\"metrics\"][\"final_loss\"] = critic_metrics[\"train_loss\"][-1]\n","    if critic_metrics[\"eval_loss\"]:\n","        history[\"2.0\"][\"metrics\"][\"final_eval_loss\"] = critic_metrics[\"val_loss\"]\n","\n","print(\"Loss curves generated and saved to /assets.\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":661},"id":"T1Oi0fqmhVWm","outputId":"cc3cf482-a44f-4e75-b2a7-4081f8d9b557","executionInfo":{"status":"ok","timestamp":1768934311307,"user_tz":300,"elapsed":694,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"execution_count":31,"outputs":[{"output_type":"stream","name":"stdout","text":["Generating Loss Curves for LyricLoop 2.0 (The Critic)...\n","    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_loss_curve_2.0.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1200x600 with 1 Axes>"],"image/png":"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curves generated and saved to /assets.\n"]}]},{"cell_type":"code","source":["# -------------------------\n","# Evaluation: LyricLoop 2.0 Perplexity Comparison\n","# -------------------------\n","\n","print(\"Calculating Post-Training Perplexity for the Critic...\")\n","\n","# Calculate new scores using the 'evaluator_model' which now carries the LyricLoop 2.0 adapters\n","trained_critique_ppl = [\n","    calculate_perplexity(evaluator_model, evaluator_tokenizer, p)\n","    for p in critique_prompts\n","]\n","\n","# Persist metrics for the final project summary\n","history[\"2.0\"][\"critique_ppl\"] = trained_critique_ppl\n","\n","# Standardized Comparison Visualization\n","plot_perplexity(\n","    genres=critique_lyrics_df[\"tag\"].to_list(),\n","    scores_dict={\n","        \"Base Critique (Untrained)\": history[\"baseline\"][\"critique_ppl\"],\n","        \"Fine-Tuned Critique (2.0)\": trained_critique_ppl\n","    },\n","    title=\"Impact of Fine-Tuning on Critique Model Uncertainty\",\n","    filename=\"eval_9_critique_ppl_comparison.png\"\n",")\n","\n","# Statistical Summary\n","print(\"\\nPerplexity Improvement Summary:\")\n","print(\"-\" * 50)\n","genres = critique_lyrics_df[\"tag\"].to_list()\n","base_scores = history[\"baseline\"][\"critique_ppl\"]\n","\n","for g, base, new in zip(genres, base_scores, trained_critique_ppl):\n","    improvement = (base - new) / base * 100\n","    print(f\"{g:<12} | Baseline: {base:>6.1f} -> Trained: {new:>6.1f} | Improvement: {improvement:>5.1f}%\")\n","print(\"-\" * 50)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":820},"id":"kq8-ycoHiidi","outputId":"2d8fcabe-c871-47db-c389-1643306c5600","executionInfo":{"status":"ok","timestamp":1768934312715,"user_tz":300,"elapsed":1403,"user":{"displayName":"Alexander Tung","userId":"08068206678761504036"}}},"execution_count":32,"outputs":[{"output_type":"stream","name":"stdout","text":["Calculating Post-Training Perplexity for the Critic...\n","    Artifact Saved: /content/drive/My Drive/repositories/lyricloop-llm/assets/eval_9_critique_ppl_comparison.png\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 1000x600 with 1 Axes>"],"image/png":"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\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["\n","Perplexity Improvement Summary:\n","--------------------------------------------------\n","country      | Baseline:  227.8 -> Trained:    2.9 | Improvement:  98.7%\n","misc         | Baseline:   95.4 -> Trained:    2.8 | Improvement:  97.1%\n","pop          | Baseline:  282.7 -> Trained:    5.3 | Improvement:  98.1%\n","rap          | Baseline:  250.3 -> Trained:    6.7 | Improvement:  97.3%\n","rb           | Baseline:  125.6 -> Trained:    4.3 | Improvement:  96.6%\n","rock         | Baseline:  184.9 -> Trained:    3.8 | Improvement:  98.0%\n","--------------------------------------------------\n"]}]},{"cell_type":"markdown","source":["# User Interface for LyricLoop 2.0"],"metadata":{"id":"XXY4n3N1gE6t"}},{"cell_type":"code","source":["# -------------------------\n","# User Interface: LyricLoop Studio 2.0 (Refinement Mode)\n","# -------------------------\n","\n","# Widget Definitions & Styling by adding specific 2.0 labeling\n","style = {'description_width': 'initial'}\n","layout = widgets.Layout(width='450px')\n","\n","genre_widget = widgets.Dropdown(\n","    options=[\"Pop\", \"Hip-hop\", \"Country\", \"EDM\", \"R&B\", \"Rock\", \"Electronic\"],\n","    value=\"Pop\",\n","    description=\"Target Genre:\",\n","    style=style,\n","    layout=layout\n",")\n","\n","artist_widget = widgets.Text(\n","    placeholder=\"e.g. Taylor Swift\",\n","    description=\"Artist Style:\",\n","    style=style,\n","    layout=layout\n",")\n","\n","title_widget = widgets.Text(\n","    placeholder=\"e.g. Midnight Love\",\n","    description=\"Song Title:\",\n","    style=style,\n","    layout=layout\n",")\n","\n","# Using a distinct color to represent the Refinement mode\n","generate_btn = widgets.Button(\n","    description=\"Generate Lyrics\",\n","    button_style='success',    # green to indicate advanced mode\n","    layout=widgets.Layout(width='250px', margin='10px 0 10px 105px'),\n","    icon='magic'\n",")\n","\n","output_area = widgets.Output()\n","\n","# Refined Event Handler\n","def on_click_refinement(b):\n","    output_area.clear_output()\n","\n","    # Input Validation\n","    if not artist_widget.value or not title_widget.value:\n","        with output_area:\n","            print(\"Error: Please enter both an Artist and a Title to begin refinement.\")\n","        return\n","\n","    with output_area:\n","        # Utilizing the generate_with_refinement logic (Draft -> Critique -> Revision)\n","        # This function handles the model-switching and prompts automatically.\n","        try:\n","            draft, critique, revised = generate_with_refinement(\n","                genre=genre_widget.value,\n","                artist=artist_widget.value,\n","                title=title_widget.value\n","            )\n","\n","            # Post-Generation Logging\n","            # Log the 'Revised' version as the primary entry for history 2.0\n","            history[\"2.0\"][\"samples\"][title_widget.value] = {\n","                \"genre\": genre_widget.value,\n","                \"artist\": artist_widget.value,\n","                \"lyrics\": revised,\n","                \"critique\": critique\n","            }\n","\n","        except Exception as e:\n","            print(f\"Refinement Loop Error: {str(e)}\")\n","\n","generate_btn.on_click(on_click_refinement)\n","\n","# Display Layout add a header that explicitly mentions the Refinement Agent logic\n","ui_box = widgets.VBox([\n","    widgets.HTML(\"<h2 style='color: #2E86C1;'>LyricLoop Studio v2.0</h2>\"),\n","    widgets.HTML(\"<p style='color: gray;'><b>Mode:</b> Agentic Refinement (Draft → Critique → Revision)</p>\"),\n","    genre_widget,\n","    artist_widget,\n","    title_widget,\n","    generate_btn,\n","    widgets.HTML(\"<hr>\"),\n","    output_area\n","])\n","\n","display(ui_box)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":276,"referenced_widgets":["f13ef2049679448b84368c700733283c","961e72a6bfe8446292b8d0dd851029bd","4de2e2019e124304b4279e87adc07bc4","20a3817e7de84183ad136bc6fc280b0f","1c044eddd3ed4c06b921fbcbac922fbf","a5236eb5e7fe4231bb9c84076aeb0bea","8adb6f6b015345649c635b56c8f969aa","f41333e5f22d4b109e9e82f54d52d361","4948c28e4c7b43f5bdea3486824cc503","a7e35e71f1b54ba3959f67208863999e","822591dd222643449701d259a9dba653","f8dd4f885111408ea04b14d634007f7a","c79aea7b96e6466881c3ddba3c02e6c6","10c4c08a56454d748828817a9c7d8087","04031a98e47249d7bf3a5c61eb3680a4","93f58c42165b49bf9b57f24464ce3771","ca9676a0973d44e5900719a88a017afc","e154c546507a441283cf3cb73f5629b9","92c0996bf4e3486d945dbd9e09e479e5","e477b2bcc8454391a29996284215db2a","65bd2e4e91d94b9c8d9d7978684cfa83","62ce63ee1df04965a4538f972a08a919","97f485f9859e4647811bb56124adf230"]},"id":"9lOMOTlBgHMI","executionInfo":{"status":"ok","timestamp":1768934312747,"user_tz":300,"elapsed":29,"user":{"displayName":"Alexander 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