diff --git "a/scripts/04_Finetune_Embedding.ipynb" "b/scripts/04_Finetune_Embedding.ipynb"
new file mode 100644--- /dev/null
+++ "b/scripts/04_Finetune_Embedding.ipynb"
@@ -0,0 +1,9638 @@
+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "mcZqgUKBYQYn"
+      },
+      "source": [
+        "# Install Packages and Setup Variables\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "collapsed": true,
+        "id": "F0rUftGtpnZc",
+        "outputId": "fe0c7ec7-4773-4f39-8e08-d16e56ffe54b"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m19.3/19.3 MB\u001b[0m \u001b[31m98.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m259.5/259.5 kB\u001b[0m \u001b[31m14.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m94.9/94.9 kB\u001b[0m \u001b[31m5.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m284.2/284.2 kB\u001b[0m \u001b[31m16.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.3/3.3 MB\u001b[0m \u001b[31m91.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.9/1.9 MB\u001b[0m \u001b[31m65.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.7/7.7 MB\u001b[0m \u001b[31m105.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m266.8/266.8 kB\u001b[0m \u001b[31m15.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m41.0/41.0 kB\u001b[0m \u001b[31m2.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m101.6/101.6 kB\u001b[0m \u001b[31m5.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m16.4/16.4 MB\u001b[0m \u001b[31m102.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m65.8/65.8 kB\u001b[0m \u001b[31m2.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m55.7/55.7 kB\u001b[0m \u001b[31m2.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m196.2/196.2 kB\u001b[0m \u001b[31m8.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m118.5/118.5 kB\u001b[0m \u001b[31m6.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m4.5/4.5 MB\u001b[0m \u001b[31m88.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m100.0/100.0 kB\u001b[0m \u001b[31m5.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m363.4/363.4 MB\u001b[0m \u001b[31m2.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m13.8/13.8 MB\u001b[0m \u001b[31m106.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m24.6/24.6 MB\u001b[0m \u001b[31m94.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m883.7/883.7 kB\u001b[0m \u001b[31m36.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m664.8/664.8 MB\u001b[0m \u001b[31m2.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m211.5/211.5 MB\u001b[0m \u001b[31m5.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m56.3/56.3 MB\u001b[0m \u001b[31m42.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m127.9/127.9 MB\u001b[0m \u001b[31m21.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m207.5/207.5 MB\u001b[0m \u001b[31m4.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.1/21.1 MB\u001b[0m \u001b[31m92.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m186.1/186.1 kB\u001b[0m \u001b[31m8.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m459.8/459.8 kB\u001b[0m \u001b[31m27.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m374.1/374.1 kB\u001b[0m \u001b[31m18.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m304.2/304.2 kB\u001b[0m \u001b[31m18.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m71.5/71.5 kB\u001b[0m \u001b[31m4.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m4.0/4.0 MB\u001b[0m \u001b[31m77.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m453.1/453.1 kB\u001b[0m \u001b[31m20.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m46.0/46.0 kB\u001b[0m \u001b[31m2.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m207.4/207.4 kB\u001b[0m \u001b[31m10.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m86.8/86.8 kB\u001b[0m \u001b[31m4.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m50.9/50.9 kB\u001b[0m \u001b[31m2.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m115.4/115.4 kB\u001b[0m \u001b[31m7.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m129.3/129.3 kB\u001b[0m \u001b[31m6.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25h  Building wheel for pypika (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install -q llama-index==0.12.42 llama-index-finetuning==0.3.2 llama-index-embeddings-adapter==0.3.0 openai==1.84.0 tiktoken==0.9.0 chromadb==1.0.12 llama-index-vector-stores-chroma==0.4.2 cohere==5.15.0 llama-index-llms-gemini==0.5.0 html2text==2025.4.15 llama-index-llms-openai==0.4.7 llama-index-embeddings-huggingface==0.5.4 llama-index-embeddings-openai==0.3.1"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "RyE625lCtTsi"
+      },
+      "outputs": [],
+      "source": [
+        "import os\n",
+        "\n",
+        "# Set the following API Keys in the Python environment. Will be used later.\n",
+        "#os.environ[\"OPENAI_API_KEY\"] = \"<YOUR_API_KEY>\"\n",
+        "\n",
+        "from google.colab import userdata\n",
+        "os.environ[\"OPENAI_API_KEY\"] = userdata.get('openai_api_key')\n",
+        "\n",
+        "os.environ[\"HF_TOKEN\"] = userdata.get('HF_TOKEN2')\n",
+        "HF_TOKEN = userdata.get('HF_TOKEN2')"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "OWgHCmejcCFV"
+      },
+      "source": [
+        "# Download the Dataset\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "source": [
+        "from huggingface_hub import snapshot_download\n",
+        "\n",
+        "snapshot_download(repo_id=\"vicpada/AzureResources\", allow_patterns=[ \"*.pkl\"],repo_type=\"dataset\",local_dir=\"/content\")"
+      ],
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 67,
+          "referenced_widgets": [
+            "e3aaa3aa136542ff8a2b0f979d54384e",
+            "c2a6ac74466f4a28838026f4c65f9711",
+            "6c3e7f955cb64d91bd51db688b4ff6dc",
+            "fc7e632c559b4d319a8639ce3f477f14",
+            "dee1ff14e3d041c1ae9352743d13daf7",
+            "955937509365428faa9e5a70649a5348",
+            "c9c6746c92b044159c6159693c3b747c",
+            "86c805c91a7b4d2f8cc460e9e2cf20f0",
+            "769820a63a0c4630ba29408078bf1082",
+            "f9f342478ebe4f10a3f1a428e19d8fe9",
+            "972d9be1714d40249b04c6776bef756d"
+          ]
+        },
+        "id": "O_WVOh5oIw5_",
+        "outputId": "86c10632-48b4-4ea0-9a3c-32b60f7162df"
+      },
+      "execution_count": null,
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Fetching 4 files:   0%|          | 0/4 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "e3aaa3aa136542ff8a2b0f979d54384e"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "'/content'"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "string"
+            }
+          },
+          "metadata": {},
+          "execution_count": 8
+        }
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "qYb-F-uJiWNo",
+        "outputId": "ae4ee065-fd33-4f85-f90b-c1b8e3d0abd7"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Combined data from 5 files into a single list with 391414 items.\n"
+          ]
+        }
+      ],
+      "source": [
+        "# prompt: join all pkl into one file using pickle.load\n",
+        "\n",
+        "import pickle\n",
+        "import os\n",
+        "\n",
+        "all_data = []\n",
+        "\n",
+        "# Assuming the directory is /content where the files were downloaded\n",
+        "for filename in os.listdir('/content'):\n",
+        "  if filename.endswith('.pkl'):\n",
+        "    file_path = os.path.join('/content', filename)\n",
+        "    with open(file_path, 'rb') as f:\n",
+        "      data = pickle.load(f)\n",
+        "      all_data.extend(data) # Assuming each pickle file contains a list\n",
+        "\n",
+        "# Optional: Save the combined data to a new pickle file\n",
+        "with open('combined_data.pkl', 'wb') as f:\n",
+        "  pickle.dump(all_data, f)\n",
+        "\n",
+        "print(f\"Combined data from {len([f for f in os.listdir('/content') if f.endswith('.pkl')])} files into a single list with {len(all_data)} items.\")\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "3R7P7GUmemIL"
+      },
+      "source": [
+        "### Splitting Dataset\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "85wLYJw6gic0"
+      },
+      "outputs": [],
+      "source": [
+        "import random\n",
+        "\n",
+        "random.shuffle(all_data)\n",
+        "split_index = int(len(all_data) * 0.9)\n",
+        "\n",
+        "# TRAIN_DOCs and VALIDATION_DOCs\n",
+        "TRAIN_NODEs = all_data[:split_index]\n",
+        "VALIDATION_NODEs = all_data[split_index:]"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "TGbmUhUVezdU"
+      },
+      "source": [
+        "# Chunking\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Y6iEHKfZsUiv"
+      },
+      "outputs": [],
+      "source": [
+        "# Use a subset of the dataset if testing.\n",
+        "\n",
+        "# Test with a few sample, processing dataset fully can be costly depanding on the size.\n",
+        "# NOTE: Checkpoints are provided in the lesson, so no need to run the code on full dataset.\n",
+        "\n",
+        "testing = False\n",
+        "\n",
+        "if testing:\n",
+        "    TRAIN_NODEs = TRAIN_NODEs[:10]\n",
+        "    VALIDATION_NODEs = VALIDATION_NODEs[:5]\n",
+        "else: #10000 is enough\n",
+        "    TRAIN_NODEs = TRAIN_NODEs[:9000]\n",
+        "    VALIDATION_NODEs = VALIDATION_NODEs[:1000]"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "LvKf6i9Lg_2G"
+      },
+      "source": [
+        "# Generate Question\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "1DMXD7nbhFsm"
+      },
+      "source": [
+        "We use a Large Language Model (LLM) to produce questions for each chunk of the dataset. Then we can use these data to train the model to develop embeddings that more accurately represent the types of questions users may ask.\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "C8fhKPVlMbz3",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "3fbbc669-4e17-44ba-c313-0539ed85d370"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "  6%|▌         | 500/8891 [06:12<1:16:36,  1.83it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 500 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 11%|█         | 1000/8891 [11:58<1:39:08,  1.33it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 1000 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 17%|█▋        | 1500/8891 [17:38<1:14:58,  1.64it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 1500 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 22%|██▏       | 2000/8891 [24:38<1:38:43,  1.16it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 2000 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 28%|██▊       | 2500/8891 [30:29<1:13:50,  1.44it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 2500 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 34%|███▎      | 3000/8891 [36:39<1:06:05,  1.49it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 3000 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 39%|███▉      | 3500/8891 [43:31<1:01:10,  1.47it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 3500 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 45%|████▍     | 4000/8891 [50:38<1:05:59,  1.24it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 4000 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 51%|█████     | 4500/8891 [56:45<48:04,  1.52it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 4500 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 56%|█████▌    | 5000/8891 [1:04:01<1:04:42,  1.00it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 5000 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 62%|██████▏   | 5500/8891 [1:09:18<40:14,  1.40it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 5500 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 67%|██████▋   | 6000/8891 [1:14:55<30:28,  1.58it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 6000 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 73%|███████▎  | 6500/8891 [1:20:44<26:17,  1.52it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 6500 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 79%|███████▊  | 7000/8891 [1:26:43<24:24,  1.29it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 7000 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 84%|████████▍ | 7500/8891 [1:33:10<20:52,  1.11it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 7500 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 90%|████████▉ | 8000/8891 [1:39:00<09:45,  1.52it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 8000 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 96%|█████████▌| 8500/8891 [1:45:14<17:20,  2.66s/it]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 8500 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "8901it [1:50:10,  1.34it/s]\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Final dataset saved.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            " 50%|█████     | 500/995 [06:29<05:35,  1.48it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 500 entries.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "1000it [11:49,  1.40it/s]"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Saved progress at 1000 entries.\n",
+            "Final dataset saved.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Use this block of code if you don't want to generate the questions for the dataset. (Avoid API call charges!)\n",
+        "# Uncomment the following code, and keep in mind to comment all the contents in the next coding block.\n",
+        "\n",
+        "\n",
+        "from llama_index.finetuning import generate_qa_embedding_pairs\n",
+        "from llama_index.llms.openai import OpenAI\n",
+        "\n",
+        "\n",
+        "\n",
+        "llm = OpenAI(model=\"gpt-4.1-nano\", temperature=1, max_tokens=512)\n",
+        "\n",
+        "#Generate questions for each chunk.\n",
+        "\n",
+        "TRAIN_DATASET = generate_qa_embedding_pairs(TRAIN_NODEs, llm=llm, num_questions_per_chunk=1, output_path=\"./train_dataset_full.json\")\n",
+        "\n",
+        "VALIDATION_DATASET = generate_qa_embedding_pairs(VALIDATION_NODEs,  num_questions_per_chunk=1, llm=llm, output_path=\"./val_dataset_full.json\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "R6CGytzHClGu",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "f9ccafa4-40a5-4b84-8cf0-ed86ff5875d3"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "No files have been modified since last commit. Skipping to prevent empty commit.\n",
+            "WARNING:huggingface_hub.hf_api:No files have been modified since last commit. Skipping to prevent empty commit.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "No files have been modified since last commit. Skipping to prevent empty commit.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "No files have been modified since last commit. Skipping to prevent empty commit.\n",
+            "WARNING:huggingface_hub.hf_api:No files have been modified since last commit. Skipping to prevent empty commit.\n"
+          ]
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "No files have been modified since last commit. Skipping to prevent empty commit.\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Upload the new documents CSV to Hugging Face\n",
+        "\n",
+        "from huggingface_hub import HfApi\n",
+        "\n",
+        "api = HfApi(token=HF_TOKEN)\n",
+        "\n",
+        "files = ['train_dataset_full.json','val_dataset_full.json']\n",
+        "\n",
+        "for file in files:\n",
+        "  api.upload_file(\n",
+        "      path_or_fileobj=file,\n",
+        "      path_in_repo=file,\n",
+        "      repo_id=\"vicpada/AzureResources\",\n",
+        "      repo_type=\"dataset\",\n",
+        "  )\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "geqDZn-pB4fI"
+      },
+      "outputs": [],
+      "source": [
+        "#from huggingface_hub import snapshot_download\n",
+        "#snapshot_download(repo_id=\"jaiganesan/Embedding-model-fine-tuning-dataset\", repo_type=\"dataset\",local_dir=\"/content/\")\n",
+        "\n",
+        "\n",
+        "#from llama_index.finetuning import EmbeddingQAFinetuneDataset\n",
+        "\n",
+        "# Load the pre-generated questions json files.\n",
+        "#TRAIN_DATASET = EmbeddingQAFinetuneDataset.from_json(\"./train_dataset.json\")\n",
+        "#VALIDATION_DATASET = EmbeddingQAFinetuneDataset.from_json(\"./val_dataset.json\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "Hthjh_SjlB-C"
+      },
+      "source": [
+        "# Load an Embedding Model\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "ZHWPMZHUupNW",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 369,
+          "referenced_widgets": [
+            "45873e43d6004511b0428bc59b6908bc",
+            "88cd12c3b98a456ba652108dd9e78477",
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+          ]
+        },
+        "outputId": "9b9a4b59-32cc-4f3f-c5b0-1e6223a8aa90"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "modules.json:   0%|          | 0.00/349 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "45873e43d6004511b0428bc59b6908bc"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "config_sentence_transformers.json:   0%|          | 0.00/124 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "d1e4d83f1e1d4af39c1cbfe55ca866c3"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "README.md:   0%|          | 0.00/94.8k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "ff97c055357143dc9f1c13ff59b3fa61"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "sentence_bert_config.json:   0%|          | 0.00/52.0 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "5d0593f9828f4777932c6df2ce65f67d"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "config.json:   0%|          | 0.00/743 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "5e0154cd06844415acbd911ebf4aa347"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "model.safetensors:   0%|          | 0.00/133M [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "55fe00f8fdd64aba8e240a9c696d5c16"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "tokenizer_config.json:   0%|          | 0.00/366 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "248a6b31169045d9bf1a4b94cbb20736"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "189017ccf08640c28d19c65375a8dfea"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "tokenizer.json:   0%|          | 0.00/711k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "1d1015ba9da2400ba9c3031fda7a65ee"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "special_tokens_map.json:   0%|          | 0.00/125 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "efc3ac3ddae644d5aa206bf5e5ddc1d8"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "config.json:   0%|          | 0.00/190 [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "79ac3c58d46b4c4a8ba409103e7a9725"
+            }
+          },
+          "metadata": {}
+        }
+      ],
+      "source": [
+        "from llama_index.core.embeddings import resolve_embed_model\n",
+        "\n",
+        "# Load an existing embedding model with a adapter layer on top.\n",
+        "base_embed_model = resolve_embed_model(\"local:BAAI/bge-small-en-v1.5\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "evLkr4EZB4cJ"
+      },
+      "outputs": [],
+      "source": [
+        "from llama_index.finetuning import EmbeddingAdapterFinetuneEngine\n",
+        "import torch\n",
+        "\n",
+        "# Finetune the adapter\n",
+        "finetune_engine = EmbeddingAdapterFinetuneEngine(\n",
+        "    TRAIN_DATASET,\n",
+        "    base_embed_model,\n",
+        "    model_output_path=\"model_output_test\",\n",
+        "    epochs=2,\n",
+        "    verbose=True,\n",
+        "    bias=True,\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000,
+          "referenced_widgets": [
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+            "f5b39d8727194ee69cf49d76a04b32fb",
+            "82873eb5697d4ca199321e6431cbf96e",
+            "e3c817ea61c0456898dafbe436675a19",
+            "e04374e6767d470aa7be288ddceb5a8b",
+            "c6b1a81f40f8493996cd1302b0503343",
+            "68824b033fc745af806021f0e17784d1",
+            "08183ed699e2452787a4496525d323b3",
+            "1acf7ae54aae4311b7ebf7730017a498",
+            "faef4f01a0354d87b9fc2e78a859e0bf",
+            "ce43818d26e54a55a4a83a463be62abd",
+            "a14473ac8d8040e7a0a823b1e4dd83a7",
+            "1662e09e772d4ad9bfd4883a6d5afa15",
+            "145ca301e54a428a8da9f1682ebe0fae"
+          ]
+        },
+        "collapsed": true,
+        "id": "qwi98s-RjXDA",
+        "outputId": "00af6c14-76c3-415d-945f-2aff70f820d6"
+      },
+      "outputs": [
+        {
+          "metadata": {
+            "tags": null
+          },
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\u001b[1;3;34m> Prepared optimizer, scheduler, and loss model.\n",
+            "\u001b[0m"
+          ]
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "af338204d9bc49de9f8df27ff99946ef",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Epoch:   0%|          | 0/2 [00:00<?, ?it/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "f78735205e79483ca507915cd8846dbb",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Iteration:   0%|          | 0/892 [00:00<?, ?it/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "metadata": {
+            "tags": null
+          },
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\u001b[1;3;34m> [Epoch 0] Current loss: 1.1686890125274658\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2109415531158447\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0172332525253296\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.46401476860046387\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.44793954491615295\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.3964780569076538\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9287071228027344\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4293813705444336\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4944758415222168\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.400224506855011\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6548662781715393\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4040919542312622\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1982499361038208\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.764290452003479\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6448008418083191\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.229644536972046\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5034639835357666\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7340461015701294\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6743256449699402\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6154863834381104\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9786117672920227\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9326823353767395\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.084015965461731\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8978285789489746\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5490273237228394\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.3875563144683838\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7812208533287048\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6503602266311646\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1673493385314941\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5492271184921265\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8830272555351257\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5465624332427979\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2095041275024414\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9526968002319336\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.741216778755188\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2041683197021484\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.362602561712265\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8845462799072266\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7575890421867371\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0675756931304932\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.5337493419647217\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8530877828598022\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.21131575107574463\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8154996633529663\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.334611177444458\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0168170928955078\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.163464903831482\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8910343050956726\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.90489661693573\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7487941980361938\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4568307399749756\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.317371129989624\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6305375099182129\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5695048570632935\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8635719418525696\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7462315559387207\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8226891756057739\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5675550699234009\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2999171316623688\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.043426752090454\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.024554967880249\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7352371215820312\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4390337467193604\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5346826314926147\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4741318225860596\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7588261961936951\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8508687019348145\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3022160232067108\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7972490787506104\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7435654401779175\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8934499621391296\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9835186004638672\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.6084661483764648\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.855241596698761\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2556037902832031\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8176941871643066\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2734076678752899\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.38925492763519287\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9947880506515503\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2798517346382141\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6703335046768188\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0624160766601562\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8957670331001282\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6363506317138672\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.45637941360473633\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0167988538742065\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.522438645362854\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4305551052093506\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0584889650344849\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6270517110824585\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.43209171295166016\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2468489408493042\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8995102643966675\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1571905612945557\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6127537488937378\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5891226530075073\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3491991460323334\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1398735046386719\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5365657806396484\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2639046609401703\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6209295392036438\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7907155752182007\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6780142784118652\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.6285021305084229\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0872790813446045\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0357065200805664\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8619267344474792\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.6903616189956665\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.44556474685668945\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8347668647766113\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.49776801466941833\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5123392343521118\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6870003938674927\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.753280758857727\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1627655029296875\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.579830527305603\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5012811422348022\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8629649877548218\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1037304401397705\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.48271042108535767\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2416323870420456\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7497590780258179\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.21048104763031\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6525905728340149\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5026901364326477\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.49815067648887634\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7700098156929016\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7579312920570374\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.311855435371399\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.720994770526886\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4498388171195984\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.273449420928955\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0286552906036377\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0018891096115112\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.034618616104126\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0734201669692993\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5489518642425537\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9490172266960144\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4571792185306549\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7415177822113037\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9007806777954102\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.891856849193573\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.399590402841568\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6799910664558411\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6983045339584351\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4704338014125824\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4530316889286041\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3401614725589752\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0800248384475708\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7418848276138306\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4805751442909241\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0719926357269287\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8212272524833679\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5522814393043518\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9486926198005676\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1430940628051758\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4560277462005615\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9528031349182129\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0295565128326416\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9046360850334167\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1063240766525269\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.043729543685913\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.734546422958374\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7258633971214294\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3883017897605896\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4621579647064209\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5631368160247803\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6105697751045227\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9117363691329956\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1348613500595093\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.5036897659301758\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0528719425201416\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.40577974915504456\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7368844747543335\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.48780784010887146\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6654853820800781\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5000728368759155\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5302039384841919\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6257218718528748\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7602575421333313\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8159067034721375\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.389861822128296\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9580931663513184\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.49464669823646545\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5406604409217834\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7497000694274902\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.938892662525177\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5663012266159058\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6235870718955994\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5564602613449097\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9150993227958679\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4450883865356445\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5422238111495972\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5529656410217285\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0600056648254395\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2215569019317627\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4656639099121094\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7082825303077698\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.049132227897644\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1685378551483154\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1766306161880493\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9535520672798157\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9690760374069214\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.908011257648468\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6518787145614624\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7419278025627136\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.165303349494934\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.238515019416809\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6357395052909851\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8810602426528931\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6060119271278381\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8655808568000793\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5829785466194153\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.40879303216934204\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.30600705742836\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.259878158569336\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9186221361160278\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.254689484834671\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.818304181098938\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3257579803466797\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3689870834350586\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5435227155685425\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6435825228691101\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.940880298614502\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8537432551383972\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2899634838104248\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7864688634872437\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.219948649406433\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0383127927780151\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.79634028673172\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.35234004259109497\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6236242055892944\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.45152682065963745\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5737555027008057\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2549316883087158\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7939597964286804\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.44083818793296814\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9522851705551147\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7925666570663452\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.5059642791748047\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6304775476455688\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7087777853012085\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9891059994697571\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8995330929756165\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9530295133590698\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.23707687854766846\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5967267751693726\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.1776236742734909\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4253705739974976\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9443747401237488\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6066902875900269\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4990761876106262\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9715850949287415\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9761857986450195\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.46700987219810486\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8592890501022339\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5530516505241394\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7116178870201111\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6599297523498535\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.978756308555603\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4559723138809204\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.721023678779602\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.561477541923523\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5860936641693115\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.48737573623657227\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8333219289779663\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6772375106811523\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.29528114199638367\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4946824014186859\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8177139163017273\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.45414528250694275\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6206184029579163\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.920340359210968\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8576154708862305\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.36447781324386597\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4493650496006012\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6712568998336792\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5199145078659058\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7992440462112427\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7529635429382324\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7652021646499634\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5400312542915344\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4262651205062866\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.42673611640930176\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2244153767824173\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.586736798286438\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0502612590789795\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2545032799243927\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2566081285476685\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1088579893112183\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4469708800315857\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6685680150985718\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2988557815551758\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.42248234152793884\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0310442447662354\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5424414873123169\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3268962502479553\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.41971293091773987\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.456533819437027\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0134732723236084\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6779102087020874\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5684795379638672\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4619031846523285\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.700812578201294\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.730731189250946\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6374763250350952\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.8079897165298462\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7582178115844727\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.291639804840088\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3997127115726471\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9439404606819153\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6693755388259888\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4973059594631195\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.356999933719635\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7253875136375427\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8810194730758667\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2614845037460327\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2289178371429443\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.408543199300766\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4003877639770508\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5918134450912476\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9567184448242188\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6344185471534729\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.46689900755882263\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3634904623031616\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.49982619285583496\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5180662274360657\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.48351946473121643\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6675016283988953\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.730776309967041\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8214290738105774\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6307635307312012\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.31433776021003723\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.8733301162719727\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7327796220779419\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5366925597190857\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9873870015144348\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7972428202629089\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.36179226636886597\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9202958345413208\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9761309623718262\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9706419110298157\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6692256927490234\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8742380142211914\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.14746108651161194\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.998182475566864\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0373384952545166\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3896868824958801\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3797362446784973\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.53105628490448\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1049768924713135\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8518416285514832\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7186427712440491\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.39640191197395325\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8403179049491882\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3122968077659607\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9274663925170898\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7401518821716309\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8754352331161499\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5447078943252563\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7643533945083618\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0962344408035278\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4282076358795166\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3139949440956116\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8829754590988159\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5745552182197571\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5353369116783142\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7505242228507996\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.308685541152954\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4246944785118103\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4700320363044739\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.48499202728271484\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5947331190109253\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4720833897590637\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5157237648963928\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.470162957906723\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.6972663402557373\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.169446587562561\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7663125991821289\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4945755898952484\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4738384187221527\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.32752758264541626\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.43279391527175903\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6717013120651245\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9218109250068665\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6499069929122925\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.774545431137085\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0592893362045288\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.699486494064331\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.28991609811782837\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5212212800979614\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4443179666996002\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1452975273132324\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.39852291345596313\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5755517482757568\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.069602370262146\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0208303928375244\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.46849504113197327\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8696101903915405\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3309476375579834\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9441106915473938\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9357656240463257\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1366360187530518\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5215038061141968\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9985995292663574\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7065132856369019\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.210052251815796\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.37673020362854\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6189479827880859\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9237591028213501\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2407281398773193\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2740277647972107\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.44636034965515137\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9234116673469543\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6005136966705322\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6334501504898071\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5579533576965332\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5021544694900513\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.854320228099823\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8926353454589844\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5683653354644775\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9203543663024902\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6412383913993835\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9667760729789734\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.21743814647197723\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2052308320999146\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4722369611263275\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8142490386962891\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5565084218978882\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7656330466270447\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.607663631439209\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5669881105422974\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.23381046950817108\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.18267947435379028\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.226064920425415\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1144649982452393\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.509479284286499\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2820419371128082\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7236689329147339\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9591693878173828\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.836466908454895\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.47718220949172974\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.321850448846817\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8143555521965027\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6746194958686829\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1643439531326294\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.1558072417974472\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5993514657020569\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5833286046981812\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3580191731452942\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4867216944694519\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0794923305511475\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5314744114875793\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8115967512130737\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5539885759353638\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.34858036041259766\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9252978563308716\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.45150595903396606\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7107765674591064\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.47313252091407776\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6509560346603394\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.763563871383667\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0388227701187134\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5483134388923645\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6689183115959167\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.591375708580017\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.722699761390686\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5996810793876648\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4522250294685364\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5852845311164856\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4844815731048584\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8840319514274597\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6425830721855164\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5969546437263489\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0218093395233154\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0399730205535889\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.044161081314087\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0567289590835571\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6989996433258057\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6971579194068909\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.27909180521965027\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6093946695327759\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.20750796794891357\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5569921135902405\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5221778154373169\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.391778826713562\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6546900868415833\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.303506463766098\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9187625646591187\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3270733952522278\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.38331523537635803\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0936554670333862\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8024320602416992\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5529798865318298\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.38319042325019836\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8035988807678223\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4871346354484558\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5944925546646118\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.863093376159668\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.497063398361206\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5445171594619751\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5507420301437378\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6039719581604004\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3840488791465759\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5855404138565063\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9945186376571655\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6240091323852539\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0937144756317139\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8104745149612427\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9880197644233704\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.31046563386917114\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3193361759185791\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.22234702110290527\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6651269793510437\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.16811002790927887\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5377350449562073\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2807364463806152\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8132864832878113\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.10943100601434708\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4029616117477417\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4991745352745056\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3842194974422455\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4993146061897278\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6938549280166626\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.12062563002109528\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8446639776229858\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7730199694633484\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5597454905509949\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.0969277024269104\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7811844348907471\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4499943256378174\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6536169052124023\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5893500447273254\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5310107469558716\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3520551323890686\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7179120182991028\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4451095163822174\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.49531111121177673\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9603055715560913\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.20674602687358856\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3758031725883484\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5195836424827576\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7472203969955444\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7515604496002197\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0340138673782349\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1896820068359375\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8222304582595825\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7415155172348022\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.516306459903717\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6667037606239319\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4808301031589508\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5843924283981323\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7643530368804932\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5719950199127197\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0819553136825562\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.923902690410614\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3833830654621124\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.16598322987556458\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8814549446105957\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5353034734725952\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7111490964889526\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8930636644363403\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4945586323738098\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2559519410133362\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6780365109443665\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.541227400302887\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.44856828451156616\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3312003016471863\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.30346769094467163\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3738974928855896\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9454129338264465\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8175085783004761\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9633558392524719\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.789056122303009\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6683667302131653\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.08391273021698\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5485206842422485\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4185398519039154\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7880872488021851\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1255848407745361\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.31618478894233704\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.27560314536094666\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8802461624145508\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6280568838119507\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.31704044342041016\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5625113248825073\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.32493841648101807\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.591899037361145\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6191031336784363\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.3464338779449463\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5176588892936707\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8964262008666992\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.46611738204956055\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6594528555870056\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.38106444478034973\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.16518254578113556\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7856554985046387\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6175894141197205\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3299408555030823\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6160686612129211\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3721281886100769\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.37660926580429077\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.45389074087142944\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5581178069114685\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5020020604133606\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.532004475593567\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5475854277610779\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9118024706840515\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5082064867019653\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.661189079284668\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3706361651420593\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5418719053268433\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.45263442397117615\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.43160027265548706\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8726578950881958\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8754042387008667\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4229381084442139\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.725399374961853\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.32283109426498413\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.18605487048625946\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.589924156665802\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.45861372351646423\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.415802001953125\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2857764959335327\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5553827881813049\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.1219441145658493\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.38675829768180847\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.15368445217609406\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1269569396972656\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3779222071170807\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.809599757194519\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4807012677192688\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7973144054412842\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3351472020149231\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2107255458831787\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6935175657272339\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8944453001022339\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9324116706848145\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9322229623794556\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.588208794593811\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3663535416126251\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5693646669387817\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6374915838241577\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0263031721115112\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2643340528011322\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.291027545928955\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6596980690956116\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8983871340751648\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9973651170730591\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4787512719631195\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.41786623001098633\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5900927186012268\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4496050775051117\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.192314863204956\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.733590841293335\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9873678088188171\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8453286290168762\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2650141716003418\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.79301518201828\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.14812913537025452\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3973846137523651\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.868281364440918\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8193802833557129\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8541287183761597\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2820283770561218\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5555464029312134\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5269271731376648\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.3115206956863403\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5597141981124878\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6431191563606262\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2746244668960571\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5573058128356934\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.49382027983665466\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3180597722530365\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6115123629570007\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8413252830505371\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6242806315422058\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.19563418626785278\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5194505453109741\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5893558263778687\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.48265376687049866\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.426032692193985\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3923627436161041\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5152896642684937\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7547458410263062\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3488917648792267\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0358160734176636\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.3193318843841553\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.19387027621269226\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5172775983810425\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4128230810165405\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.3118200302124023\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9629192352294922\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9961862564086914\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5467601418495178\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.43248075246810913\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2241235226392746\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.27037352323532104\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.39626333117485046\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2301192283630371\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5974247455596924\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1528085470199585\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7706993818283081\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5516456961631775\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7471241354942322\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1546818017959595\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8140014410018921\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6938985586166382\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8011201620101929\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6566814184188843\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3499520421028137\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.43820270895957947\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6652326583862305\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6238992810249329\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3428296148777008\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6628527641296387\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.610322117805481\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7506480813026428\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0068600177764893\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6165105700492859\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.34484314918518066\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.316842257976532\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5920791029930115\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5169770121574402\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.21517567336559296\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7522836923599243\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.36341509222984314\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.719159722328186\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4432404041290283\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7697175145149231\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.15875399112701416\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.6266920566558838\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.23236587643623352\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.07251422107219696\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.23193450272083282\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7870271801948547\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7617512941360474\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2212003469467163\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.34837833046913147\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8698738217353821\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4500318169593811\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8767801523208618\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.583321213722229\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.41566792130470276\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8178278207778931\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9104909896850586\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5724477171897888\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5555489659309387\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.330480694770813\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.5994210243225098\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.400679349899292\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6188820600509644\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0200519561767578\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.1269436776638031\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.41881901025772095\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0164825916290283\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6655095815658569\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7762905359268188\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2674741744995117\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.34583795070648193\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8144800066947937\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6713412404060364\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7677648067474365\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.693071722984314\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.40711426734924316\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7103587985038757\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8998964428901672\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.1053531169891357\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0599331855773926\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.35678377747535706\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.20743367075920105\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8094668388366699\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.10450209677219391\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.32000288367271423\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.31366226077079773\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.21485920250415802\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2576361298561096\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6588408946990967\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8939476013183594\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9851663708686829\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.42837706208229065\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.681017279624939\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5524986386299133\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9052640795707703\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7812560796737671\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.29861897230148315\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.21717879176139832\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.38394981622695923\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5827987790107727\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.462874174118042\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.687475860118866\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5606183409690857\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5631300210952759\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3090953826904297\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8596498370170593\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.3931005001068115\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9240862131118774\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.48542699217796326\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4357369542121887\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0142323970794678\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8074242472648621\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0624876022338867\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3361406624317169\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.36746740341186523\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8393542170524597\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6170657277107239\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.36889609694480896\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0149742364883423\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2073705643415451\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0743160247802734\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3452621102333069\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6182336211204529\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.35366106033325195\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6667119860649109\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6985947489738464\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6001237034797668\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7930500507354736\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.23449595272541046\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.23576727509498596\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2746952474117279\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7308512926101685\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6861001253128052\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.429328978061676\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8328436613082886\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3386766016483307\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.17160002887248993\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2561492323875427\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8546099662780762\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2087602615356445\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2802619934082031\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.26459118723869324\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.295235276222229\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4073828160762787\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8839006423950195\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5047510862350464\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4329870343208313\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4145700931549072\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4044317305088043\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5118858814239502\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.4038519263267517\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7358403205871582\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8686337471008301\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6704308390617371\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.34177571535110474\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8480837941169739\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.3550760746002197\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.38109904527664185\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8654744029045105\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.1640007495880127\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9848535656929016\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8729785680770874\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6672987341880798\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2627026438713074\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2815773487091064\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.34808072447776794\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.514835000038147\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7670866250991821\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9659241437911987\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3527647852897644\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6580389142036438\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.654032826423645\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9062610864639282\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8630844950675964\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.2081964015960693\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7180591821670532\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.20214033126831055\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7079119682312012\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0418040752410889\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.1557975858449936\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.9176150560379028\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5600460767745972\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6822589039802551\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.2333553582429886\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.40022778511047363\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.644103467464447\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7181699872016907\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6644114255905151\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7555739283561707\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.36665114760398865\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.435706228017807\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.5480362176895142\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.38220611214637756\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8728442192077637\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.8206315040588379\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3409115672111511\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.6681713461875916\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.0608118772506714\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.4767439365386963\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.3597763180732727\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.7095452547073364\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 1.3745276927947998\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 0] Current loss: 0.0\n",
+            "\u001b[0m"
+          ]
+        },
+        {
+          "data": {
+            "application/vnd.jupyter.widget-view+json": {
+              "model_id": "e3c817ea61c0456898dafbe436675a19",
+              "version_major": 2,
+              "version_minor": 0
+            },
+            "text/plain": [
+              "Iteration:   0%|          | 0/892 [00:00<?, ?it/s]"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "\u001b[1;3;34m> [Epoch 1] Current loss: 1.0316441059112549\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9674192667007446\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9151577949523926\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.27198293805122375\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.29684069752693176\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1955819129943848\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6276596188545227\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.20209062099456787\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.2147716283798218\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2806827127933502\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4517034888267517\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.3200963735580444\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9926549792289734\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.539482057094574\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5028634071350098\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.2258899211883545\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.36430853605270386\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.41147369146347046\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5218351483345032\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4308963418006897\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6535804271697998\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6963011026382446\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9644440412521362\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5502710342407227\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3664945960044861\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.307079792022705\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6729812622070312\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6234843134880066\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7578686475753784\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3781713545322418\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7738128900527954\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.33760103583335876\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9037502408027649\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7422286868095398\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.38257619738578796\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0682368278503418\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.22403207421302795\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5912734270095825\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5806069374084473\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9720719456672668\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.399533987045288\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.713485598564148\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.10054327547550201\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.746392548084259\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1300690174102783\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7664757966995239\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9244223833084106\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8076906204223633\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6366703510284424\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6160528063774109\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.20535023510456085\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1885567903518677\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3842800259590149\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6516439914703369\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.635150134563446\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5633819103240967\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7218374013900757\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4383440613746643\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.10871906578540802\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8776147961616516\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.871791660785675\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6421437859535217\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.3449665307998657\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3903026580810547\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1792973279953003\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7563822269439697\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5811230540275574\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.10662280023097992\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4609517455101013\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4058631360530853\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6726959943771362\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9538784027099609\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0450694561004639\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5983946323394775\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.900189995765686\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6358808279037476\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.11369069665670395\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.196960911154747\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8308110237121582\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.18907204270362854\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5001832246780396\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9443808794021606\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5790921449661255\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4632874131202698\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.32783088088035583\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7687095403671265\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4333934783935547\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1811972856521606\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9984828233718872\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4296693801879883\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.35480251908302307\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8868905305862427\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8115571141242981\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.882696807384491\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5226954221725464\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3369199335575104\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.0877305120229721\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8433453440666199\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.42666706442832947\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.11356604099273682\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.46746826171875\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6362219452857971\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4618569016456604\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.4943586587905884\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9861983060836792\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9021025896072388\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7198148965835571\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.4033013582229614\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.31483492255210876\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8020951151847839\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2974599003791809\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2729932367801666\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.46182769536972046\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7157434225082397\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0225250720977783\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4140934944152832\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.41041937470436096\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5377541780471802\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9328367114067078\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3154369294643402\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.13335558772087097\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4549012780189514\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9916417002677917\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5157998204231262\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3212047219276428\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3103780746459961\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7111392021179199\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5777910947799683\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0058540105819702\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5781736969947815\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2324540913105011\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0848023891448975\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8508531451225281\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8222706913948059\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9012084007263184\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0403451919555664\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.39738455414772034\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6728881597518921\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3739578425884247\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5899878740310669\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.524836540222168\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6817453503608704\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.19248203933238983\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4030659794807434\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4451529383659363\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4122057855129242\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2455657422542572\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.1472478210926056\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8533232808113098\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.48847150802612305\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3433310389518738\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8597183227539062\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6397424936294556\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.39492395520210266\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7798044681549072\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0218257904052734\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.24783095717430115\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7432832717895508\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9254280924797058\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7124679684638977\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9407333135604858\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8430343866348267\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6810030937194824\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5551513433456421\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.24969355762004852\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3264215290546417\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4548342823982239\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4352068305015564\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.794334888458252\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0053342580795288\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.4013084173202515\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9708837270736694\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2256893664598465\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6192845106124878\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.39845210313796997\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.44687241315841675\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3198944628238678\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4212319254875183\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4936474859714508\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6028770208358765\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.663640558719635\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.333927869796753\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8091253042221069\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3285607695579529\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.38854318857192993\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6428887248039246\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.598563551902771\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.36828479170799255\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.43242186307907104\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4422251284122467\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5424360036849976\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.2297934293746948\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.43276247382164\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3252118229866028\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9364555478096008\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1028534173965454\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.31720811128616333\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5034605264663696\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8842613101005554\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9849981069564819\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0956075191497803\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8569531440734863\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.714077889919281\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7897613048553467\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.44881048798561096\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5397692918777466\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9574443697929382\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1277202367782593\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.532397985458374\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.744533360004425\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.42537277936935425\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7047160863876343\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3698130249977112\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.24891170859336853\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.21626517176628113\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1653249263763428\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.799798846244812\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.16990183293819427\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.681280255317688\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.34763067960739136\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2581799328327179\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3668173849582672\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4530579149723053\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7297843098640442\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8511874079704285\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.058087706565857\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7144336104393005\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1279792785644531\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8954153060913086\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.701806902885437\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.26661691069602966\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.43972715735435486\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3769923150539398\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4267981946468353\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.12330583482980728\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6591717600822449\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.25743958353996277\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7216693162918091\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6193684935569763\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.3594584465026855\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5519589185714722\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5376901030540466\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8866264224052429\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7634109258651733\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8416412472724915\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.14193834364414215\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.47483760118484497\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.0944913923740387\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.25202476978302\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.817936897277832\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.42257171869277954\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3071710467338562\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8789806365966797\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.711893618106842\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3719698190689087\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5848435163497925\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3624515235424042\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.637520968914032\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4599713683128357\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8941878080368042\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.3237720727920532\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5329040884971619\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5092231631278992\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.47887372970581055\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3803052604198456\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6564062833786011\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5838273763656616\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.18578851222991943\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3723192512989044\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.697498619556427\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.40110301971435547\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5316736102104187\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7643936276435852\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7692715525627136\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.24603280425071716\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.36736419796943665\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5352928042411804\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4262351989746094\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.643977701663971\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6346887350082397\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6474141478538513\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4579986035823822\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.389432668685913\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.34710901975631714\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.12201714515686035\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.388098955154419\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9893554449081421\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.1511714607477188\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.2261329889297485\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9274479150772095\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.254150927066803\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6057888269424438\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1850051879882812\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.326945960521698\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8583537936210632\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4385455548763275\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.23351871967315674\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.30269601941108704\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.32150721549987793\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.894398033618927\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4801427721977234\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.40418267250061035\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4164174199104309\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.562174379825592\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5580481290817261\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5638153553009033\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.612691879272461\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5945937633514404\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1097296476364136\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.28091201186180115\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7259707450866699\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5109994411468506\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3827299177646637\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2586829960346222\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.584875762462616\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7652763724327087\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.1804589182138443\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9858702421188354\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.39952048659324646\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.4175093173980713\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4476102292537689\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9018875360488892\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5502542853355408\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.35502704977989197\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.27725502848625183\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.39003005623817444\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4117296636104584\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.42274942994117737\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3968103229999542\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6382723450660706\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7097622156143188\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5440627336502075\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.18546125292778015\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.8157050609588623\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6230961680412292\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4596315026283264\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9000623822212219\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.748869776725769\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2305462807416916\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8630072474479675\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8969904184341431\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9004312753677368\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5476467609405518\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6967941522598267\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.08229409158229828\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8794270753860474\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9459322094917297\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2628784477710724\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3114493191242218\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4715866446495056\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9308165311813354\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7018381357192993\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5634402632713318\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2905440330505371\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7194246053695679\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.21933133900165558\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8219102621078491\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6594659090042114\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7237578630447388\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.42805081605911255\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6528264284133911\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9203751683235168\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.31694716215133667\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2046201527118683\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7560026049613953\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.414508581161499\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.39658766984939575\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7466791868209839\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1694231033325195\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2881415784358978\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3653802275657654\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3586781919002533\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.47405344247817993\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3510412275791168\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.43687400221824646\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.32180142402648926\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.564708948135376\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0715014934539795\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6856183409690857\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3630639910697937\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3424263298511505\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2833022475242615\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3321757912635803\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5375088453292847\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9241777658462524\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5284923911094666\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6529611349105835\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.010920763015747\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4902827739715576\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2079680860042572\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.45809030532836914\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3597211539745331\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0511023998260498\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.32867830991744995\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5149017572402954\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0179822444915771\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8876876831054688\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3692387044429779\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7289718985557556\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2748594880104065\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8301830291748047\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8599624633789062\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.117677092552185\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4241623878479004\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9192094802856445\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.617241621017456\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.093696117401123\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.3215574026107788\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.48047390580177307\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.869714081287384\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.2139770984649658\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.17233717441558838\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3620559871196747\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8216296434402466\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4558330178260803\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5342925786972046\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.463481605052948\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.36772793531417847\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7677474617958069\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7802424430847168\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.45180147886276245\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8522955775260925\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5410407185554504\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9332214593887329\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.14963248372077942\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0608056783676147\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4309317469596863\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7226675152778625\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.45032936334609985\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6622468829154968\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5670055747032166\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4442763328552246\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.15350529551506042\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.116366907954216\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1915018558502197\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9960911870002747\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.462973415851593\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.17874079942703247\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6618425846099854\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.830583393573761\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8034427762031555\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3987031877040863\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.23921413719654083\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7238019704818726\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6295786499977112\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.109302043914795\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.09973497688770294\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5434783101081848\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5610625147819519\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.27649831771850586\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3875977396965027\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0116946697235107\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4828921854496002\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6769505739212036\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.45806264877319336\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.23874029517173767\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8960731625556946\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3478643000125885\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6567783951759338\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4363250732421875\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5781033039093018\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6978379487991333\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9462133646011353\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.38288068771362305\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5402261018753052\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.5300413370132446\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6468068361282349\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.49964314699172974\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.39766567945480347\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.47334298491477966\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4014645218849182\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7999290823936462\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5350527167320251\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5732935667037964\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9582298398017883\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0010038614273071\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9028741121292114\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9853053092956543\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5983830094337463\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6192678213119507\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.18543817102909088\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5223942399024963\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.18926092982292175\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5328329801559448\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.45957961678504944\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3205704092979431\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5495873689651489\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.27227747440338135\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8774644732475281\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2693784236907959\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.27275586128234863\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0099576711654663\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6404201984405518\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5169190764427185\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.29122525453567505\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7211357355117798\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.37411385774612427\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5145820379257202\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.806534469127655\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.3859124183654785\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.45294928550720215\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.43770503997802734\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5139846205711365\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3144128918647766\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5171456933021545\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9296926259994507\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5395800471305847\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.066176176071167\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6742824912071228\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9099605679512024\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2741292417049408\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.22269999980926514\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.122303806245327\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5963033437728882\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.12303180992603302\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4960533678531647\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.2203128337860107\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7519341707229614\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.06949365139007568\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.371307373046875\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.44921374320983887\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3219274878501892\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4610837399959564\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6304925680160522\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.07602771371603012\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7275603413581848\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6450814604759216\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4975648522377014\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.07364913821220398\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7151793241500854\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.39439016580581665\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5764346122741699\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5194821357727051\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4955548346042633\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.30678078532218933\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5935832262039185\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3762891888618469\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.38628843426704407\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8824838399887085\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.14973512291908264\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3019319176673889\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.472689688205719\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6882864236831665\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6506119966506958\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9833782315254211\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0920284986495972\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7743032574653625\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5957948565483093\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4704458713531494\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6041201949119568\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4208011031150818\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5092365145683289\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7202826738357544\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5252314209938049\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.040958046913147\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9011915326118469\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3301081955432892\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.11585402488708496\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7683641910552979\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.41774997115135193\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6695249676704407\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.820937991142273\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.42855167388916016\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.16892990469932556\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6210666298866272\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4875754415988922\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3650580048561096\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2873910963535309\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2426530420780182\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3184627592563629\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8699131011962891\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7435359954833984\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9377996325492859\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6889961957931519\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5622069239616394\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0141475200653076\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5222089886665344\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3345128893852234\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6842151284217834\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1162880659103394\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2860979437828064\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.23226241767406464\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.802322506904602\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5480754375457764\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.28360360860824585\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5108619928359985\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2901518642902374\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5292728543281555\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5930256247520447\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.329682469367981\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4516727328300476\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8265607953071594\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.43058663606643677\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6120604276657104\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3056958019733429\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.11362520605325699\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7184881567955017\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5340360403060913\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.26717180013656616\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5421828031539917\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.32875704765319824\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3313360810279846\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3962869346141815\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.48873716592788696\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4045414328575134\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.4836128950119019\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4720110297203064\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8581844568252563\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4590500295162201\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5812928080558777\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3016548752784729\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4895384907722473\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3685556948184967\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.36657655239105225\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8286280632019043\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8255589604377747\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.3814153671264648\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.659164547920227\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.269178569316864\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.12250974029302597\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5039529800415039\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.36657851934432983\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.34296074509620667\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2168288230895996\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4933181703090668\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.09829780459403992\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.33952686190605164\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.12093373388051987\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1103781461715698\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3299165368080139\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7626181244850159\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4193941652774811\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.704915463924408\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.24582064151763916\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1245241165161133\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6591411828994751\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8188349604606628\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8889755010604858\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8808355331420898\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5156434178352356\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.28680211305618286\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5355910658836365\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6111354231834412\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9527393579483032\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.19147442281246185\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.2097947597503662\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5340811610221863\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8374941945075989\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9684858322143555\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.39324507117271423\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3631642460823059\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.521700382232666\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3932870328426361\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0783605575561523\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6849791407585144\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9058488607406616\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8299660682678223\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.21347804367542267\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6953077912330627\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.10843553394079208\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3362831175327301\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8803009986877441\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7602874040603638\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8365427851676941\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2590992748737335\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5131534337997437\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4902663826942444\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.2413769960403442\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4997800290584564\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5415701270103455\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.218851089477539\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.49852338433265686\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4452537000179291\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.25797656178474426\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.53743577003479\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7962325811386108\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5636298656463623\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.15640197694301605\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.45115548372268677\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.543043315410614\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.42020517587661743\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.37160414457321167\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.33160600066185\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.44965505599975586\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7254192233085632\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.29546672105789185\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9200876951217651\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.2912590503692627\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.15741096436977386\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4457557797431946\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.3728662729263306\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.2749148607254028\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8727973103523254\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9272635579109192\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.46391767263412476\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.39103513956069946\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.15429097414016724\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.23752078413963318\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.35662102699279785\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.19316701591014862\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.538925051689148\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0940639972686768\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7345141172409058\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.48290127515792847\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7076364159584045\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1132993698120117\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7504252195358276\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6005457639694214\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7882511615753174\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.641342282295227\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.286693811416626\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.38470131158828735\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6068949103355408\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5825878381729126\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.30332475900650024\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5745834112167358\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5753259658813477\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7300834059715271\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9690524935722351\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5694550275802612\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3150884509086609\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.27707651257514954\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5503836870193481\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.457122802734375\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.1593097597360611\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6754880547523499\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.36714819073677063\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6749690771102905\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.3567335605621338\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7570483684539795\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.14206968247890472\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.5623811483383179\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.20195086300373077\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.052363622933626175\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.1887689083814621\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7275243997573853\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7308861017227173\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1880782842636108\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.31475740671157837\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8303731679916382\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.41609376668930054\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8120074272155762\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5476750135421753\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3840315341949463\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7940429449081421\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.84857577085495\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5341698527336121\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5136061310768127\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.30431100726127625\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.5772178173065186\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3530595898628235\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5764427781105042\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9872108697891235\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.09675242006778717\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.362461656332016\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9807437658309937\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5975340008735657\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7592388391494751\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2433420717716217\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3003523349761963\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7784306406974792\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6132789850234985\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7139512300491333\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6460822820663452\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.36187225580215454\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.646933913230896\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9114141464233398\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.076592206954956\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0349524021148682\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3102310299873352\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.18528994917869568\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8076218366622925\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.07943816483020782\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2915002405643463\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.27606549859046936\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.15745969116687775\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.243329718708992\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.611862063407898\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8283163905143738\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9362762570381165\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.37165600061416626\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.6033796072006226\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5009823441505432\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.84453946352005\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7541886568069458\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.26490503549575806\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.18625599145889282\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.31068167090415955\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5295357704162598\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.3940842151641846\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6257697939872742\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.523142397403717\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.511459231376648\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.27016061544418335\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8170843124389648\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.3110010623931885\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8794683218002319\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.44792240858078003\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.41943874955177307\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9647241830825806\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7217757105827332\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0247989892959595\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.30790239572525024\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3219734728336334\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8093096017837524\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5566107034683228\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3342598080635071\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9847332239151001\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.17090573906898499\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0314929485321045\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3226064443588257\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.582430362701416\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.30162182450294495\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.634689211845398\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6642847657203674\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.552049458026886\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.76859050989151\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.19783049821853638\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.21265721321105957\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2368711531162262\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6953392028808594\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6379991769790649\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3801306486129761\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7874071598052979\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.31276264786720276\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.14630253612995148\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2314266711473465\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7518502473831177\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1772936582565308\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2570364475250244\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.21978752315044403\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2820161283016205\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3766135275363922\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8355828523635864\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4419933259487152\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4029410481452942\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.4128211736679077\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.38978132605552673\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4661563038825989\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.37369558215141296\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.67713463306427\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8154858350753784\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6348110437393188\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.29591408371925354\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8234394192695618\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.3019393682479858\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.36610108613967896\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.811869740486145\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.13849413394927979\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.95075523853302\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8338335752487183\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6129546761512756\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.2225479781627655\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.2439148426055908\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.31776702404022217\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5092067718505859\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7565910816192627\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.9311893582344055\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3285469114780426\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.623365044593811\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6217605471611023\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.882775604724884\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8068552017211914\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.1639070510864258\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6891547441482544\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.1958160698413849\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6878679990768433\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.004830241203308\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.14777623116970062\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8704832196235657\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.5259945392608643\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6374325752258301\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.19885116815567017\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.350452721118927\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6163203120231628\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.670238733291626\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6360015869140625\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7089076042175293\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3190380036830902\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.46258530020713806\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.4936365485191345\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3589979112148285\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.8185552358627319\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.7842639684677124\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.3248451352119446\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6132020950317383\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.0749304294586182\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.4263488054275513\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.34589922428131104\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.6781661510467529\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 1.3276325464248657\n",
+            "\u001b[0m\u001b[1;3;34m> [Epoch 1] Current loss: 0.0\n",
+            "\u001b[0m\u001b[1;3;34m> Finished training, saving to model_output_test\n",
+            "\u001b[0m"
+          ]
+        }
+      ],
+      "source": [
+        "# Initiate the Finetuning process\n",
+        "finetune_engine.finetune()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "JJOhEdlawqL7"
+      },
+      "outputs": [],
+      "source": [
+        "embed_model = finetune_engine.get_finetuned_model()\n",
+        "\n",
+        "# Or, import model from the directory whenever required.\n",
+        "# from llama_index.core.embeddings import LinearAdapterEmbeddingModel\n",
+        "# embed_model = LinearAdapterEmbeddingModel(base_embed_model, \"model_output_test\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "9hjc_5c5w9xm",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "49890ce8-21f0-4c58-8728-9913ad69f3d0"
+      },
+      "outputs": [
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "AdapterEmbeddingModel(model_name='Adapter for BAAI/bge-small-en-v1.5', embed_batch_size=10, callback_manager=<llama_index.core.callbacks.base.CallbackManager object at 0x782e56075c90>, num_workers=None, embeddings_cache=None)"
+            ]
+          },
+          "metadata": {},
+          "execution_count": 27
+        }
+      ],
+      "source": [
+        "embed_model"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Y7NEOeuLFa5z",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 118,
+          "referenced_widgets": [
+            "976cd4b4745a43e8984c8614802f799a",
+            "fbd6133d12504a18985823b34b10455c",
+            "326467e5a0704ac6a3b36deb74f0e362",
+            "d84a71b5d6414a54b6761d59734ec216",
+            "bb652c51c43549c9b90b81a0e0db19d2",
+            "785bda4e561f4010968625256b1375f8",
+            "570a98a6d7c84e68a87bc3f02ea08dc7",
+            "e37f3eb972e3464ea94939bd47ce4ac0",
+            "be66efab12324d6da49d8052710c7f17",
+            "3cb52b704de5496da4c67b7d696fc08a",
+            "62d5d2795f5c45abaf80528e193352a9"
+          ]
+        },
+        "outputId": "68717b7d-7ee9-4ced-e243-1c96e26782c1"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "pytorch_model.bin:   0%|          | 0.00/593k [00:00<?, ?B/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "976cd4b4745a43e8984c8614802f799a"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "execute_result",
+          "data": {
+            "text/plain": [
+              "CommitInfo(commit_url='https://huggingface.co/vicpada/finetuned_embed_model_full/commit/735fcb7f7aeea0841454d92e38d7f307f25878e4', commit_message='Upload folder using huggingface_hub', commit_description='', oid='735fcb7f7aeea0841454d92e38d7f307f25878e4', pr_url=None, repo_url=RepoUrl('https://huggingface.co/vicpada/finetuned_embed_model_full', endpoint='https://huggingface.co', repo_type='model', repo_id='vicpada/finetuned_embed_model_full'), pr_revision=None, pr_num=None)"
+            ],
+            "application/vnd.google.colaboratory.intrinsic+json": {
+              "type": "string"
+            }
+          },
+          "metadata": {},
+          "execution_count": 25
+        }
+      ],
+      "source": [
+        "# prompt: upload embed_model to hugging face\n",
+        "\n",
+        "repo_id = \"vicpada/finetuned_embed_model_full\"\n",
+        "\n",
+        "# Create a new repository\n",
+        "api.create_repo(repo_id=repo_id, repo_type=\"model\",exist_ok=True)\n",
+        "\n",
+        "# Upload the model files\n",
+        "api.upload_folder(\n",
+        "    folder_path=\"model_output_test\",\n",
+        "    repo_id=repo_id,\n",
+        "    repo_type=\"model\",\n",
+        "\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "slrZrRyKqhPI"
+      },
+      "source": [
+        "## Fine tuning OpenAI Embedding Model using Adapter method"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "sEMBr8iMqfzh"
+      },
+      "outputs": [],
+      "source": [
+        "from llama_index.finetuning import EmbeddingAdapterFinetuneEngine\n",
+        "from llama_index.embeddings.openai import OpenAIEmbedding\n",
+        "\n",
+        "openai_finetune_engine = EmbeddingAdapterFinetuneEngine(\n",
+        "    TRAIN_DATASET,\n",
+        "    OpenAIEmbedding(model=\"text-embedding-3-small\"),\n",
+        "    model_output_path=\"model_output_test_openai\",\n",
+        "    bias=True,\n",
+        "    epochs=2,\n",
+        "    verbose=True,\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "collapsed": true,
+        "id": "iqiJyY1Mqfgi"
+      },
+      "outputs": [],
+      "source": [
+        "openai_finetune_engine.finetune()\n",
+        "\n",
+        "openai_embed_model = openai_finetune_engine.get_finetuned_model()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "sFxmUjtjrTFB"
+      },
+      "outputs": [],
+      "source": [
+        "openai_embed_model"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "vrj0FrzhygGD"
+      },
+      "source": [
+        "# Evaluate\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "yEj5ZAEioCss"
+      },
+      "source": [
+        "## Define the Evaluation Functions\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Z_5jANKro1Hn"
+      },
+      "outputs": [],
+      "source": [
+        "from llama_index.core import VectorStoreIndex\n",
+        "from llama_index.core.schema import TextNode\n",
+        "from llama_index.core import Settings\n",
+        "from tqdm import tqdm\n",
+        "import pandas as pd\n",
+        "\n",
+        "def evaluate(dataset, embedding_model, top_k=5, verbose=False):\n",
+        "    corpus = dataset.corpus\n",
+        "    queries = dataset.queries\n",
+        "    relevant_docs = dataset.relevant_docs\n",
+        "\n",
+        "    Settings.embed_model = embedding_model\n",
+        "\n",
+        "    # Chunking the documents and generating embeddings\n",
+        "    nodes = [TextNode(id_=id_, text=text) for id_, text in corpus.items()]\n",
+        "    index = VectorStoreIndex(nodes, show_progress=True)\n",
+        "\n",
+        "    # Define a retriever to answer the questions\n",
+        "    retriever = index.as_retriever(similarity_top_k=top_k)\n",
+        "\n",
+        "    eval_results = []\n",
+        "\n",
+        "    # Look into each response sources to see if the chunk that contains the answer is retrieved.\n",
+        "    for query_id, query in tqdm(queries.items()):\n",
+        "        retrieved_nodes = retriever.retrieve(query)\n",
+        "        retrieved_ids = [node.node.node_id for node in retrieved_nodes]\n",
+        "        expected_id = relevant_docs[query_id][0]\n",
+        "\n",
+        "        try:\n",
+        "            rank = retrieved_ids.index(expected_id) + 1\n",
+        "            reciprocal_rank = 1 / rank\n",
+        "        except ValueError:\n",
+        "            rank = None\n",
+        "            reciprocal_rank = 0\n",
+        "\n",
+        "        is_hit = expected_id in retrieved_ids\n",
+        "\n",
+        "        eval_result = {\n",
+        "            \"is_hit\": is_hit,\n",
+        "            \"retrieved\": retrieved_ids,\n",
+        "            \"expected\": expected_id,\n",
+        "            \"query\": query_id,\n",
+        "            \"rank\": rank,\n",
+        "            \"reciprocal_rank\": reciprocal_rank\n",
+        "        }\n",
+        "        eval_results.append(eval_result)\n",
+        "\n",
+        "    return eval_results"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "dKsxY6Vvy7M3"
+      },
+      "source": [
+        "## OpenAI Embedding Model Evaluation\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "oqN3lRAjBrFA"
+      },
+      "outputs": [],
+      "source": [
+        "# Load the OpenAI Ada model and evaluate it.\n",
+        "openai_text_embedding_small = OpenAIEmbedding(model=\"text-embedding-3-small\")\n",
+        "openai_embedding_val_results = evaluate(VALIDATION_DATASET, embedding_model=openai_text_embedding_small)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "YE3ydaj5S4lf"
+      },
+      "outputs": [],
+      "source": [
+        "openai_embedding_val_results = [\n",
+        "    result for result in openai_embedding_val_results if isinstance(result, dict)\n",
+        "]\n",
+        "\n",
+        "df_openai = pd.DataFrame(openai_embedding_val_results)\n",
+        "\n",
+        "hit_rate_openai = df_openai[\"is_hit\"].mean()\n",
+        "mrr_openai = df_openai[\"reciprocal_rank\"].mean()\n",
+        "\n",
+        "print(f\"Hit rate: {hit_rate_openai}\")\n",
+        "print(f\"MRR: {mrr_openai}\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "YHiOXyFmsF_s"
+      },
+      "source": [
+        "### OpenAI Embedding Model with Fine Tuned Adapter Model Evaluation"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "xnaV6XqDC56H"
+      },
+      "outputs": [],
+      "source": [
+        "from llama_index.embeddings.adapter import AdapterEmbeddingModel\n",
+        "\n",
+        "openai_embed_model = AdapterEmbeddingModel(openai_text_embedding_small, \"model_output_test_openai\")\n",
+        "\n",
+        "val_results_ft_openai = evaluate(VALIDATION_DATASET, embedding_model = openai_embed_model)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "AlXUyAH9S_Fg"
+      },
+      "outputs": [],
+      "source": [
+        "val_results_ft_openai = [\n",
+        "    result for result in val_results_ft_openai if isinstance(result, dict)\n",
+        "]\n",
+        "\n",
+        "df_openai_ft = pd.DataFrame(val_results_ft_openai)\n",
+        "\n",
+        "hit_rate_openai_ft = df_openai_ft[\"is_hit\"].mean()\n",
+        "mrr_openai_ft = df_openai_ft[\"reciprocal_rank\"].mean()\n",
+        "\n",
+        "print(f\"Hit rate: {hit_rate_openai_ft}\")\n",
+        "print(f\"MRR: {mrr_openai_ft}\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "hBVSCKGQy81W"
+      },
+      "source": [
+        "## Open Source BAAI Model Evaluation\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "GfBu0PcFB-tm",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 66,
+          "referenced_widgets": [
+            "33769fd654b74795a6be0b9684bbf11e",
+            "5326928bdadb4bb28bdd82d2d919cee8",
+            "d4c53c38259e436bbda1a89e9828d802",
+            "3c2dbe96bf164d7a8ea9bfd94c9b841e",
+            "0c57b2f162d149a3b3168cc81900ec44",
+            "4ec2fda863e84fef91fce100597b6acd",
+            "545d9915bd264089862dbe35e3ef3132",
+            "8834bd8474344682b6daaf04a1de5ec1",
+            "c528e147c35b4f61a7998e0b3eb8f85a",
+            "c7fe134f61d6475d961701934b5f7c5c",
+            "2bdc34ddec854cc998cab0c414f62437"
+          ]
+        },
+        "outputId": "4abe31f5-9bc4-4157-ae77-d351a066ec23"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Generating embeddings:   0%|          | 0/1000 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "33769fd654b74795a6be0b9684bbf11e"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "100%|██████████| 1005/1005 [00:56<00:00, 17.76it/s]\n"
+          ]
+        }
+      ],
+      "source": [
+        "# Load the Base model without fine-tuning\n",
+        "base_embed_model = resolve_embed_model(\"local:BAAI/bge-small-en-v1.5\")\n",
+        "bge_val_results = evaluate(VALIDATION_DATASET, embedding_model=base_embed_model)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "5-LR8Hu0TC39",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "f7738865-3082-4fcc-9ec0-7eb00bcb4bb0"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Hit rate: 0.6567164179104478\n",
+            "MRR: 0.5616915422885572\n"
+          ]
+        }
+      ],
+      "source": [
+        "bge_val_results = [\n",
+        "    result for result in bge_val_results if isinstance(result, dict)\n",
+        "]\n",
+        "\n",
+        "df_bge = pd.DataFrame(bge_val_results)\n",
+        "\n",
+        "hit_rate_bge = df_bge[\"is_hit\"].mean()\n",
+        "mrr_bge = df_bge[\"reciprocal_rank\"].mean()\n",
+        "\n",
+        "print(f\"Hit rate: {hit_rate_bge}\")\n",
+        "print(f\"MRR: {mrr_bge}\")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "1awOq9cLzo7M"
+      },
+      "source": [
+        "## FineTuned BAAI Adapter Embedding Model Evaluation\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "aZWaDw9oTGXz",
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 66,
+          "referenced_widgets": [
+            "cadf93eec02846958247b8dee1892c66",
+            "128dc781f534482396c4eb04ac510d7e",
+            "945a92a122694d1383fa93f67372b745",
+            "ce0b0bedcb0b4085b2068487438164e6",
+            "27a8c4d6f55340b9aaea1152e0f1a247",
+            "ccec182b25b7416e98511e6b086c7380",
+            "2e973eadd3074a23a3211901dd110713",
+            "5902422b16ea430cb3f8d7f438b4683f",
+            "63c5c5097d8b49a28b77b54113c31cca",
+            "b998018ed1274b06a01c0a704478e5c9",
+            "ad8057bf850143f9a10f7e18e32eb8aa"
+          ]
+        },
+        "outputId": "6cfd708a-73bf-4460-8f44-55e0399240b0"
+      },
+      "outputs": [
+        {
+          "output_type": "display_data",
+          "data": {
+            "text/plain": [
+              "Generating embeddings:   0%|          | 0/1000 [00:00<?, ?it/s]"
+            ],
+            "application/vnd.jupyter.widget-view+json": {
+              "version_major": 2,
+              "version_minor": 0,
+              "model_id": "cadf93eec02846958247b8dee1892c66"
+            }
+          },
+          "metadata": {}
+        },
+        {
+          "output_type": "stream",
+          "name": "stderr",
+          "text": [
+            "100%|██████████| 1005/1005 [00:57<00:00, 17.57it/s]\n"
+          ]
+        }
+      ],
+      "source": [
+        "from llama_index.embeddings.adapter import AdapterEmbeddingModel\n",
+        "\n",
+        "# Load the Fine-tuned model.\n",
+        "embed_model = AdapterEmbeddingModel(base_embed_model, \"model_output_test\")\n",
+        "\n",
+        "val_results_finetuned = evaluate(VALIDATION_DATASET, embedding_model=embed_model)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "UJB6X40nTH2Y",
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "outputId": "1c1e4b43-5d1e-4742-efc6-f3e44d32856b"
+      },
+      "outputs": [
+        {
+          "output_type": "stream",
+          "name": "stdout",
+          "text": [
+            "Hit rate: 0.7074626865671642\n",
+            "MRR: 0.6007628524046434\n"
+          ]
+        }
+      ],
+      "source": [
+        "val_results_finetuned = [\n",
+        "    result for result in val_results_finetuned if isinstance(result, dict)\n",
+        "]\n",
+        "\n",
+        "df_finetuned = pd.DataFrame(val_results_finetuned)\n",
+        "\n",
+        "hit_rate_finetuned = df_finetuned[\"is_hit\"].mean()\n",
+        "mrr_finetuned = df_finetuned[\"reciprocal_rank\"].mean()\n",
+        "\n",
+        "print(f\"Hit rate: {hit_rate_finetuned}\")\n",
+        "print(f\"MRR: {mrr_finetuned}\")"
+      ]
+    },
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+  "nbformat_minor": 0
+}
\ No newline at end of file