diff --git "a/FineTuneSAM_SEG_ECHO.ipynb" "b/FineTuneSAM_SEG_ECHO.ipynb"
--- "a/FineTuneSAM_SEG_ECHO.ipynb"
+++ "b/FineTuneSAM_SEG_ECHO.ipynb"
@@ -1,14 +1,9563 @@
 {
  "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text",
+    "id": "view-in-github"
+   },
+   "source": [
+    "<a href=\"https://colab.research.google.com/github/unreal-kz/Notes/blob/master/FineTuneSAM_SEG_ECHO.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Collecting environment information...\n",
+      "PyTorch version: 2.1.2+cu121\n",
+      "Is debug build: False\n",
+      "CUDA used to build PyTorch: 12.1\n",
+      "ROCM used to build PyTorch: N/A\n",
+      "\n",
+      "OS: Microsoft Windows 11 Home\n",
+      "GCC version: Could not collect\n",
+      "Clang version: Could not collect\n",
+      "CMake version: Could not collect\n",
+      "Libc version: N/A\n",
+      "\n",
+      "Python version: 3.9.18 (main, Sep 11 2023, 14:09:26) [MSC v.1916 64 bit (AMD64)] (64-bit runtime)\n",
+      "Python platform: Windows-10-10.0.22621-SP0\n",
+      "Is CUDA available: True\n",
+      "CUDA runtime version: 12.3.107\n",
+      "\n",
+      "CUDA_MODULE_LOADING set to: LAZY\n",
+      "GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3080 Ti\n",
+      "Nvidia driver version: 551.23\n",
+      "cuDNN version: C:\\Program Files\\NVIDIA GPU Computing Toolkit\\CUDA\\v12.3\\bin\\cudnn_ops_train64_8.dll\n",
+      "HIP runtime version: N/A\n",
+      "MIOpen runtime version: N/A\n",
+      "Is XNNPACK available: True\n",
+      "\n",
+      "CPU:\n",
+      "Architecture=9\n",
+      "\n",
+      "\n",
+      "CurrentClockSpeed=3504\n",
+      "\n",
+      "\n",
+      "DeviceID=CPU0\n",
+      "\n",
+      "\n",
+      "Family=207\n",
+      "\n",
+      "\n",
+      "L2CacheSize=4096\n",
+      "\n",
+      "\n",
+      "L2CacheSpeed=\n",
+      "\n",
+      "\n",
+      "Manufacturer=GenuineIntel\n",
+      "\n",
+      "\n",
+      "MaxClockSpeed=3504\n",
+      "\n",
+      "\n",
+      "Name=11th Gen Intel(R) Core(TM) i9-11900KF @ 3.50GHz\n",
+      "\n",
+      "\n",
+      "ProcessorType=3\n",
+      "\n",
+      "\n",
+      "Revision=\n",
+      "\n",
+      "Versions of relevant libraries:\n",
+      "[pip3] numpy==1.26.3\n",
+      "[pip3] torch==2.1.2+cu121\n",
+      "[pip3] torchaudio==2.1.2\n",
+      "[pip3] torchvision==0.16.2\n",
+      "[conda] blas                      1.0                         mkl  \n",
+      "[conda] cudatoolkit               11.3.1               h59b6b97_2  \n",
+      "[conda] mkl                       2023.1.0         h6b88ed4_46358  \n",
+      "[conda] mkl-service               2.4.0            py39h2bbff1b_1  \n",
+      "[conda] mkl_fft                   1.3.8            py39h2bbff1b_0  \n",
+      "[conda] mkl_random                1.2.4            py39h59b6b97_0  \n",
+      "[conda] numpy                     1.26.3           py39h055cbcc_0  \n",
+      "[conda] numpy-base                1.26.3           py39h65a83cf_0  \n",
+      "[conda] pytorch-cuda              12.1                 hde6ce7c_5    pytorch\n",
+      "[conda] pytorch-mutex             1.0                         cpu    pytorch\n",
+      "[conda] torch                     2.1.2+cu121              pypi_0    pypi\n",
+      "[conda] torchaudio                2.1.2                  py39_cpu    pytorch\n",
+      "[conda] torchvision               0.16.2                 py39_cpu    pytorch\n"
+     ]
+    }
+   ],
+   "source": [
+    "!python -m torch.utils.collect_env"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import torch"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "a=torch.cuda.FloatTensor()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# !pip uninstall torch"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "iobAOGDyff7W",
+    "outputId": "b256e5a4-a406-46f5-fd61-0b46f61afc2a"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: accelerate in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (0.27.2)\n",
+      "Requirement already satisfied: numpy>=1.17 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from accelerate) (1.26.3)\n",
+      "Requirement already satisfied: packaging>=20.0 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from accelerate) (23.1)\n",
+      "Requirement already satisfied: psutil in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from accelerate) (5.9.0)\n",
+      "Requirement already satisfied: pyyaml in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from accelerate) (6.0.1)\n",
+      "Requirement already satisfied: torch>=1.10.0 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from accelerate) (2.1.2+cu121)\n",
+      "Requirement already satisfied: huggingface-hub in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from accelerate) (0.20.2)\n",
+      "Requirement already satisfied: safetensors>=0.3.1 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from accelerate) (0.4.1)\n",
+      "Requirement already satisfied: filelock in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from torch>=1.10.0->accelerate) (3.13.1)\n",
+      "Requirement already satisfied: typing-extensions in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from torch>=1.10.0->accelerate) (4.9.0)\n",
+      "Requirement already satisfied: sympy in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from torch>=1.10.0->accelerate) (1.12)\n",
+      "Requirement already satisfied: networkx in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from torch>=1.10.0->accelerate) (3.1)\n",
+      "Requirement already satisfied: jinja2 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from torch>=1.10.0->accelerate) (3.1.2)\n",
+      "Requirement already satisfied: fsspec in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from torch>=1.10.0->accelerate) (2023.10.0)\n",
+      "Requirement already satisfied: requests in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from huggingface-hub->accelerate) (2.31.0)\n",
+      "Requirement already satisfied: tqdm>=4.42.1 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from huggingface-hub->accelerate) (4.66.1)\n",
+      "Requirement already satisfied: colorama in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from tqdm>=4.42.1->huggingface-hub->accelerate) (0.4.6)\n",
+      "Requirement already satisfied: MarkupSafe>=2.0 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from jinja2->torch>=1.10.0->accelerate) (2.1.3)\n",
+      "Requirement already satisfied: charset-normalizer<4,>=2 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->huggingface-hub->accelerate) (2.0.4)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->huggingface-hub->accelerate) (3.4)\n",
+      "Requirement already satisfied: urllib3<3,>=1.21.1 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->huggingface-hub->accelerate) (2.1.0)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->huggingface-hub->accelerate) (2023.11.17)\n",
+      "Requirement already satisfied: mpmath>=0.19 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from sympy->torch>=1.10.0->accelerate) (1.3.0)\n",
+      "Requirement already satisfied: transformers in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (4.37.2)\n",
+      "Requirement already satisfied: filelock in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (3.13.1)\n",
+      "Requirement already satisfied: huggingface-hub<1.0,>=0.19.3 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (0.20.2)\n",
+      "Requirement already satisfied: numpy>=1.17 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (1.26.3)\n",
+      "Requirement already satisfied: packaging>=20.0 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (23.1)\n",
+      "Requirement already satisfied: pyyaml>=5.1 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (6.0.1)\n",
+      "Requirement already satisfied: regex!=2019.12.17 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (2023.12.25)\n",
+      "Requirement already satisfied: requests in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (2.31.0)\n",
+      "Requirement already satisfied: tokenizers<0.19,>=0.14 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (0.15.0)\n",
+      "Requirement already satisfied: safetensors>=0.4.1 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (0.4.1)\n",
+      "Requirement already satisfied: tqdm>=4.27 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from transformers) (4.66.1)\n",
+      "Requirement already satisfied: fsspec>=2023.5.0 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (2023.10.0)\n",
+      "Requirement already satisfied: typing-extensions>=3.7.4.3 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (4.9.0)\n",
+      "Requirement already satisfied: colorama in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from tqdm>=4.27->transformers) (0.4.6)\n",
+      "Requirement already satisfied: charset-normalizer<4,>=2 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->transformers) (2.0.4)\n",
+      "Requirement already satisfied: idna<4,>=2.5 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->transformers) (3.4)\n",
+      "Requirement already satisfied: urllib3<3,>=1.21.1 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->transformers) (2.1.0)\n",
+      "Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages (from requests->transformers) (2023.11.17)\n"
+     ]
+    }
+   ],
+   "source": [
+    "!pip install -q transformers datasets segments-ai evaluate\n",
+    "!pip install -U accelerate\n",
+    "!pip install -U transformers"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# !pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu121"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "True\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(torch.backends.cudnn.enabled)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
    "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "True\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(torch.cuda.is_available())"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Available CUDA Devices:\n",
+      "Device 0: NVIDIA GeForce RTX 3080 Ti\n",
+      "CUDA_VISIBLE_DEVICES: Not set (All GPUs are visible)\n"
+     ]
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "\n",
+    "# List all available GPUs\n",
+    "if torch.cuda.is_available():\n",
+    "    print(\"Available CUDA Devices:\")\n",
+    "    for i in range(torch.cuda.device_count()):\n",
+    "        print(f\"Device {i}: {torch.cuda.get_device_name(i)}\")\n",
+    "else:\n",
+    "    print(\"No CUDA devices are available\")\n",
+    "\n",
+    "# Check CUDA_VISIBLE_DEVICES environment variable\n",
+    "import os\n",
+    "cuda_visible_devices = os.getenv('CUDA_VISIBLE_DEVICES')\n",
+    "print(\"CUDA_VISIBLE_DEVICES:\", cuda_visible_devices if cuda_visible_devices is not None else \"Not set (All GPUs are visible)\")\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 145,
+     "referenced_widgets": [
+      "8d90aa42c48d4172b040253e980b52a9",
+      "79daa4b480e54dcf8856407c85c65f16",
+      "9b760908da26488aa1fb961aacb8f5ef",
+      "287bfe09367f4253a1566b026c36ad74",
+      "a88e4591259a405b9676fc7446e4625f",
+      "632bb774dbac423e86f9ae4d803e080c",
+      "db0dca9600cc4b1181d00ccd31510d16",
+      "37f202b56e8a4b50ad00bf8d82ac3204",
+      "6347558ca6214490a2de105c9c53edfd",
+      "d96edc8b0bb8422abde7dd63edea1c7f",
+      "22bc3403d15649e48934ada0e462a95a",
+      "ec882c565c89456a97652611d7fc4fb0",
+      "e6427564f5694a65890b06dce89c83f6",
+      "251e600b28934e7d8fc7150c1e293912",
+      "86480f72044b4250af1788dee3bbbb11",
+      "8ebfcb2835664461959c24a642bfc16c",
+      "c16da0793fb9493193b6474650fb7510",
+      "033ce4defe4540cb9b251d2ce1c8d80c",
+      "ee9ba91f11bf4527bc9ea5044b5d7469",
+      "79bce1c28005482fabc4eee0d9871ca7",
+      "0b4ac6328e7840e0b04375152e4cff5f",
+      "4df24038fd64437faefd38f087e8d8a6",
+      "c77d147d149a428c9251a086e068f7c0",
+      "eff45d541581479682d9f448746c82a4",
+      "e7a7df4c1862415799c131fea102087b",
+      "8151bdec05a34ea9bca0634b529814ee",
+      "4de89176ac3946ad870e27a40e04b638",
+      "c99eb0c52f6341cca6c14d611b1eae09",
+      "09fd23cf33ab4ea6b9fb25a97b4b371d",
+      "a00c758a1b0b4f3db31d9dbfa7b50f77",
+      "ccddcb21092644a5a2b586be5db09b86",
+      "41dc48fff7054bfd903dc976a0263684"
+     ]
+    },
+    "id": "WT2jsBUffigw",
+    "outputId": "07fe7e41-3c4d-4ba3-a312-3084e8c43a12"
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "babf77d7da6a454996bbc87bbe6b73b0",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from huggingface_hub import notebook_login\n",
+    "\n",
+    "notebook_login()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "rOAmX6BawqdJ",
+    "outputId": "2c4d8c5e-3e2b-4b7b-aa87-9a2005f5aecd"
+   },
+   "outputs": [],
+   "source": [
+    "# # fc54be4c5ea286d6edd6ad27a963a73a91e5ab1b\n",
+    "from segments import SegmentsClient\n",
+    "from getpass import getpass\n",
+    "\n",
+    "api_key = getpass('Enter your API key: ')\n",
+    "segments_client = SegmentsClient(api_key)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 81,
+     "referenced_widgets": [
+      "9cebf22c32cd44748d31bc579a8ae4a2",
+      "9d433d2f08d14da7a8be97c7872ada56",
+      "fff06ddb73604fdfb406a3376446b5f3",
+      "dabf129903e141ebb989ccc2eb540b34",
+      "24aa75f08b12441fa621d6091c6d0582",
+      "cb7dc2eddd9d4661985df4987ffa6d99",
+      "1dcf2e633103438fb18a18e41f6b42d1",
+      "1538b309424147b2ae5f53dc5388ec61",
+      "41fe2c9e1d774ea68a822356f1d97d7a",
+      "b69f3d8e102043058a92d8d34e92298a",
+      "6b82763efb014b8e92b18686886735ad",
+      "07e2dc52f8234edea0d51c172afa3f56",
+      "7814436b11404b0da781358d8359ce67",
+      "90c80bda0558499182c83f530342257e",
+      "d7d51cd892cf415194b987a553d16ba7",
+      "8397c244f58c48a19c95b63c7fe233d7",
+      "6b6ed63656a44dfb82968e9c2bb3824a",
+      "3b5bb13fe66b48b2a8d589deedc2f548",
+      "c1dff6ce7224438997be06a6fb151dd9",
+      "074f947b9af24017823ee319173423c7",
+      "74ebb22ba2794a46a29fb0a5d3dcb105",
+      "05989c1cfad44c8ba3bb5aa1e01afc85"
+     ]
+    },
+    "id": "Fqox12Ctwxtq",
+    "outputId": "7397d109-c45f-4206-a96c-adc878b695a2"
+   },
+   "outputs": [],
+   "source": [
+    "# from segments.huggingface import release2dataset\n",
+    "\n",
+    "# # dataset_identifier = 'label_h/Test_seg'\n",
+    "# dataset_identifier = 'ai_segment/Real_ECHO_Dateset'\n",
+    "# release_name = 'v0.3_full_label' #'v0.1_9_lbls'\n",
+    "\n",
+    "# release = segments_client.get_release(dataset_identifier, release_name)\n",
+    "# hf_dataset = release2dataset(release)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "id": "9eme461pw8QD",
+    "outputId": "207487a3-5d06-4bf6-b004-2c825beab476",
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "# hf_dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 84,
+     "referenced_widgets": [
+      "39bd4e893b5b4424ab6117b4603f2667",
+      "6fdd569fe7e0451f9190a22f6ef2bd71",
+      "fc0904c810f34c9cabb44a0a4f75d791",
+      "e45f6e7eb34f4587bc506a556e20e3f6",
+      "db168606bdb74c06bf6d64785828ea11",
+      "255a99c1b3074f46a92bba2e6affd4af",
+      "f00ce5e6f92f44ca946d3a3680bab9b2",
+      "66175f804f78452898366d5a994f1c3d",
+      "bf9fe521b3094e61b80e76ca7d584e7d",
+      "90d454feb6c547938f90c57076b670a8",
+      "91f025b6a33b42e99f324323f9b07740"
+     ]
+    },
+    "id": "Gq0M2WMbw-Wr",
+    "outputId": "bf76ade7-9992-4080-908e-e2e010d5ec56"
+   },
+   "outputs": [],
+   "source": [
+    "# from segments.utils import get_semantic_bitmap\n",
+    "\n",
+    "\n",
+    "# def convert_segmentation_bitmap(example):\n",
+    "#     return {\n",
+    "#         \"label.segmentation_bitmap\":\n",
+    "#             get_semantic_bitmap(\n",
+    "#                 example[\"label.segmentation_bitmap\"],\n",
+    "#                 example[\"label.annotations\"],\n",
+    "#             )\n",
+    "#     }\n",
+    "\n",
+    "\n",
+    "# semantic_dataset = hf_dataset.map(\n",
+    "#     convert_segmentation_bitmap,\n",
+    "# )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "id": "AZbQ0YZZw_4o"
+   },
+   "outputs": [],
+   "source": [
+    "# semantic_dataset = semantic_dataset.rename_column('image', 'pixel_values')\n",
+    "# semantic_dataset = semantic_dataset.rename_column('label.segmentation_bitmap', 'label')\n",
+    "# semantic_dataset = semantic_dataset.remove_columns(['name', 'uuid', 'status', 'label.annotations'])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 113,
+     "referenced_widgets": [
+      "45ed8bfce96e4e54aec336887adf12cb",
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+      "af2be1d82c7b490aa1875a180823f7cf",
+      "210f07dc198a47b2a1562e4258abe58c",
+      "a0c213fcd9f64da6862675aed0bd74c4",
+      "7887c0594a9644489ac6660ce2cd9adf",
+      "b3020aba141a49f5809b0051783b462e",
+      "7c7a7e16a30949dc94eb37e320d7e72e",
+      "1884788cbb234753b1b5f048519ec8fc",
+      "323bf0a287cd410ab5d500fca6f548ee",
+      "4ca35eafdcb74cd2a69daef85e219d0e",
+      "9db3135bd3e54f03bd7aa3bc5a2db490",
+      "a6f84aa825ff41a6b7019821ffb5922b",
+      "78fddd61995a4c84886421a874c8e6df",
+      "5d49d5d1072c423ea031f432fc2b0305",
+      "12477a5d060a4d42be6405e81099b67e"
+     ]
+    },
+    "id": "DQ7g8yFaxBS4",
+    "outputId": "ef5c9bfe-6814-4495-cd9a-11bfa1387a9e"
+   },
+   "outputs": [],
+   "source": [
+    "hf_dataset_identifier = \"unreal-hug/REAL_DATASET_SEG_401_6_lbls\"\n",
+    "# semantic_dataset.push_to_hub(hf_dataset_identifier)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 177,
+     "referenced_widgets": [
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+      "8c27ef8011ce49c2a30dc4534c8788c4",
+      "301c874428444bf3a0e4cb8a0d066058",
+      "438c48a905804740af8a14b3b7e8c47e",
+      "e9bfb79bad4a4bc5900739359e9dd12f",
+      "0a3f4106603d4526bf932912e1b82d50",
+      "1fe0124d8b604280ab52f77179d9c13b",
+      "a96d66b43ef849309507e67208884cd3"
+     ]
+    },
+    "id": "_DFh0t9AxLOP",
+    "outputId": "f82100b1-1b06-4902-a10f-6041b793f16e"
+   },
+   "outputs": [],
+   "source": [
+    "from datasets import load_dataset\n",
+    "\n",
+    "ds = load_dataset(hf_dataset_identifier)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "metadata": {
+    "id": "3YZr1fuhxPgw"
+   },
+   "outputs": [],
+   "source": [
+    "ds = ds.shuffle(seed=1)\n",
+    "ds = ds[\"train\"].train_test_split(test_size=0.2)\n",
+    "train_ds = ds[\"train\"]\n",
+    "test_ds = ds[\"test\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 66,
+     "referenced_widgets": [
+      "9ae07b85926d4542a434bd9e5f0ed62f",
+      "74de63c9f98a4c518a9ff869b67cb3aa",
+      "8128cfb290bc4f38a13b93ead427f7bd",
+      "b15a4e0c0ac24155902d5385107404a6",
+      "66c97bf84f0940689ffaad737da38f15",
+      "427711db87ff4e01b7029662d7600ca9",
+      "37edb76ff36d455f825cd429c85f8710",
+      "cd40fe4c65b84aaab4d221be3b324881",
+      "292366156ea544f0a6c58a2b3a2142b9",
+      "b3fc1287b95341f7b76cb7f405a6a912",
+      "34bdb99553574cd7a6963ab3fd14b295"
+     ]
+    },
+    "id": "FdU0XqN5xSae",
+    "outputId": "0d40b716-5a11-4bbc-d455-e6a310fef4f5"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Id2label: {0: 'unlabeled', 1: 'LV', 2: 'RV', 3: 'RA', 4: 'LA', 5: 'VS', 6: 'AS', 7: 'MK', 8: 'TK', 9: 'ASD', 10: 'VSD', 11: 'AK'}\n"
+     ]
+    }
+   ],
+   "source": [
+    "import json\n",
+    "from huggingface_hub import hf_hub_download\n",
+    "\n",
+    "filename = \"id2label.json\"\n",
+    "id2label = json.load(open(hf_hub_download(repo_id=hf_dataset_identifier, filename=filename, repo_type=\"dataset\"), \"r\"))\n",
+    "id2label = {int(k): v for k, v in id2label.items()}\n",
+    "label2id = {v: k for k, v in id2label.items()}\n",
+    "\n",
+    "num_labels = len(id2label)\n",
+    "print(\"Id2label:\", id2label)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 86,
+     "referenced_widgets": [
+      "248f4eeefce349c6826f70434b4a62bd",
+      "d665536d08d2456599c2c199ae6eb963",
+      "3fa0d1986e084dc3a997911de0978134",
+      "4e69219df0334d1686a8b34accc23ac9",
+      "6b0251377c8e4f60b24cee42ca9eaf4e",
+      "e0a94a2dfd42444eb99c87fbaa3241b6",
+      "da53d5b7a96b4ced9fc59ade2ce51e8a",
+      "2f05adc64d8d48009e1af2660c42d949",
+      "66a776fc0dc3401898edbeb36542b20c",
+      "27549d9d4c77424fae38439faf7a57ce",
+      "db626e91ae3441c49ce83f64a06e8e8c"
+     ]
+    },
+    "id": "oIOUoYIUxYYp",
+    "outputId": "c22328c5-fd68-4051-81ed-f0d77361523c"
+   },
+   "outputs": [],
+   "source": [
+    "from torchvision.transforms import ColorJitter\n",
+    "from transformers import (\n",
+    "    SegformerImageProcessor,\n",
+    ")\n",
+    "\n",
+    "processor = SegformerImageProcessor()\n",
+    "jitter = ColorJitter(brightness=0.25, contrast=0.25, saturation=0.25, hue=0.1)\n",
+    "\n",
+    "def train_transforms(example_batch):\n",
+    "    images = [jitter(x) for x in example_batch['pixel_values']]\n",
+    "    labels = [x for x in example_batch['label']]\n",
+    "    inputs = processor(images, labels)\n",
+    "    return inputs\n",
+    "\n",
+    "\n",
+    "def val_transforms(example_batch):\n",
+    "    images = [x for x in example_batch['pixel_values']]\n",
+    "    labels = [x for x in example_batch['label']]\n",
+    "    inputs = processor(images, labels)\n",
+    "    return inputs\n",
+    "\n",
+    "\n",
+    "# Set transforms\n",
+    "train_ds.set_transform(train_transforms)\n",
+    "test_ds.set_transform(val_transforms)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 136,
+     "referenced_widgets": [
+      "28eda5e67d504706bd83d82f3e349cf3",
+      "6169c712f769466d8cff57bc7960c80c",
+      "0affca424db7480ab22b1ceb2fa8fde2",
+      "17242d5535e948e0a2300520fa57f043",
+      "31a490d434e94ed78fd10c7db24a8d02",
+      "9472f331dc554d94ae55f97f3d05464a",
+      "a5483fa4f6094619b3b6876bb6ebf0fd",
+      "279fd67611434a289814418c88390c35",
+      "4f283af77def49928ccf8e418c4e41b9",
+      "966cea19958848d1b3a3f38d80b321df",
+      "b422f30febba47a5a1bac8f6d8737889",
+      "155f1606babb421682f63e7c3c4be4ad",
+      "4fae82b35b724f159a1d3c6adbf07a72",
+      "b7f46a19851d4e51ad0989c6a83cc680",
+      "b200d1094984483d8e6470baf38ed5df",
+      "8a7657ddeb9d470da7bbcefa05a1c218",
+      "ca3524e554024cb09782911a2ba50190",
+      "ae6e98344cc24026b09dbe48435d0352",
+      "94ff6ad15fe24220b187c227f9461711",
+      "49b14296a40b4ed0a06a49f09d79a182",
+      "c7b8b1c90f51462a8635700ed51da6ae",
+      "764f8717531b437cbc546ba2755699d5"
+     ]
+    },
+    "id": "kqKDS-8KxaJX",
+    "outputId": "17108fff-c192-4d22-ff6e-fe38abf0e58a"
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "c:\\Users\\rogbeast\\anaconda3\\envs\\hugging_face\\lib\\site-packages\\torch\\_utils.py:831: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly.  To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()\n",
+      "  return self.fget.__get__(instance, owner)()\n",
+      "Some weights of SegformerForSemanticSegmentation were not initialized from the model checkpoint at nvidia/mit-b0 and are newly initialized: ['decode_head.batch_norm.bias', 'decode_head.batch_norm.num_batches_tracked', 'decode_head.batch_norm.running_mean', 'decode_head.batch_norm.running_var', 'decode_head.batch_norm.weight', 'decode_head.classifier.bias', 'decode_head.classifier.weight', 'decode_head.linear_c.0.proj.bias', 'decode_head.linear_c.0.proj.weight', 'decode_head.linear_c.1.proj.bias', 'decode_head.linear_c.1.proj.weight', 'decode_head.linear_c.2.proj.bias', 'decode_head.linear_c.2.proj.weight', 'decode_head.linear_c.3.proj.bias', 'decode_head.linear_c.3.proj.weight', 'decode_head.linear_fuse.weight']\n",
+      "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "SegformerForSemanticSegmentation(\n",
+       "  (segformer): SegformerModel(\n",
+       "    (encoder): SegformerEncoder(\n",
+       "      (patch_embeddings): ModuleList(\n",
+       "        (0): SegformerOverlapPatchEmbeddings(\n",
+       "          (proj): Conv2d(3, 32, kernel_size=(7, 7), stride=(4, 4), padding=(3, 3))\n",
+       "          (layer_norm): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+       "        )\n",
+       "        (1): SegformerOverlapPatchEmbeddings(\n",
+       "          (proj): Conv2d(32, 64, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
+       "          (layer_norm): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+       "        )\n",
+       "        (2): SegformerOverlapPatchEmbeddings(\n",
+       "          (proj): Conv2d(64, 160, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
+       "          (layer_norm): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+       "        )\n",
+       "        (3): SegformerOverlapPatchEmbeddings(\n",
+       "          (proj): Conv2d(160, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
+       "          (layer_norm): LayerNorm((256,), eps=1e-05, elementwise_affine=True)\n",
+       "        )\n",
+       "      )\n",
+       "      (block): ModuleList(\n",
+       "        (0): ModuleList(\n",
+       "          (0): SegformerLayer(\n",
+       "            (layer_norm_1): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+       "            (attention): SegformerAttention(\n",
+       "              (self): SegformerEfficientSelfAttention(\n",
+       "                (query): Linear(in_features=32, out_features=32, bias=True)\n",
+       "                (key): Linear(in_features=32, out_features=32, bias=True)\n",
+       "                (value): Linear(in_features=32, out_features=32, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "                (sr): Conv2d(32, 32, kernel_size=(8, 8), stride=(8, 8))\n",
+       "                (layer_norm): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+       "              )\n",
+       "              (output): SegformerSelfOutput(\n",
+       "                (dense): Linear(in_features=32, out_features=32, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "            (drop_path): Identity()\n",
+       "            (layer_norm_2): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+       "            (mlp): SegformerMixFFN(\n",
+       "              (dense1): Linear(in_features=32, out_features=128, bias=True)\n",
+       "              (dwconv): SegformerDWConv(\n",
+       "                (dwconv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128)\n",
+       "              )\n",
+       "              (intermediate_act_fn): GELUActivation()\n",
+       "              (dense2): Linear(in_features=128, out_features=32, bias=True)\n",
+       "              (dropout): Dropout(p=0.0, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (1): SegformerLayer(\n",
+       "            (layer_norm_1): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+       "            (attention): SegformerAttention(\n",
+       "              (self): SegformerEfficientSelfAttention(\n",
+       "                (query): Linear(in_features=32, out_features=32, bias=True)\n",
+       "                (key): Linear(in_features=32, out_features=32, bias=True)\n",
+       "                (value): Linear(in_features=32, out_features=32, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "                (sr): Conv2d(32, 32, kernel_size=(8, 8), stride=(8, 8))\n",
+       "                (layer_norm): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+       "              )\n",
+       "              (output): SegformerSelfOutput(\n",
+       "                (dense): Linear(in_features=32, out_features=32, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "            (drop_path): SegformerDropPath(p=0.014285714365541935)\n",
+       "            (layer_norm_2): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+       "            (mlp): SegformerMixFFN(\n",
+       "              (dense1): Linear(in_features=32, out_features=128, bias=True)\n",
+       "              (dwconv): SegformerDWConv(\n",
+       "                (dwconv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=128)\n",
+       "              )\n",
+       "              (intermediate_act_fn): GELUActivation()\n",
+       "              (dense2): Linear(in_features=128, out_features=32, bias=True)\n",
+       "              (dropout): Dropout(p=0.0, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (1): ModuleList(\n",
+       "          (0): SegformerLayer(\n",
+       "            (layer_norm_1): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+       "            (attention): SegformerAttention(\n",
+       "              (self): SegformerEfficientSelfAttention(\n",
+       "                (query): Linear(in_features=64, out_features=64, bias=True)\n",
+       "                (key): Linear(in_features=64, out_features=64, bias=True)\n",
+       "                (value): Linear(in_features=64, out_features=64, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "                (sr): Conv2d(64, 64, kernel_size=(4, 4), stride=(4, 4))\n",
+       "                (layer_norm): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+       "              )\n",
+       "              (output): SegformerSelfOutput(\n",
+       "                (dense): Linear(in_features=64, out_features=64, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "            (drop_path): SegformerDropPath(p=0.02857142873108387)\n",
+       "            (layer_norm_2): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+       "            (mlp): SegformerMixFFN(\n",
+       "              (dense1): Linear(in_features=64, out_features=256, bias=True)\n",
+       "              (dwconv): SegformerDWConv(\n",
+       "                (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)\n",
+       "              )\n",
+       "              (intermediate_act_fn): GELUActivation()\n",
+       "              (dense2): Linear(in_features=256, out_features=64, bias=True)\n",
+       "              (dropout): Dropout(p=0.0, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (1): SegformerLayer(\n",
+       "            (layer_norm_1): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+       "            (attention): SegformerAttention(\n",
+       "              (self): SegformerEfficientSelfAttention(\n",
+       "                (query): Linear(in_features=64, out_features=64, bias=True)\n",
+       "                (key): Linear(in_features=64, out_features=64, bias=True)\n",
+       "                (value): Linear(in_features=64, out_features=64, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "                (sr): Conv2d(64, 64, kernel_size=(4, 4), stride=(4, 4))\n",
+       "                (layer_norm): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+       "              )\n",
+       "              (output): SegformerSelfOutput(\n",
+       "                (dense): Linear(in_features=64, out_features=64, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "            (drop_path): SegformerDropPath(p=0.04285714402794838)\n",
+       "            (layer_norm_2): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+       "            (mlp): SegformerMixFFN(\n",
+       "              (dense1): Linear(in_features=64, out_features=256, bias=True)\n",
+       "              (dwconv): SegformerDWConv(\n",
+       "                (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)\n",
+       "              )\n",
+       "              (intermediate_act_fn): GELUActivation()\n",
+       "              (dense2): Linear(in_features=256, out_features=64, bias=True)\n",
+       "              (dropout): Dropout(p=0.0, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (2): ModuleList(\n",
+       "          (0): SegformerLayer(\n",
+       "            (layer_norm_1): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+       "            (attention): SegformerAttention(\n",
+       "              (self): SegformerEfficientSelfAttention(\n",
+       "                (query): Linear(in_features=160, out_features=160, bias=True)\n",
+       "                (key): Linear(in_features=160, out_features=160, bias=True)\n",
+       "                (value): Linear(in_features=160, out_features=160, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "                (sr): Conv2d(160, 160, kernel_size=(2, 2), stride=(2, 2))\n",
+       "                (layer_norm): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+       "              )\n",
+       "              (output): SegformerSelfOutput(\n",
+       "                (dense): Linear(in_features=160, out_features=160, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "            (drop_path): SegformerDropPath(p=0.05714285746216774)\n",
+       "            (layer_norm_2): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+       "            (mlp): SegformerMixFFN(\n",
+       "              (dense1): Linear(in_features=160, out_features=640, bias=True)\n",
+       "              (dwconv): SegformerDWConv(\n",
+       "                (dwconv): Conv2d(640, 640, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=640)\n",
+       "              )\n",
+       "              (intermediate_act_fn): GELUActivation()\n",
+       "              (dense2): Linear(in_features=640, out_features=160, bias=True)\n",
+       "              (dropout): Dropout(p=0.0, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (1): SegformerLayer(\n",
+       "            (layer_norm_1): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+       "            (attention): SegformerAttention(\n",
+       "              (self): SegformerEfficientSelfAttention(\n",
+       "                (query): Linear(in_features=160, out_features=160, bias=True)\n",
+       "                (key): Linear(in_features=160, out_features=160, bias=True)\n",
+       "                (value): Linear(in_features=160, out_features=160, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "                (sr): Conv2d(160, 160, kernel_size=(2, 2), stride=(2, 2))\n",
+       "                (layer_norm): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+       "              )\n",
+       "              (output): SegformerSelfOutput(\n",
+       "                (dense): Linear(in_features=160, out_features=160, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "            (drop_path): SegformerDropPath(p=0.0714285746216774)\n",
+       "            (layer_norm_2): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+       "            (mlp): SegformerMixFFN(\n",
+       "              (dense1): Linear(in_features=160, out_features=640, bias=True)\n",
+       "              (dwconv): SegformerDWConv(\n",
+       "                (dwconv): Conv2d(640, 640, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=640)\n",
+       "              )\n",
+       "              (intermediate_act_fn): GELUActivation()\n",
+       "              (dense2): Linear(in_features=640, out_features=160, bias=True)\n",
+       "              (dropout): Dropout(p=0.0, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "        (3): ModuleList(\n",
+       "          (0): SegformerLayer(\n",
+       "            (layer_norm_1): LayerNorm((256,), eps=1e-05, elementwise_affine=True)\n",
+       "            (attention): SegformerAttention(\n",
+       "              (self): SegformerEfficientSelfAttention(\n",
+       "                (query): Linear(in_features=256, out_features=256, bias=True)\n",
+       "                (key): Linear(in_features=256, out_features=256, bias=True)\n",
+       "                (value): Linear(in_features=256, out_features=256, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "              )\n",
+       "              (output): SegformerSelfOutput(\n",
+       "                (dense): Linear(in_features=256, out_features=256, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "            (drop_path): SegformerDropPath(p=0.08571428805589676)\n",
+       "            (layer_norm_2): LayerNorm((256,), eps=1e-05, elementwise_affine=True)\n",
+       "            (mlp): SegformerMixFFN(\n",
+       "              (dense1): Linear(in_features=256, out_features=1024, bias=True)\n",
+       "              (dwconv): SegformerDWConv(\n",
+       "                (dwconv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1024)\n",
+       "              )\n",
+       "              (intermediate_act_fn): GELUActivation()\n",
+       "              (dense2): Linear(in_features=1024, out_features=256, bias=True)\n",
+       "              (dropout): Dropout(p=0.0, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "          (1): SegformerLayer(\n",
+       "            (layer_norm_1): LayerNorm((256,), eps=1e-05, elementwise_affine=True)\n",
+       "            (attention): SegformerAttention(\n",
+       "              (self): SegformerEfficientSelfAttention(\n",
+       "                (query): Linear(in_features=256, out_features=256, bias=True)\n",
+       "                (key): Linear(in_features=256, out_features=256, bias=True)\n",
+       "                (value): Linear(in_features=256, out_features=256, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "              )\n",
+       "              (output): SegformerSelfOutput(\n",
+       "                (dense): Linear(in_features=256, out_features=256, bias=True)\n",
+       "                (dropout): Dropout(p=0.0, inplace=False)\n",
+       "              )\n",
+       "            )\n",
+       "            (drop_path): SegformerDropPath(p=0.10000000149011612)\n",
+       "            (layer_norm_2): LayerNorm((256,), eps=1e-05, elementwise_affine=True)\n",
+       "            (mlp): SegformerMixFFN(\n",
+       "              (dense1): Linear(in_features=256, out_features=1024, bias=True)\n",
+       "              (dwconv): SegformerDWConv(\n",
+       "                (dwconv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1024)\n",
+       "              )\n",
+       "              (intermediate_act_fn): GELUActivation()\n",
+       "              (dense2): Linear(in_features=1024, out_features=256, bias=True)\n",
+       "              (dropout): Dropout(p=0.0, inplace=False)\n",
+       "            )\n",
+       "          )\n",
+       "        )\n",
+       "      )\n",
+       "      (layer_norm): ModuleList(\n",
+       "        (0): LayerNorm((32,), eps=1e-05, elementwise_affine=True)\n",
+       "        (1): LayerNorm((64,), eps=1e-05, elementwise_affine=True)\n",
+       "        (2): LayerNorm((160,), eps=1e-05, elementwise_affine=True)\n",
+       "        (3): LayerNorm((256,), eps=1e-05, elementwise_affine=True)\n",
+       "      )\n",
+       "    )\n",
+       "  )\n",
+       "  (decode_head): SegformerDecodeHead(\n",
+       "    (linear_c): ModuleList(\n",
+       "      (0): SegformerMLP(\n",
+       "        (proj): Linear(in_features=32, out_features=256, bias=True)\n",
+       "      )\n",
+       "      (1): SegformerMLP(\n",
+       "        (proj): Linear(in_features=64, out_features=256, bias=True)\n",
+       "      )\n",
+       "      (2): SegformerMLP(\n",
+       "        (proj): Linear(in_features=160, out_features=256, bias=True)\n",
+       "      )\n",
+       "      (3): SegformerMLP(\n",
+       "        (proj): Linear(in_features=256, out_features=256, bias=True)\n",
+       "      )\n",
+       "    )\n",
+       "    (linear_fuse): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
+       "    (batch_norm): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
+       "    (activation): ReLU()\n",
+       "    (dropout): Dropout(p=0.1, inplace=False)\n",
+       "    (classifier): Conv2d(256, 12, kernel_size=(1, 1), stride=(1, 1))\n",
+       "  )\n",
+       ")"
+      ]
+     },
+     "execution_count": 36,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from transformers import SegformerForSemanticSegmentation\n",
+    "\n",
+    "pretrained_model_name = \"nvidia/mit-b0\"\n",
+    "model = SegformerForSemanticSegmentation.from_pretrained(\n",
+    "    pretrained_model_name,\n",
+    "    id2label=id2label,\n",
+    "    label2id=label2id\n",
+    ")\n",
+    "\n",
+    "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
+    "model.to(device)  # Move your model to the selected device\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "metadata": {
+    "id": "rgrgU6shxb56"
+   },
+   "outputs": [],
+   "source": [
+    "from transformers import TrainingArguments\n",
+    "\n",
+    "epochs = 25\n",
+    "lr = 0.0001\n",
+    "batch_size = 2\n",
+    "\n",
+    "hub_model_id = \"segformer-b0-finetuned-segments-ECHO-feb-13-v1\"\n",
+    "\n",
+    "training_args = TrainingArguments(\n",
+    "    \"segformer-b0-finetuned-segments-outputs\",\n",
+    "    learning_rate=lr,\n",
+    "    num_train_epochs=epochs,\n",
+    "    per_device_train_batch_size=batch_size,\n",
+    "    per_device_eval_batch_size=batch_size,\n",
+    "    save_total_limit=3,\n",
+    "    evaluation_strategy=\"steps\",\n",
+    "    save_strategy=\"steps\",\n",
+    "    save_steps=20,\n",
+    "    eval_steps=20,\n",
+    "    logging_steps=1,\n",
+    "    eval_accumulation_steps=5,\n",
+    "    load_best_model_at_end=True,\n",
+    "    push_to_hub=True,\n",
+    "    hub_model_id=hub_model_id,\n",
+    "\n",
+    "    hub_strategy=\"end\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 49,
+     "referenced_widgets": [
+      "5ce930f685ec40e596ffe7097c563aaf",
+      "69512d0cbc3a40e688f836833b61af92",
+      "35cfdd432b6840f5b7bf0492376135e2",
+      "017cfb0b0de94adf8b2a67c4c1cbed32",
+      "f054f00917c640f3be2bfcca7e713057",
+      "e3f0794db93f4c00b05e6756f50f7e34",
+      "a1778b25578e4194a075ddec31d852fe",
+      "51568a44ad5644189f24c8ba5e324c4d",
+      "71ca7d48dd1045698bae348ea1f9118b",
+      "8d07d5c05eac47b989c92d02f075f646",
+      "56158227e30e4a00a670e2320864e269"
+     ]
+    },
+    "id": "ekMBkUy5xdFV",
+    "outputId": "9a22db9e-1c89-4821-e99b-66a0ef10585d"
+   },
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "from torch import nn\n",
+    "import evaluate\n",
+    "import multiprocessing\n",
+    "\n",
+    "metric = evaluate.load(\"mean_iou\")\n",
+    "\n",
+    "def compute_metrics(eval_pred):\n",
+    "  with torch.no_grad():\n",
+    "    logits, labels = eval_pred\n",
+    "    logits_tensor = torch.from_numpy(logits)\n",
+    "    # scale the logits to the size of the label\n",
+    "    logits_tensor = nn.functional.interpolate(\n",
+    "        logits_tensor,\n",
+    "        size=labels.shape[-2:],\n",
+    "        mode=\"bilinear\",\n",
+    "        align_corners=False,\n",
+    "    ).argmax(dim=1)\n",
+    "\n",
+    "    pred_labels = logits_tensor.detach().cpu().numpy()\n",
+    "    metrics = metric._compute(\n",
+    "            predictions=pred_labels,\n",
+    "            references=labels,\n",
+    "            num_labels=len(id2label),\n",
+    "            ignore_index=0,\n",
+    "            reduce_labels=processor.do_reduce_labels,\n",
+    "        )\n",
+    "\n",
+    "    # add per category metrics as individual key-value pairs\n",
+    "    per_category_accuracy = metrics.pop(\"per_category_accuracy\").tolist()\n",
+    "    per_category_iou = metrics.pop(\"per_category_iou\").tolist()\n",
+    "\n",
+    "    metrics.update({f\"accuracy_{id2label[i]}\": v for i, v in enumerate(per_category_accuracy)})\n",
+    "    metrics.update({f\"iou_{id2label[i]}\": v for i, v in enumerate(per_category_iou)})\n",
+    "\n",
+    "    return metrics"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "metadata": {
+    "id": "NqJfQsGHxqAQ"
+   },
+   "outputs": [],
+   "source": [
+    "from transformers import Trainer\n",
+    "\n",
+    "trainer = Trainer(\n",
+    "    model=model,\n",
+    "    args=training_args,\n",
+    "    train_dataset=train_ds,\n",
+    "    eval_dataset=test_ds,\n",
+    "    compute_metrics=compute_metrics,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000
+    },
+    "id": "eotoZ9TWxrtt",
+    "outputId": "16ad97a9-0aab-4af7-f7c6-4969f1d20d9b"
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e96e128fd6ad4843ab146fb6a8d6c5e1",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/4000 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'loss': 2.3473, 'learning_rate': 9.9975e-05, 'epoch': 0.01}\n",
+      "{'loss': 2.2622, 'learning_rate': 9.995e-05, 'epoch': 0.01}\n",
+      "{'loss': 2.2357, 'learning_rate': 9.9925e-05, 'epoch': 0.02}\n",
+      "{'loss': 2.2034, 'learning_rate': 9.99e-05, 'epoch': 0.03}\n",
+      "{'loss': 2.1585, 'learning_rate': 9.9875e-05, 'epoch': 0.03}\n",
+      "{'loss': 2.1904, 'learning_rate': 9.985000000000001e-05, 'epoch': 0.04}\n",
+      "{'loss': 2.1492, 'learning_rate': 9.9825e-05, 'epoch': 0.04}\n",
+      "{'loss': 2.0709, 'learning_rate': 9.98e-05, 'epoch': 0.05}\n",
+      "{'loss': 2.074, 'learning_rate': 9.977500000000001e-05, 'epoch': 0.06}\n",
+      "{'loss': 2.0431, 'learning_rate': 9.975000000000001e-05, 'epoch': 0.06}\n",
+      "{'loss': 1.9408, 'learning_rate': 9.9725e-05, 'epoch': 0.07}\n",
+      "{'loss': 1.9906, 'learning_rate': 9.970000000000001e-05, 'epoch': 0.07}\n",
+      "{'loss': 1.8631, 'learning_rate': 9.967500000000001e-05, 'epoch': 0.08}\n",
+      "{'loss': 1.8883, 'learning_rate': 9.965000000000001e-05, 'epoch': 0.09}\n",
+      "{'loss': 1.9316, 'learning_rate': 9.9625e-05, 'epoch': 0.09}\n",
+      "{'loss': 1.8542, 'learning_rate': 9.960000000000001e-05, 'epoch': 0.1}\n",
+      "{'loss': 1.8428, 'learning_rate': 9.957500000000001e-05, 'epoch': 0.11}\n",
+      "{'loss': 1.821, 'learning_rate': 9.955000000000001e-05, 'epoch': 0.11}\n",
+      "{'loss': 1.7534, 'learning_rate': 9.952500000000001e-05, 'epoch': 0.12}\n",
+      "{'loss': 1.8939, 'learning_rate': 9.95e-05, 'epoch': 0.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "85479fe8168347a9b2489831835a2bc3",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n",
+      "Checkpoint destination directory segformer-b0-finetuned-segments-outputs\\checkpoint-20 already exists and is non-empty.Saving will proceed but saved results may be invalid.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 1.4656, 'learning_rate': 9.900000000000001e-05, 'epoch': 0.25}\n"
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+    {
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+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n",
+      "Checkpoint destination directory segformer-b0-finetuned-segments-outputs\\checkpoint-40 already exists and is non-empty.Saving will proceed but saved results may be invalid.\n"
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+     "name": "stdout",
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+      "{'loss': 1.1969, 'learning_rate': 9.850000000000001e-05, 'epoch': 0.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
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+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.9788, 'learning_rate': 9.8e-05, 'epoch': 0.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2f1c5479f6954e67904d88cf701c57b1",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.8709, 'learning_rate': 9.7725e-05, 'epoch': 0.57}\n",
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+      "{'loss': 0.908, 'learning_rate': 9.7575e-05, 'epoch': 0.61}\n",
+      "{'loss': 0.8604, 'learning_rate': 9.755000000000001e-05, 'epoch': 0.61}\n",
+      "{'loss': 0.9128, 'learning_rate': 9.7525e-05, 'epoch': 0.62}\n",
+      "{'loss': 1.0336, 'learning_rate': 9.75e-05, 'epoch': 0.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3351bd79e8014326b0a901e14400c6b0",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.8202, 'learning_rate': 9.7225e-05, 'epoch': 0.69}\n",
+      "{'loss': 1.0136, 'learning_rate': 9.72e-05, 'epoch': 0.7}\n",
+      "{'loss': 0.8614, 'learning_rate': 9.7175e-05, 'epoch': 0.71}\n",
+      "{'loss': 0.7755, 'learning_rate': 9.715e-05, 'epoch': 0.71}\n",
+      "{'loss': 1.0192, 'learning_rate': 9.7125e-05, 'epoch': 0.72}\n",
+      "{'loss': 0.8027, 'learning_rate': 9.71e-05, 'epoch': 0.72}\n",
+      "{'loss': 0.8195, 'learning_rate': 9.7075e-05, 'epoch': 0.73}\n",
+      "{'loss': 0.7645, 'learning_rate': 9.705e-05, 'epoch': 0.74}\n",
+      "{'loss': 0.7002, 'learning_rate': 9.7025e-05, 'epoch': 0.74}\n",
+      "{'loss': 0.7608, 'learning_rate': 9.7e-05, 'epoch': 0.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4c0a888748054704bbb5debf62478d77",
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+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.772982656955719, 'eval_mean_iou': 0.11847309312735094, 'eval_mean_accuracy': 0.16782188908966506, 'eval_overall_accuracy': 0.36559400959451593, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6321322351523323, 'eval_accuracy_RV': 0.0660294541949821, 'eval_accuracy_RA': 0.09785898170490587, 'eval_accuracy_LA': 0.5117882943763336, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.0, 'eval_accuracy_VSD': 0.0, 'eval_accuracy_AK': 0.3704099254680967, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.5162607493922966, 'eval_iou_RV': 0.06572081485011792, 'eval_iou_RA': 0.08951885277670119, 'eval_iou_LA': 0.3125089021641685, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.0, 'eval_iou_VSD': 0.0, 'eval_iou_AK': 0.31919470521757615, 'eval_runtime': 4.6624, 'eval_samples_per_second': 17.373, 'eval_steps_per_second': 8.794, 'epoch': 0.75}\n",
+      "{'loss': 0.7608, 'learning_rate': 9.6975e-05, 'epoch': 0.76}\n",
+      "{'loss': 0.806, 'learning_rate': 9.695000000000001e-05, 'epoch': 0.76}\n",
+      "{'loss': 0.8687, 'learning_rate': 9.6925e-05, 'epoch': 0.77}\n",
+      "{'loss': 0.8092, 'learning_rate': 9.69e-05, 'epoch': 0.78}\n",
+      "{'loss': 0.8942, 'learning_rate': 9.687500000000001e-05, 'epoch': 0.78}\n",
+      "{'loss': 0.6562, 'learning_rate': 9.685000000000001e-05, 'epoch': 0.79}\n",
+      "{'loss': 0.6344, 'learning_rate': 9.682500000000001e-05, 'epoch': 0.79}\n",
+      "{'loss': 0.8349, 'learning_rate': 9.680000000000001e-05, 'epoch': 0.8}\n",
+      "{'loss': 0.6989, 'learning_rate': 9.677500000000001e-05, 'epoch': 0.81}\n",
+      "{'loss': 0.6603, 'learning_rate': 9.675000000000001e-05, 'epoch': 0.81}\n",
+      "{'loss': 0.7843, 'learning_rate': 9.6725e-05, 'epoch': 0.82}\n",
+      "{'loss': 0.6712, 'learning_rate': 9.67e-05, 'epoch': 0.82}\n",
+      "{'loss': 0.7004, 'learning_rate': 9.6675e-05, 'epoch': 0.83}\n",
+      "{'loss': 0.7142, 'learning_rate': 9.665e-05, 'epoch': 0.84}\n",
+      "{'loss': 0.6205, 'learning_rate': 9.6625e-05, 'epoch': 0.84}\n",
+      "{'loss': 0.5963, 'learning_rate': 9.66e-05, 'epoch': 0.85}\n",
+      "{'loss': 0.6111, 'learning_rate': 9.6575e-05, 'epoch': 0.86}\n",
+      "{'loss': 0.6874, 'learning_rate': 9.655e-05, 'epoch': 0.86}\n",
+      "{'loss': 0.6815, 'learning_rate': 9.652500000000002e-05, 'epoch': 0.87}\n",
+      "{'loss': 0.7414, 'learning_rate': 9.65e-05, 'epoch': 0.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "70fa7f02cc8e42c88feb87803688b249",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.6474451422691345, 'eval_mean_iou': 0.04891277196450219, 'eval_mean_accuracy': 0.0774306070558676, 'eval_overall_accuracy': 0.17798108361337173, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.28409168876651525, 'eval_accuracy_RV': 0.008459333198278667, 'eval_accuracy_RA': 0.00011701758491845085, 'eval_accuracy_LA': 0.4478162583442532, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.0, 'eval_accuracy_VSD': 0.0, 'eval_accuracy_AK': 0.033821772664710315, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.2739769574945681, 'eval_iou_RV': 0.008456659619450317, 'eval_iou_RA': 0.0001167469469666929, 'eval_iou_LA': 0.2219268973090961, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.0, 'eval_iou_VSD': 0.0, 'eval_iou_AK': 0.03356323023944283, 'eval_runtime': 4.5942, 'eval_samples_per_second': 17.631, 'eval_steps_per_second': 8.924, 'epoch': 0.88}\n",
+      "{'loss': 0.7572, 'learning_rate': 9.6475e-05, 'epoch': 0.88}\n",
+      "{'loss': 0.759, 'learning_rate': 9.645000000000001e-05, 'epoch': 0.89}\n",
+      "{'loss': 0.8043, 'learning_rate': 9.642500000000001e-05, 'epoch': 0.89}\n",
+      "{'loss': 0.6027, 'learning_rate': 9.64e-05, 'epoch': 0.9}\n",
+      "{'loss': 0.7729, 'learning_rate': 9.6375e-05, 'epoch': 0.91}\n",
+      "{'loss': 0.64, 'learning_rate': 9.635000000000001e-05, 'epoch': 0.91}\n",
+      "{'loss': 0.5524, 'learning_rate': 9.632500000000001e-05, 'epoch': 0.92}\n",
+      "{'loss': 0.6216, 'learning_rate': 9.63e-05, 'epoch': 0.93}\n",
+      "{'loss': 0.5912, 'learning_rate': 9.627500000000001e-05, 'epoch': 0.93}\n",
+      "{'loss': 0.5917, 'learning_rate': 9.625000000000001e-05, 'epoch': 0.94}\n",
+      "{'loss': 0.6682, 'learning_rate': 9.622500000000001e-05, 'epoch': 0.94}\n",
+      "{'loss': 0.5461, 'learning_rate': 9.620000000000001e-05, 'epoch': 0.95}\n",
+      "{'loss': 0.6526, 'learning_rate': 9.6175e-05, 'epoch': 0.96}\n",
+      "{'loss': 0.5377, 'learning_rate': 9.615e-05, 'epoch': 0.96}\n",
+      "{'loss': 0.5735, 'learning_rate': 9.6125e-05, 'epoch': 0.97}\n",
+      "{'loss': 0.6248, 'learning_rate': 9.61e-05, 'epoch': 0.97}\n",
+      "{'loss': 0.6059, 'learning_rate': 9.6075e-05, 'epoch': 0.98}\n",
+      "{'loss': 0.5096, 'learning_rate': 9.605e-05, 'epoch': 0.99}\n",
+      "{'loss': 0.5913, 'learning_rate': 9.6025e-05, 'epoch': 0.99}\n",
+      "{'loss': 0.5762, 'learning_rate': 9.6e-05, 'epoch': 1.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f6f478c8f3b140e3a170d7a41d2f18a8",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.5441722273826599, 'eval_mean_iou': 0.14150500670393024, 'eval_mean_accuracy': 0.1824663095712377, 'eval_overall_accuracy': 0.4102464301865889, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6756550156463945, 'eval_accuracy_RV': 0.17909169597966815, 'eval_accuracy_RA': 0.23293762559214934, 'eval_accuracy_LA': 0.5537445372155407, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.0035363741339491917, 'eval_accuracy_VSD': 0.0, 'eval_accuracy_AK': 0.179697847144675, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6016633195730596, 'eval_iou_RV': 0.1771311475409836, 'eval_iou_RA': 0.20535989029069054, 'eval_iou_LA': 0.3955678677148066, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.0035357042996689786, 'eval_iou_VSD': 0.0, 'eval_iou_AK': 0.17329714432402313, 'eval_runtime': 4.6331, 'eval_samples_per_second': 17.483, 'eval_steps_per_second': 8.849, 'epoch': 1.0}\n",
+      "{'loss': 0.5981, 'learning_rate': 9.5975e-05, 'epoch': 1.01}\n",
+      "{'loss': 0.6938, 'learning_rate': 9.595e-05, 'epoch': 1.01}\n",
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+      "{'loss': 0.7974, 'learning_rate': 9.59e-05, 'epoch': 1.02}\n",
+      "{'loss': 0.6084, 'learning_rate': 9.5875e-05, 'epoch': 1.03}\n",
+      "{'loss': 0.5131, 'learning_rate': 9.585000000000001e-05, 'epoch': 1.04}\n",
+      "{'loss': 0.5361, 'learning_rate': 9.582500000000001e-05, 'epoch': 1.04}\n",
+      "{'loss': 0.5649, 'learning_rate': 9.58e-05, 'epoch': 1.05}\n",
+      "{'loss': 0.5017, 'learning_rate': 9.5775e-05, 'epoch': 1.06}\n",
+      "{'loss': 0.7074, 'learning_rate': 9.575000000000001e-05, 'epoch': 1.06}\n",
+      "{'loss': 0.6453, 'learning_rate': 9.572500000000001e-05, 'epoch': 1.07}\n",
+      "{'loss': 0.4785, 'learning_rate': 9.57e-05, 'epoch': 1.07}\n",
+      "{'loss': 0.5102, 'learning_rate': 9.567500000000001e-05, 'epoch': 1.08}\n",
+      "{'loss': 0.5039, 'learning_rate': 9.565000000000001e-05, 'epoch': 1.09}\n",
+      "{'loss': 0.6512, 'learning_rate': 9.562500000000001e-05, 'epoch': 1.09}\n",
+      "{'loss': 0.4928, 'learning_rate': 9.56e-05, 'epoch': 1.1}\n",
+      "{'loss': 0.7025, 'learning_rate': 9.5575e-05, 'epoch': 1.11}\n",
+      "{'loss': 0.4502, 'learning_rate': 9.555e-05, 'epoch': 1.11}\n",
+      "{'loss': 0.6009, 'learning_rate': 9.5525e-05, 'epoch': 1.12}\n",
+      "{'loss': 0.415, 'learning_rate': 9.55e-05, 'epoch': 1.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3338b497a5024925a96e6af5cd942b42",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.5521490573883057, 'eval_mean_iou': 0.07551821481078022, 'eval_mean_accuracy': 0.0982198563939587, 'eval_overall_accuracy': 0.20918219410177458, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.2811011243329028, 'eval_accuracy_RV': 0.09344862090769014, 'eval_accuracy_RA': 0.1495121577235641, 'eval_accuracy_LA': 0.4375527411686414, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.0, 'eval_accuracy_VSD': 0.0, 'eval_accuracy_AK': 0.020583919806788375, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.27621776504297996, 'eval_iou_RV': 0.0922673616898762, 'eval_iou_RA': 0.1378895856204529, 'eval_iou_LA': 0.3038060759071584, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.0, 'eval_iou_VSD': 0.0, 'eval_iou_AK': 0.020519574658114957, 'eval_runtime': 4.6876, 'eval_samples_per_second': 17.28, 'eval_steps_per_second': 8.746, 'epoch': 1.12}\n",
+      "{'loss': 0.5745, 'learning_rate': 9.5475e-05, 'epoch': 1.13}\n",
+      "{'loss': 0.4934, 'learning_rate': 9.545e-05, 'epoch': 1.14}\n",
+      "{'loss': 0.6813, 'learning_rate': 9.542500000000002e-05, 'epoch': 1.14}\n",
+      "{'loss': 0.5679, 'learning_rate': 9.54e-05, 'epoch': 1.15}\n",
+      "{'loss': 0.6221, 'learning_rate': 9.5375e-05, 'epoch': 1.16}\n",
+      "{'loss': 0.6616, 'learning_rate': 9.535e-05, 'epoch': 1.16}\n",
+      "{'loss': 0.7268, 'learning_rate': 9.532500000000001e-05, 'epoch': 1.17}\n",
+      "{'loss': 0.5867, 'learning_rate': 9.53e-05, 'epoch': 1.18}\n",
+      "{'loss': 0.4495, 'learning_rate': 9.5275e-05, 'epoch': 1.18}\n",
+      "{'loss': 0.5045, 'learning_rate': 9.525000000000001e-05, 'epoch': 1.19}\n",
+      "{'loss': 0.3763, 'learning_rate': 9.522500000000001e-05, 'epoch': 1.19}\n",
+      "{'loss': 0.4899, 'learning_rate': 9.52e-05, 'epoch': 1.2}\n",
+      "{'loss': 0.4069, 'learning_rate': 9.517500000000001e-05, 'epoch': 1.21}\n",
+      "{'loss': 0.5152, 'learning_rate': 9.515000000000001e-05, 'epoch': 1.21}\n",
+      "{'loss': 0.4862, 'learning_rate': 9.512500000000001e-05, 'epoch': 1.22}\n",
+      "{'loss': 0.4025, 'learning_rate': 9.51e-05, 'epoch': 1.23}\n",
+      "{'loss': 0.5992, 'learning_rate': 9.507500000000001e-05, 'epoch': 1.23}\n",
+      "{'loss': 0.4861, 'learning_rate': 9.505e-05, 'epoch': 1.24}\n",
+      "{'loss': 0.5212, 'learning_rate': 9.5025e-05, 'epoch': 1.24}\n",
+      "{'loss': 0.6288, 'learning_rate': 9.5e-05, 'epoch': 1.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4be17cf5d7de4f9c900db6990578cbda",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.49277088046073914, 'eval_mean_iou': 0.15986059506496886, 'eval_mean_accuracy': 0.2117566757408771, 'eval_overall_accuracy': 0.42997858869301225, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.5575836537687078, 'eval_accuracy_RV': 0.3023843287476135, 'eval_accuracy_RA': 0.4286394486454206, 'eval_accuracy_LA': 0.6450013378247655, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.0009652857967667437, 'eval_accuracy_VSD': 0.0, 'eval_accuracy_AK': 0.18299270262549666, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.5262478109814124, 'eval_iou_RV': 0.2917372454720982, 'eval_iou_RA': 0.31250284988078303, 'eval_iou_LA': 0.44697093956141914, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.0009652857967667437, 'eval_iou_VSD': 0.0, 'eval_iou_AK': 0.18004241402217794, 'eval_runtime': 4.5847, 'eval_samples_per_second': 17.667, 'eval_steps_per_second': 8.943, 'epoch': 1.25}\n",
+      "{'loss': 0.387, 'learning_rate': 9.4975e-05, 'epoch': 1.26}\n",
+      "{'loss': 0.4524, 'learning_rate': 9.495e-05, 'epoch': 1.26}\n",
+      "{'loss': 0.3905, 'learning_rate': 9.4925e-05, 'epoch': 1.27}\n",
+      "{'loss': 0.4167, 'learning_rate': 9.49e-05, 'epoch': 1.27}\n",
+      "{'loss': 0.5956, 'learning_rate': 9.4875e-05, 'epoch': 1.28}\n",
+      "{'loss': 0.4746, 'learning_rate': 9.485e-05, 'epoch': 1.29}\n",
+      "{'loss': 0.4655, 'learning_rate': 9.482500000000001e-05, 'epoch': 1.29}\n",
+      "{'loss': 0.4751, 'learning_rate': 9.48e-05, 'epoch': 1.3}\n",
+      "{'loss': 0.3517, 'learning_rate': 9.4775e-05, 'epoch': 1.31}\n",
+      "{'loss': 0.3458, 'learning_rate': 9.475e-05, 'epoch': 1.31}\n",
+      "{'loss': 0.323, 'learning_rate': 9.472500000000001e-05, 'epoch': 1.32}\n",
+      "{'loss': 0.4955, 'learning_rate': 9.47e-05, 'epoch': 1.32}\n",
+      "{'loss': 0.7288, 'learning_rate': 9.4675e-05, 'epoch': 1.33}\n",
+      "{'loss': 0.613, 'learning_rate': 9.465000000000001e-05, 'epoch': 1.34}\n",
+      "{'loss': 0.5115, 'learning_rate': 9.462500000000001e-05, 'epoch': 1.34}\n",
+      "{'loss': 0.6908, 'learning_rate': 9.46e-05, 'epoch': 1.35}\n",
+      "{'loss': 0.3459, 'learning_rate': 9.457500000000001e-05, 'epoch': 1.36}\n",
+      "{'loss': 0.4636, 'learning_rate': 9.455000000000001e-05, 'epoch': 1.36}\n",
+      "{'loss': 0.4643, 'learning_rate': 9.452500000000001e-05, 'epoch': 1.37}\n",
+      "{'loss': 0.4221, 'learning_rate': 9.449999999999999e-05, 'epoch': 1.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "5e67fb9f534d4072b998b34fd9824869",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.4520528018474579, 'eval_mean_iou': 0.16301503940611636, 'eval_mean_accuracy': 0.19409682960990843, 'eval_overall_accuracy': 0.41306214147691495, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6759011219464175, 'eval_accuracy_RV': 0.23537879764513772, 'eval_accuracy_RA': 0.22916683479538064, 'eval_accuracy_LA': 0.3900994106710392, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.0, 'eval_accuracy_VSD': 0.0, 'eval_accuracy_AK': 0.4104221310411094, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6238599114224312, 'eval_iou_RV': 0.22526684066817756, 'eval_iou_RA': 0.21724960360798024, 'eval_iou_LA': 0.36088614986227296, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.0, 'eval_iou_VSD': 0.0, 'eval_iou_AK': 0.36590292790641815, 'eval_runtime': 4.6418, 'eval_samples_per_second': 17.45, 'eval_steps_per_second': 8.833, 'epoch': 1.38}\n",
+      "{'loss': 0.637, 'learning_rate': 9.4475e-05, 'epoch': 1.38}\n",
+      "{'loss': 0.498, 'learning_rate': 9.445e-05, 'epoch': 1.39}\n",
+      "{'loss': 0.5555, 'learning_rate': 9.4425e-05, 'epoch': 1.39}\n",
+      "{'loss': 0.5663, 'learning_rate': 9.44e-05, 'epoch': 1.4}\n",
+      "{'loss': 0.3853, 'learning_rate': 9.4375e-05, 'epoch': 1.41}\n",
+      "{'loss': 0.3576, 'learning_rate': 9.435e-05, 'epoch': 1.41}\n",
+      "{'loss': 0.3541, 'learning_rate': 9.4325e-05, 'epoch': 1.42}\n",
+      "{'loss': 0.4817, 'learning_rate': 9.43e-05, 'epoch': 1.43}\n",
+      "{'loss': 0.6509, 'learning_rate': 9.4275e-05, 'epoch': 1.43}\n",
+      "{'loss': 0.4235, 'learning_rate': 9.425e-05, 'epoch': 1.44}\n",
+      "{'loss': 0.4191, 'learning_rate': 9.422500000000001e-05, 'epoch': 1.44}\n",
+      "{'loss': 0.4426, 'learning_rate': 9.42e-05, 'epoch': 1.45}\n",
+      "{'loss': 0.7491, 'learning_rate': 9.4175e-05, 'epoch': 1.46}\n",
+      "{'loss': 0.4551, 'learning_rate': 9.415e-05, 'epoch': 1.46}\n",
+      "{'loss': 0.6243, 'learning_rate': 9.412500000000001e-05, 'epoch': 1.47}\n",
+      "{'loss': 0.5315, 'learning_rate': 9.41e-05, 'epoch': 1.48}\n",
+      "{'loss': 0.4044, 'learning_rate': 9.4075e-05, 'epoch': 1.48}\n",
+      "{'loss': 0.5055, 'learning_rate': 9.405000000000001e-05, 'epoch': 1.49}\n",
+      "{'loss': 0.4889, 'learning_rate': 9.402500000000001e-05, 'epoch': 1.49}\n",
+      "{'loss': 0.5465, 'learning_rate': 9.4e-05, 'epoch': 1.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c4802a9402d74f859ec5ee0b4856b868",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.45336952805519104, 'eval_mean_iou': 0.161036143367334, 'eval_mean_accuracy': 0.1927746073916334, 'eval_overall_accuracy': 0.39753164091323173, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.575299578487028, 'eval_accuracy_RV': 0.23857253356415403, 'eval_accuracy_RA': 0.3341195031998257, 'eval_accuracy_LA': 0.5009124650964949, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.0, 'eval_accuracy_VSD': 0.003995861696704351, 'eval_accuracy_AK': 0.27484613187212714, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.5256841847026114, 'eval_iou_RV': 0.23496292310436248, 'eval_iou_RA': 0.3119592511033962, 'eval_iou_LA': 0.4285802335068884, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.0, 'eval_iou_VSD': 0.0039937359039105644, 'eval_iou_AK': 0.2662172487195047, 'eval_runtime': 4.5185, 'eval_samples_per_second': 17.926, 'eval_steps_per_second': 9.074, 'epoch': 1.5}\n",
+      "{'loss': 0.4438, 'learning_rate': 9.397500000000001e-05, 'epoch': 1.51}\n",
+      "{'loss': 0.3783, 'learning_rate': 9.395000000000001e-05, 'epoch': 1.51}\n",
+      "{'loss': 0.3391, 'learning_rate': 9.3925e-05, 'epoch': 1.52}\n",
+      "{'loss': 0.5848, 'learning_rate': 9.39e-05, 'epoch': 1.52}\n",
+      "{'loss': 0.3349, 'learning_rate': 9.3875e-05, 'epoch': 1.53}\n",
+      "{'loss': 0.5815, 'learning_rate': 9.385e-05, 'epoch': 1.54}\n",
+      "{'loss': 0.4199, 'learning_rate': 9.3825e-05, 'epoch': 1.54}\n",
+      "{'loss': 0.4206, 'learning_rate': 9.38e-05, 'epoch': 1.55}\n",
+      "{'loss': 0.4687, 'learning_rate': 9.3775e-05, 'epoch': 1.56}\n",
+      "{'loss': 0.3436, 'learning_rate': 9.375e-05, 'epoch': 1.56}\n",
+      "{'loss': 0.2999, 'learning_rate': 9.3725e-05, 'epoch': 1.57}\n",
+      "{'loss': 0.3216, 'learning_rate': 9.370000000000001e-05, 'epoch': 1.57}\n",
+      "{'loss': 0.3429, 'learning_rate': 9.3675e-05, 'epoch': 1.58}\n",
+      "{'loss': 0.5147, 'learning_rate': 9.365e-05, 'epoch': 1.59}\n",
+      "{'loss': 0.4584, 'learning_rate': 9.362500000000001e-05, 'epoch': 1.59}\n",
+      "{'loss': 0.3741, 'learning_rate': 9.360000000000001e-05, 'epoch': 1.6}\n",
+      "{'loss': 0.4427, 'learning_rate': 9.3575e-05, 'epoch': 1.61}\n",
+      "{'loss': 0.4493, 'learning_rate': 9.355000000000001e-05, 'epoch': 1.61}\n",
+      "{'loss': 0.2984, 'learning_rate': 9.352500000000001e-05, 'epoch': 1.62}\n",
+      "{'loss': 0.3448, 'learning_rate': 9.350000000000001e-05, 'epoch': 1.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "fe87ad4d1c0446d0a4725cd3d9c6fbb2",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.4172816276550293, 'eval_mean_iou': 0.16281101333395698, 'eval_mean_accuracy': 0.1922913092093184, 'eval_overall_accuracy': 0.4307840822782756, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.690813672174476, 'eval_accuracy_RV': 0.2713677968286709, 'eval_accuracy_RA': 0.43704857440300854, 'eval_accuracy_LA': 0.4058051303864598, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.0, 'eval_accuracy_VSD': 0.0, 'eval_accuracy_AK': 0.11787791830056872, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6447587221220287, 'eval_iou_RV': 0.2664601131121824, 'eval_iou_RA': 0.38250895247243627, 'eval_iou_LA': 0.38021125436497544, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.0, 'eval_iou_VSD': 0.0, 'eval_iou_AK': 0.1169821046019039, 'eval_runtime': 4.4288, 'eval_samples_per_second': 18.289, 'eval_steps_per_second': 9.258, 'epoch': 1.62}\n",
+      "{'loss': 0.4993, 'learning_rate': 9.3475e-05, 'epoch': 1.63}\n",
+      "{'loss': 0.2848, 'learning_rate': 9.345000000000001e-05, 'epoch': 1.64}\n",
+      "{'loss': 0.5976, 'learning_rate': 9.342500000000001e-05, 'epoch': 1.64}\n",
+      "{'loss': 0.296, 'learning_rate': 9.340000000000001e-05, 'epoch': 1.65}\n",
+      "{'loss': 0.3256, 'learning_rate': 9.3375e-05, 'epoch': 1.66}\n",
+      "{'loss': 0.5176, 'learning_rate': 9.335e-05, 'epoch': 1.66}\n",
+      "{'loss': 0.5289, 'learning_rate': 9.3325e-05, 'epoch': 1.67}\n",
+      "{'loss': 0.3203, 'learning_rate': 9.33e-05, 'epoch': 1.68}\n",
+      "{'loss': 0.4322, 'learning_rate': 9.3275e-05, 'epoch': 1.68}\n",
+      "{'loss': 0.4831, 'learning_rate': 9.325e-05, 'epoch': 1.69}\n",
+      "{'loss': 0.5493, 'learning_rate': 9.3225e-05, 'epoch': 1.69}\n",
+      "{'loss': 0.4065, 'learning_rate': 9.320000000000002e-05, 'epoch': 1.7}\n",
+      "{'loss': 0.3502, 'learning_rate': 9.3175e-05, 'epoch': 1.71}\n",
+      "{'loss': 0.3821, 'learning_rate': 9.315e-05, 'epoch': 1.71}\n",
+      "{'loss': 0.3596, 'learning_rate': 9.3125e-05, 'epoch': 1.72}\n",
+      "{'loss': 0.5821, 'learning_rate': 9.310000000000001e-05, 'epoch': 1.73}\n",
+      "{'loss': 0.5057, 'learning_rate': 9.3075e-05, 'epoch': 1.73}\n",
+      "{'loss': 0.2717, 'learning_rate': 9.305e-05, 'epoch': 1.74}\n",
+      "{'loss': 0.5739, 'learning_rate': 9.302500000000001e-05, 'epoch': 1.74}\n",
+      "{'loss': 0.3597, 'learning_rate': 9.300000000000001e-05, 'epoch': 1.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1703d24f8b974527840e53f4d1e7b852",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.39834341406822205, 'eval_mean_iou': 0.23368899572115878, 'eval_mean_accuracy': 0.28216748128012564, 'eval_overall_accuracy': 0.561677601327739, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7492989699332679, 'eval_accuracy_RV': 0.48166786374211923, 'eval_accuracy_RA': 0.5431754537457733, 'eval_accuracy_LA': 0.6134115217585192, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.008101183602771362, 'eval_accuracy_VSD': 0.005667676252736378, 'eval_accuracy_AK': 0.4203521437660685, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6947936274353871, 'eval_iou_RV': 0.45352394356834963, 'eval_iou_RA': 0.47541400464066624, 'eval_iou_LA': 0.5384918836472922, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.008055039781850147, 'eval_iou_VSD': 0.005661776269967871, 'eval_iou_AK': 0.3946386775892335, 'eval_runtime': 4.5197, 'eval_samples_per_second': 17.922, 'eval_steps_per_second': 9.071, 'epoch': 1.75}\n",
+      "{'loss': 0.3049, 'learning_rate': 9.2975e-05, 'epoch': 1.76}\n",
+      "{'loss': 0.5127, 'learning_rate': 9.295000000000001e-05, 'epoch': 1.76}\n",
+      "{'loss': 0.336, 'learning_rate': 9.292500000000001e-05, 'epoch': 1.77}\n",
+      "{'loss': 0.4611, 'learning_rate': 9.290000000000001e-05, 'epoch': 1.77}\n",
+      "{'loss': 0.5614, 'learning_rate': 9.2875e-05, 'epoch': 1.78}\n",
+      "{'loss': 0.4789, 'learning_rate': 9.285000000000001e-05, 'epoch': 1.79}\n",
+      "{'loss': 0.3917, 'learning_rate': 9.2825e-05, 'epoch': 1.79}\n",
+      "{'loss': 0.4881, 'learning_rate': 9.28e-05, 'epoch': 1.8}\n",
+      "{'loss': 0.5099, 'learning_rate': 9.2775e-05, 'epoch': 1.81}\n",
+      "{'loss': 0.369, 'learning_rate': 9.275e-05, 'epoch': 1.81}\n",
+      "{'loss': 0.3493, 'learning_rate': 9.2725e-05, 'epoch': 1.82}\n",
+      "{'loss': 0.3695, 'learning_rate': 9.27e-05, 'epoch': 1.82}\n",
+      "{'loss': 0.3515, 'learning_rate': 9.2675e-05, 'epoch': 1.83}\n",
+      "{'loss': 0.3622, 'learning_rate': 9.265e-05, 'epoch': 1.84}\n",
+      "{'loss': 0.4467, 'learning_rate': 9.2625e-05, 'epoch': 1.84}\n",
+      "{'loss': 0.3902, 'learning_rate': 9.260000000000001e-05, 'epoch': 1.85}\n",
+      "{'loss': 0.3866, 'learning_rate': 9.2575e-05, 'epoch': 1.86}\n",
+      "{'loss': 0.423, 'learning_rate': 9.255e-05, 'epoch': 1.86}\n",
+      "{'loss': 0.3186, 'learning_rate': 9.252500000000001e-05, 'epoch': 1.87}\n",
+      "{'loss': 0.36, 'learning_rate': 9.250000000000001e-05, 'epoch': 1.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a6e06aee8a004137ae6b180fd687cc0c",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3886105716228485, 'eval_mean_iou': 0.2351076549535976, 'eval_mean_accuracy': 0.28246478600134295, 'eval_overall_accuracy': 0.5731525039003417, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7717058298853592, 'eval_accuracy_RV': 0.5411793955689792, 'eval_accuracy_RA': 0.5920666112514426, 'eval_accuracy_LA': 0.581238551307295, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.00166895207852194, 'eval_accuracy_VSD': 0.026689057486430565, 'eval_accuracy_AK': 0.3100994624354014, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6866473875669714, 'eval_iou_RV': 0.5001964608674067, 'eval_iou_RA': 0.5372247139588101, 'eval_iou_LA': 0.530196428152355, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.0016601159389077334, 'eval_iou_VSD': 0.026574303544235765, 'eval_iou_AK': 0.30368479446088703, 'eval_runtime': 4.4243, 'eval_samples_per_second': 18.308, 'eval_steps_per_second': 9.267, 'epoch': 1.88}\n",
+      "{'loss': 0.3527, 'learning_rate': 9.2475e-05, 'epoch': 1.88}\n",
+      "{'loss': 0.43, 'learning_rate': 9.245e-05, 'epoch': 1.89}\n",
+      "{'loss': 0.3043, 'learning_rate': 9.242500000000001e-05, 'epoch': 1.89}\n",
+      "{'loss': 0.5576, 'learning_rate': 9.240000000000001e-05, 'epoch': 1.9}\n",
+      "{'loss': 0.5312, 'learning_rate': 9.2375e-05, 'epoch': 1.91}\n",
+      "{'loss': 0.3172, 'learning_rate': 9.235000000000001e-05, 'epoch': 1.91}\n",
+      "{'loss': 0.3492, 'learning_rate': 9.232500000000001e-05, 'epoch': 1.92}\n",
+      "{'loss': 0.4139, 'learning_rate': 9.230000000000001e-05, 'epoch': 1.93}\n",
+      "{'loss': 0.4694, 'learning_rate': 9.2275e-05, 'epoch': 1.93}\n",
+      "{'loss': 0.5302, 'learning_rate': 9.225e-05, 'epoch': 1.94}\n",
+      "{'loss': 0.4117, 'learning_rate': 9.2225e-05, 'epoch': 1.94}\n",
+      "{'loss': 0.7422, 'learning_rate': 9.22e-05, 'epoch': 1.95}\n",
+      "{'loss': 0.4317, 'learning_rate': 9.2175e-05, 'epoch': 1.96}\n",
+      "{'loss': 0.3891, 'learning_rate': 9.215e-05, 'epoch': 1.96}\n",
+      "{'loss': 0.3885, 'learning_rate': 9.2125e-05, 'epoch': 1.97}\n",
+      "{'loss': 0.4188, 'learning_rate': 9.21e-05, 'epoch': 1.98}\n",
+      "{'loss': 0.3182, 'learning_rate': 9.2075e-05, 'epoch': 1.98}\n",
+      "{'loss': 0.3709, 'learning_rate': 9.205e-05, 'epoch': 1.99}\n",
+      "{'loss': 0.3262, 'learning_rate': 9.2025e-05, 'epoch': 1.99}\n",
+      "{'loss': 0.3836, 'learning_rate': 9.200000000000001e-05, 'epoch': 2.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "96bee66a6e144a3ba55068adc2cb5482",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3900052607059479, 'eval_mean_iou': 0.20475405271000732, 'eval_mean_accuracy': 0.24384930529723764, 'eval_overall_accuracy': 0.5000221794741408, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.742627997649312, 'eval_accuracy_RV': 0.2543892766594842, 'eval_accuracy_RA': 0.3730439905417511, 'eval_accuracy_LA': 0.6500490535747364, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.018160002886836026, 'eval_accuracy_VSD': 0.012040063573934686, 'eval_accuracy_AK': 0.38818266808632196, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6909496639195988, 'eval_iou_RV': 0.2489916826019621, 'eval_iou_RA': 0.3515556671001696, 'eval_iou_LA': 0.5556570426592814, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.018085115940596728, 'eval_iou_VSD': 0.012031494647258452, 'eval_iou_AK': 0.37502391294121334, 'eval_runtime': 4.4614, 'eval_samples_per_second': 18.156, 'eval_steps_per_second': 9.19, 'epoch': 2.0}\n",
+      "{'loss': 0.376, 'learning_rate': 9.1975e-05, 'epoch': 2.01}\n",
+      "{'loss': 0.3931, 'learning_rate': 9.195e-05, 'epoch': 2.01}\n",
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+      "{'loss': 0.4269, 'learning_rate': 9.190000000000001e-05, 'epoch': 2.02}\n",
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+      "{'loss': 0.406, 'learning_rate': 9.185e-05, 'epoch': 2.04}\n",
+      "{'loss': 0.3901, 'learning_rate': 9.182500000000001e-05, 'epoch': 2.04}\n",
+      "{'loss': 0.2932, 'learning_rate': 9.180000000000001e-05, 'epoch': 2.05}\n",
+      "{'loss': 0.303, 'learning_rate': 9.1775e-05, 'epoch': 2.06}\n",
+      "{'loss': 0.4394, 'learning_rate': 9.175000000000001e-05, 'epoch': 2.06}\n",
+      "{'loss': 0.4761, 'learning_rate': 9.172500000000001e-05, 'epoch': 2.07}\n",
+      "{'loss': 0.6319, 'learning_rate': 9.17e-05, 'epoch': 2.08}\n",
+      "{'loss': 0.2983, 'learning_rate': 9.1675e-05, 'epoch': 2.08}\n",
+      "{'loss': 0.3476, 'learning_rate': 9.165e-05, 'epoch': 2.09}\n",
+      "{'loss': 0.3686, 'learning_rate': 9.1625e-05, 'epoch': 2.09}\n",
+      "{'loss': 0.4421, 'learning_rate': 9.16e-05, 'epoch': 2.1}\n",
+      "{'loss': 0.2722, 'learning_rate': 9.1575e-05, 'epoch': 2.11}\n",
+      "{'loss': 0.2889, 'learning_rate': 9.155e-05, 'epoch': 2.11}\n",
+      "{'loss': 0.3196, 'learning_rate': 9.1525e-05, 'epoch': 2.12}\n",
+      "{'loss': 0.4327, 'learning_rate': 9.15e-05, 'epoch': 2.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "69616d5d03744d289b5eece241cfadfd",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.38443613052368164, 'eval_mean_iou': 0.15378119034466137, 'eval_mean_accuracy': 0.1772061278215511, 'eval_overall_accuracy': 0.38298785646742645, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.5639592984926362, 'eval_accuracy_RV': 0.23101714580379012, 'eval_accuracy_RA': 0.441690944452963, 'eval_accuracy_LA': 0.4739347141514418, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.02516058025404157, 'eval_accuracy_VSD': 0.0, 'eval_accuracy_AK': 0.036298595060638324, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.540239098472736, 'eval_iou_RV': 0.22851174681053904, 'eval_iou_RA': 0.416410679742764, 'eval_iou_LA': 0.44522016824595295, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.02503388415657622, 'eval_iou_VSD': 0.0, 'eval_iou_AK': 0.03617751636270694, 'eval_runtime': 4.4793, 'eval_samples_per_second': 18.083, 'eval_steps_per_second': 9.153, 'epoch': 2.12}\n",
+      "{'loss': 0.461, 'learning_rate': 9.1475e-05, 'epoch': 2.13}\n",
+      "{'loss': 0.309, 'learning_rate': 9.145e-05, 'epoch': 2.14}\n",
+      "{'loss': 0.3176, 'learning_rate': 9.1425e-05, 'epoch': 2.14}\n",
+      "{'loss': 0.4472, 'learning_rate': 9.140000000000001e-05, 'epoch': 2.15}\n",
+      "{'loss': 0.3262, 'learning_rate': 9.1375e-05, 'epoch': 2.16}\n",
+      "{'loss': 0.2872, 'learning_rate': 9.135e-05, 'epoch': 2.16}\n",
+      "{'loss': 0.4221, 'learning_rate': 9.132500000000001e-05, 'epoch': 2.17}\n",
+      "{'loss': 0.3797, 'learning_rate': 9.130000000000001e-05, 'epoch': 2.17}\n",
+      "{'loss': 0.332, 'learning_rate': 9.1275e-05, 'epoch': 2.18}\n",
+      "{'loss': 0.3127, 'learning_rate': 9.125e-05, 'epoch': 2.19}\n",
+      "{'loss': 0.3217, 'learning_rate': 9.122500000000001e-05, 'epoch': 2.19}\n",
+      "{'loss': 0.4159, 'learning_rate': 9.120000000000001e-05, 'epoch': 2.2}\n",
+      "{'loss': 0.4249, 'learning_rate': 9.1175e-05, 'epoch': 2.21}\n",
+      "{'loss': 0.2103, 'learning_rate': 9.115e-05, 'epoch': 2.21}\n",
+      "{'loss': 0.2756, 'learning_rate': 9.1125e-05, 'epoch': 2.22}\n",
+      "{'loss': 0.4592, 'learning_rate': 9.11e-05, 'epoch': 2.23}\n",
+      "{'loss': 0.3955, 'learning_rate': 9.1075e-05, 'epoch': 2.23}\n",
+      "{'loss': 0.3272, 'learning_rate': 9.105e-05, 'epoch': 2.24}\n",
+      "{'loss': 0.5334, 'learning_rate': 9.1025e-05, 'epoch': 2.24}\n",
+      "{'loss': 0.5664, 'learning_rate': 9.1e-05, 'epoch': 2.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0c3775e7d50a4b4f8e0a6dbef092c564",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.36808058619499207, 'eval_mean_iou': 0.21956278893063708, 'eval_mean_accuracy': 0.2608117110510343, 'eval_overall_accuracy': 0.5051134507150447, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6625509738351715, 'eval_accuracy_RV': 0.3554899721910164, 'eval_accuracy_RA': 0.5186562346162227, 'eval_accuracy_LA': 0.623345728222614, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.006423210161662817, 'eval_accuracy_VSD': 0.05637688547695445, 'eval_accuracy_AK': 0.3852741060067001, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6286150153685914, 'eval_iou_RV': 0.3480277481034739, 'eval_iou_RA': 0.45294897049443755, 'eval_iou_LA': 0.5484440031267825, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.006412219240260091, 'eval_iou_VSD': 0.05506495028045048, 'eval_iou_AK': 0.3756777716230118, 'eval_runtime': 4.4835, 'eval_samples_per_second': 18.066, 'eval_steps_per_second': 9.145, 'epoch': 2.25}\n",
+      "{'loss': 0.2379, 'learning_rate': 9.0975e-05, 'epoch': 2.26}\n",
+      "{'loss': 0.4084, 'learning_rate': 9.095e-05, 'epoch': 2.26}\n",
+      "{'loss': 0.2814, 'learning_rate': 9.0925e-05, 'epoch': 2.27}\n",
+      "{'loss': 0.362, 'learning_rate': 9.090000000000001e-05, 'epoch': 2.27}\n",
+      "{'loss': 0.4498, 'learning_rate': 9.0875e-05, 'epoch': 2.28}\n",
+      "{'loss': 0.3613, 'learning_rate': 9.085e-05, 'epoch': 2.29}\n",
+      "{'loss': 0.3478, 'learning_rate': 9.0825e-05, 'epoch': 2.29}\n",
+      "{'loss': 0.3964, 'learning_rate': 9.080000000000001e-05, 'epoch': 2.3}\n",
+      "{'loss': 0.4782, 'learning_rate': 9.0775e-05, 'epoch': 2.31}\n",
+      "{'loss': 0.3845, 'learning_rate': 9.075e-05, 'epoch': 2.31}\n",
+      "{'loss': 0.3197, 'learning_rate': 9.072500000000001e-05, 'epoch': 2.32}\n",
+      "{'loss': 0.3112, 'learning_rate': 9.070000000000001e-05, 'epoch': 2.33}\n",
+      "{'loss': 0.5325, 'learning_rate': 9.0675e-05, 'epoch': 2.33}\n",
+      "{'loss': 0.2392, 'learning_rate': 9.065000000000001e-05, 'epoch': 2.34}\n",
+      "{'loss': 0.3856, 'learning_rate': 9.062500000000001e-05, 'epoch': 2.34}\n",
+      "{'loss': 0.6535, 'learning_rate': 9.06e-05, 'epoch': 2.35}\n",
+      "{'loss': 0.2968, 'learning_rate': 9.0575e-05, 'epoch': 2.36}\n",
+      "{'loss': 0.4268, 'learning_rate': 9.055e-05, 'epoch': 2.36}\n",
+      "{'loss': 0.3865, 'learning_rate': 9.0525e-05, 'epoch': 2.37}\n",
+      "{'loss': 0.3046, 'learning_rate': 9.05e-05, 'epoch': 2.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "50658507296f4e43baf3fefd04b51ced",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3651963770389557, 'eval_mean_iou': 0.2666626208073596, 'eval_mean_accuracy': 0.31740041154857257, 'eval_overall_accuracy': 0.5685589184206483, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7836061881564699, 'eval_accuracy_RV': 0.41047717269194645, 'eval_accuracy_RA': 0.4699466561216337, 'eval_accuracy_LA': 0.5648176098902984, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.2473386980369515, 'eval_accuracy_VSD': 0.11899121360242301, 'eval_accuracy_AK': 0.5788265769860026, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7013693966711279, 'eval_iou_RV': 0.3959625329213751, 'eval_iou_RA': 0.4383475541136132, 'eval_iou_LA': 0.5168842135663879, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.22582159624413145, 'eval_iou_VSD': 0.11417719333582713, 'eval_iou_AK': 0.5407263420284932, 'eval_runtime': 4.4345, 'eval_samples_per_second': 18.266, 'eval_steps_per_second': 9.246, 'epoch': 2.38}\n",
+      "{'loss': 0.3772, 'learning_rate': 9.0475e-05, 'epoch': 2.38}\n",
+      "{'loss': 0.2796, 'learning_rate': 9.045e-05, 'epoch': 2.39}\n",
+      "{'loss': 0.3476, 'learning_rate': 9.0425e-05, 'epoch': 2.39}\n",
+      "{'loss': 0.3463, 'learning_rate': 9.04e-05, 'epoch': 2.4}\n",
+      "{'loss': 0.3221, 'learning_rate': 9.037500000000001e-05, 'epoch': 2.41}\n",
+      "{'loss': 0.2772, 'learning_rate': 9.035e-05, 'epoch': 2.41}\n",
+      "{'loss': 0.348, 'learning_rate': 9.0325e-05, 'epoch': 2.42}\n",
+      "{'loss': 0.2359, 'learning_rate': 9.030000000000001e-05, 'epoch': 2.42}\n",
+      "{'loss': 0.21, 'learning_rate': 9.027500000000001e-05, 'epoch': 2.43}\n",
+      "{'loss': 0.5044, 'learning_rate': 9.025e-05, 'epoch': 2.44}\n",
+      "{'loss': 0.2909, 'learning_rate': 9.0225e-05, 'epoch': 2.44}\n",
+      "{'loss': 0.2885, 'learning_rate': 9.020000000000001e-05, 'epoch': 2.45}\n",
+      "{'loss': 0.2968, 'learning_rate': 9.017500000000001e-05, 'epoch': 2.46}\n",
+      "{'loss': 0.9677, 'learning_rate': 9.015e-05, 'epoch': 2.46}\n",
+      "{'loss': 0.2102, 'learning_rate': 9.012500000000001e-05, 'epoch': 2.47}\n",
+      "{'loss': 0.329, 'learning_rate': 9.010000000000001e-05, 'epoch': 2.48}\n",
+      "{'loss': 0.5877, 'learning_rate': 9.007500000000001e-05, 'epoch': 2.48}\n",
+      "{'loss': 0.2767, 'learning_rate': 9.005000000000001e-05, 'epoch': 2.49}\n",
+      "{'loss': 0.3357, 'learning_rate': 9.0025e-05, 'epoch': 2.49}\n",
+      "{'loss': 0.2496, 'learning_rate': 9e-05, 'epoch': 2.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2cdbf640cf904dcfb0b1dd3faeaeb737",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.3331, 'learning_rate': 8.9975e-05, 'epoch': 2.51}\n",
+      "{'loss': 0.2767, 'learning_rate': 8.995e-05, 'epoch': 2.51}\n",
+      "{'loss': 0.3152, 'learning_rate': 8.9925e-05, 'epoch': 2.52}\n",
+      "{'loss': 0.279, 'learning_rate': 8.99e-05, 'epoch': 2.52}\n",
+      "{'loss': 0.3776, 'learning_rate': 8.9875e-05, 'epoch': 2.53}\n",
+      "{'loss': 0.2452, 'learning_rate': 8.985e-05, 'epoch': 2.54}\n",
+      "{'loss': 0.5023, 'learning_rate': 8.9825e-05, 'epoch': 2.54}\n",
+      "{'loss': 0.3476, 'learning_rate': 8.98e-05, 'epoch': 2.55}\n",
+      "{'loss': 0.5867, 'learning_rate': 8.977500000000001e-05, 'epoch': 2.56}\n",
+      "{'loss': 0.4456, 'learning_rate': 8.975e-05, 'epoch': 2.56}\n",
+      "{'loss': 0.3586, 'learning_rate': 8.9725e-05, 'epoch': 2.57}\n",
+      "{'loss': 0.312, 'learning_rate': 8.970000000000001e-05, 'epoch': 2.58}\n",
+      "{'loss': 0.3508, 'learning_rate': 8.967500000000001e-05, 'epoch': 2.58}\n",
+      "{'loss': 0.4179, 'learning_rate': 8.965e-05, 'epoch': 2.59}\n",
+      "{'loss': 0.3118, 'learning_rate': 8.962500000000001e-05, 'epoch': 2.59}\n",
+      "{'loss': 0.622, 'learning_rate': 8.960000000000001e-05, 'epoch': 2.6}\n",
+      "{'loss': 0.2449, 'learning_rate': 8.957500000000001e-05, 'epoch': 2.61}\n",
+      "{'loss': 0.3779, 'learning_rate': 8.955e-05, 'epoch': 2.61}\n",
+      "{'loss': 0.3746, 'learning_rate': 8.952500000000001e-05, 'epoch': 2.62}\n",
+      "{'loss': 0.4916, 'learning_rate': 8.950000000000001e-05, 'epoch': 2.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6fbafb373fe54ae49ca72333af68d7d7",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.3521, 'learning_rate': 8.9475e-05, 'epoch': 2.63}\n",
+      "{'loss': 0.2653, 'learning_rate': 8.945e-05, 'epoch': 2.64}\n",
+      "{'loss': 0.3197, 'learning_rate': 8.9425e-05, 'epoch': 2.64}\n",
+      "{'loss': 0.4406, 'learning_rate': 8.94e-05, 'epoch': 2.65}\n",
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+      "{'loss': 0.5163, 'learning_rate': 8.9325e-05, 'epoch': 2.67}\n",
+      "{'loss': 0.3402, 'learning_rate': 8.93e-05, 'epoch': 2.67}\n",
+      "{'loss': 0.3368, 'learning_rate': 8.927500000000002e-05, 'epoch': 2.68}\n",
+      "{'loss': 0.4278, 'learning_rate': 8.925e-05, 'epoch': 2.69}\n",
+      "{'loss': 0.2388, 'learning_rate': 8.9225e-05, 'epoch': 2.69}\n",
+      "{'loss': 0.2915, 'learning_rate': 8.92e-05, 'epoch': 2.7}\n",
+      "{'loss': 0.2885, 'learning_rate': 8.917500000000001e-05, 'epoch': 2.71}\n",
+      "{'loss': 0.2664, 'learning_rate': 8.915e-05, 'epoch': 2.71}\n",
+      "{'loss': 0.2817, 'learning_rate': 8.9125e-05, 'epoch': 2.72}\n",
+      "{'loss': 0.299, 'learning_rate': 8.910000000000001e-05, 'epoch': 2.73}\n",
+      "{'loss': 0.2319, 'learning_rate': 8.907500000000001e-05, 'epoch': 2.73}\n",
+      "{'loss': 0.2183, 'learning_rate': 8.905e-05, 'epoch': 2.74}\n",
+      "{'loss': 0.1891, 'learning_rate': 8.902500000000001e-05, 'epoch': 2.74}\n",
+      "{'loss': 0.379, 'learning_rate': 8.900000000000001e-05, 'epoch': 2.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "46a4132ba8684bf4845c9f02462a3903",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3950377106666565, 'eval_mean_iou': 0.1516743217486218, 'eval_mean_accuracy': 0.173418268573464, 'eval_overall_accuracy': 0.3249414678267794, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.4374412700874945, 'eval_accuracy_RV': 0.13472009920379135, 'eval_accuracy_RA': 0.37555381598379506, 'eval_accuracy_LA': 0.4041705829485658, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.02578305427251732, 'eval_accuracy_VSD': 0.042762467388370765, 'eval_accuracy_AK': 0.3137513958501052, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.4249872117944207, 'eval_iou_RV': 0.13344724788424497, 'eval_iou_RA': 0.3574900565972149, 'eval_iou_LA': 0.3845988124810268, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.025533359539720545, 'eval_iou_VSD': 0.04167519069468393, 'eval_iou_AK': 0.3006856602435276, 'eval_runtime': 4.4114, 'eval_samples_per_second': 18.361, 'eval_steps_per_second': 9.294, 'epoch': 2.75}\n",
+      "{'loss': 0.2336, 'learning_rate': 8.897500000000001e-05, 'epoch': 2.76}\n",
+      "{'loss': 0.3885, 'learning_rate': 8.895e-05, 'epoch': 2.76}\n",
+      "{'loss': 0.346, 'learning_rate': 8.8925e-05, 'epoch': 2.77}\n",
+      "{'loss': 0.2284, 'learning_rate': 8.89e-05, 'epoch': 2.77}\n",
+      "{'loss': 0.2303, 'learning_rate': 8.8875e-05, 'epoch': 2.78}\n",
+      "{'loss': 0.5418, 'learning_rate': 8.885e-05, 'epoch': 2.79}\n",
+      "{'loss': 0.3538, 'learning_rate': 8.8825e-05, 'epoch': 2.79}\n",
+      "{'loss': 0.2986, 'learning_rate': 8.88e-05, 'epoch': 2.8}\n",
+      "{'loss': 0.686, 'learning_rate': 8.8775e-05, 'epoch': 2.81}\n",
+      "{'loss': 0.2777, 'learning_rate': 8.875e-05, 'epoch': 2.81}\n",
+      "{'loss': 0.286, 'learning_rate': 8.8725e-05, 'epoch': 2.82}\n",
+      "{'loss': 0.4653, 'learning_rate': 8.87e-05, 'epoch': 2.83}\n",
+      "{'loss': 0.454, 'learning_rate': 8.867500000000001e-05, 'epoch': 2.83}\n",
+      "{'loss': 0.3526, 'learning_rate': 8.865e-05, 'epoch': 2.84}\n",
+      "{'loss': 0.3189, 'learning_rate': 8.8625e-05, 'epoch': 2.84}\n",
+      "{'loss': 0.2855, 'learning_rate': 8.86e-05, 'epoch': 2.85}\n",
+      "{'loss': 0.3752, 'learning_rate': 8.857500000000001e-05, 'epoch': 2.86}\n",
+      "{'loss': 0.2247, 'learning_rate': 8.855e-05, 'epoch': 2.86}\n",
+      "{'loss': 0.2431, 'learning_rate': 8.8525e-05, 'epoch': 2.87}\n",
+      "{'loss': 0.6577, 'learning_rate': 8.850000000000001e-05, 'epoch': 2.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3154f25ef7a9403c8f0b5bcc4fa29a07",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.34359508752822876, 'eval_mean_iou': 0.2227270086772777, 'eval_mean_accuracy': 0.2598899495076218, 'eval_overall_accuracy': 0.5020240122560529, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6456479456835938, 'eval_accuracy_RV': 0.44729184699534064, 'eval_accuracy_RA': 0.5703759896056104, 'eval_accuracy_LA': 0.5855779059955132, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.12656971709006928, 'eval_accuracy_VSD': 0.04655591207604882, 'eval_accuracy_AK': 0.1768801776300413, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6094534595502905, 'eval_iou_RV': 0.433932655200343, 'eval_iou_RA': 0.5263502820651264, 'eval_iou_LA': 0.5368702943081964, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.12108919863634401, 'eval_iou_VSD': 0.04576372359005726, 'eval_iou_AK': 0.17653748209969738, 'eval_runtime': 4.5192, 'eval_samples_per_second': 17.924, 'eval_steps_per_second': 9.072, 'epoch': 2.88}\n",
+      "{'loss': 0.306, 'learning_rate': 8.847500000000001e-05, 'epoch': 2.88}\n",
+      "{'loss': 0.1876, 'learning_rate': 8.845e-05, 'epoch': 2.89}\n",
+      "{'loss': 0.2499, 'learning_rate': 8.842500000000001e-05, 'epoch': 2.89}\n",
+      "{'loss': 0.2519, 'learning_rate': 8.840000000000001e-05, 'epoch': 2.9}\n",
+      "{'loss': 0.2768, 'learning_rate': 8.837500000000001e-05, 'epoch': 2.91}\n",
+      "{'loss': 0.4043, 'learning_rate': 8.834999999999999e-05, 'epoch': 2.91}\n",
+      "{'loss': 0.3308, 'learning_rate': 8.8325e-05, 'epoch': 2.92}\n",
+      "{'loss': 0.3594, 'learning_rate': 8.83e-05, 'epoch': 2.92}\n",
+      "{'loss': 0.3887, 'learning_rate': 8.8275e-05, 'epoch': 2.93}\n",
+      "{'loss': 0.5451, 'learning_rate': 8.825e-05, 'epoch': 2.94}\n",
+      "{'loss': 0.6965, 'learning_rate': 8.8225e-05, 'epoch': 2.94}\n",
+      "{'loss': 0.3238, 'learning_rate': 8.82e-05, 'epoch': 2.95}\n",
+      "{'loss': 0.1807, 'learning_rate': 8.8175e-05, 'epoch': 2.96}\n",
+      "{'loss': 0.2612, 'learning_rate': 8.815e-05, 'epoch': 2.96}\n",
+      "{'loss': 0.2761, 'learning_rate': 8.8125e-05, 'epoch': 2.97}\n",
+      "{'loss': 0.4235, 'learning_rate': 8.81e-05, 'epoch': 2.98}\n",
+      "{'loss': 0.2349, 'learning_rate': 8.807500000000001e-05, 'epoch': 2.98}\n",
+      "{'loss': 0.2108, 'learning_rate': 8.805e-05, 'epoch': 2.99}\n",
+      "{'loss': 0.4952, 'learning_rate': 8.8025e-05, 'epoch': 2.99}\n",
+      "{'loss': 0.4409, 'learning_rate': 8.800000000000001e-05, 'epoch': 3.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "60ecc89b9a46412a9a6cdd7c5848f0fd",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3418080806732178, 'eval_mean_iou': 0.2664127756820365, 'eval_mean_accuracy': 0.3144133772210874, 'eval_overall_accuracy': 0.5290142684343888, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7061207382592379, 'eval_accuracy_RV': 0.2979858438154171, 'eval_accuracy_RA': 0.5006577195290244, 'eval_accuracy_LA': 0.6289714528776954, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3376786229792148, 'eval_accuracy_VSD': 0.2558925840405434, 'eval_accuracy_AK': 0.4168268107097411, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6587669679322604, 'eval_iou_RV': 0.291633435018422, 'eval_iou_RA': 0.46757347995093484, 'eval_iou_LA': 0.5755909133002777, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2975886660147399, 'eval_iou_VSD': 0.23626521952806484, 'eval_iou_AK': 0.4031218507577018, 'eval_runtime': 4.3518, 'eval_samples_per_second': 18.613, 'eval_steps_per_second': 9.421, 'epoch': 3.0}\n",
+      "{'loss': 0.4223, 'learning_rate': 8.797500000000001e-05, 'epoch': 3.01}\n",
+      "{'loss': 0.3792, 'learning_rate': 8.795e-05, 'epoch': 3.01}\n",
+      "{'loss': 0.504, 'learning_rate': 8.7925e-05, 'epoch': 3.02}\n",
+      "{'loss': 0.2757, 'learning_rate': 8.790000000000001e-05, 'epoch': 3.02}\n",
+      "{'loss': 0.2759, 'learning_rate': 8.787500000000001e-05, 'epoch': 3.03}\n",
+      "{'loss': 0.2198, 'learning_rate': 8.785e-05, 'epoch': 3.04}\n",
+      "{'loss': 0.3852, 'learning_rate': 8.782500000000001e-05, 'epoch': 3.04}\n",
+      "{'loss': 0.2931, 'learning_rate': 8.78e-05, 'epoch': 3.05}\n",
+      "{'loss': 0.2375, 'learning_rate': 8.7775e-05, 'epoch': 3.06}\n",
+      "{'loss': 0.3665, 'learning_rate': 8.775e-05, 'epoch': 3.06}\n",
+      "{'loss': 0.2107, 'learning_rate': 8.7725e-05, 'epoch': 3.07}\n",
+      "{'loss': 0.3242, 'learning_rate': 8.77e-05, 'epoch': 3.08}\n",
+      "{'loss': 0.1714, 'learning_rate': 8.7675e-05, 'epoch': 3.08}\n",
+      "{'loss': 0.348, 'learning_rate': 8.765e-05, 'epoch': 3.09}\n",
+      "{'loss': 0.3155, 'learning_rate': 8.7625e-05, 'epoch': 3.09}\n",
+      "{'loss': 0.5467, 'learning_rate': 8.76e-05, 'epoch': 3.1}\n",
+      "{'loss': 0.2827, 'learning_rate': 8.7575e-05, 'epoch': 3.11}\n",
+      "{'loss': 0.2763, 'learning_rate': 8.755e-05, 'epoch': 3.11}\n",
+      "{'loss': 0.1625, 'learning_rate': 8.7525e-05, 'epoch': 3.12}\n",
+      "{'loss': 0.3465, 'learning_rate': 8.75e-05, 'epoch': 3.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "493df1daa1a44c4e8a19c74ebc92d46f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3432627320289612, 'eval_mean_iou': 0.23984638689995766, 'eval_mean_accuracy': 0.28057714314713234, 'eval_overall_accuracy': 0.4988363890517788, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6128084159405288, 'eval_accuracy_RV': 0.37124993093795466, 'eval_accuracy_RA': 0.5864578373536271, 'eval_accuracy_LA': 0.6201692519844401, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.16371968822170901, 'eval_accuracy_VSD': 0.16492488079887246, 'eval_accuracy_AK': 0.28644142623419117, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.5866878292825202, 'eval_iou_RV': 0.3627293093055268, 'eval_iou_RA': 0.5335625352200577, 'eval_iou_LA': 0.5666916383514926, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.15400412420125423, 'eval_iou_VSD': 0.15447759621934007, 'eval_iou_AK': 0.2801572233193424, 'eval_runtime': 4.342, 'eval_samples_per_second': 18.655, 'eval_steps_per_second': 9.443, 'epoch': 3.12}\n",
+      "{'loss': 0.2946, 'learning_rate': 8.747500000000001e-05, 'epoch': 3.13}\n",
+      "{'loss': 0.3413, 'learning_rate': 8.745000000000001e-05, 'epoch': 3.14}\n",
+      "{'loss': 0.2077, 'learning_rate': 8.7425e-05, 'epoch': 3.14}\n",
+      "{'loss': 0.3287, 'learning_rate': 8.740000000000001e-05, 'epoch': 3.15}\n",
+      "{'loss': 0.266, 'learning_rate': 8.737500000000001e-05, 'epoch': 3.16}\n",
+      "{'loss': 0.5664, 'learning_rate': 8.735000000000001e-05, 'epoch': 3.16}\n",
+      "{'loss': 0.3705, 'learning_rate': 8.7325e-05, 'epoch': 3.17}\n",
+      "{'loss': 0.3286, 'learning_rate': 8.730000000000001e-05, 'epoch': 3.17}\n",
+      "{'loss': 0.4017, 'learning_rate': 8.727500000000001e-05, 'epoch': 3.18}\n",
+      "{'loss': 0.2436, 'learning_rate': 8.725e-05, 'epoch': 3.19}\n",
+      "{'loss': 0.2652, 'learning_rate': 8.7225e-05, 'epoch': 3.19}\n",
+      "{'loss': 0.2447, 'learning_rate': 8.72e-05, 'epoch': 3.2}\n",
+      "{'loss': 0.4323, 'learning_rate': 8.7175e-05, 'epoch': 3.21}\n",
+      "{'loss': 0.4107, 'learning_rate': 8.715e-05, 'epoch': 3.21}\n",
+      "{'loss': 0.4571, 'learning_rate': 8.7125e-05, 'epoch': 3.22}\n",
+      "{'loss': 0.3832, 'learning_rate': 8.71e-05, 'epoch': 3.23}\n",
+      "{'loss': 0.6209, 'learning_rate': 8.7075e-05, 'epoch': 3.23}\n",
+      "{'loss': 0.1511, 'learning_rate': 8.705000000000002e-05, 'epoch': 3.24}\n",
+      "{'loss': 0.2817, 'learning_rate': 8.7025e-05, 'epoch': 3.24}\n",
+      "{'loss': 0.2731, 'learning_rate': 8.7e-05, 'epoch': 3.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "205b6fe28bca4e12a3cbf58e11f71543",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.33349984884262085, 'eval_mean_iou': 0.23829880489858357, 'eval_mean_accuracy': 0.2761047385351926, 'eval_overall_accuracy': 0.5131391745773458, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6700810808392076, 'eval_accuracy_RV': 0.41878456939047376, 'eval_accuracy_RA': 0.4425161201810948, 'eval_accuracy_LA': 0.6283196920944847, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.0864787817551963, 'eval_accuracy_VSD': 0.1608990313971272, 'eval_accuracy_AK': 0.3539681096943413, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6377064736539156, 'eval_iou_RV': 0.4071734144670971, 'eval_iou_RA': 0.421895948464733, 'eval_iou_LA': 0.5762788919704194, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.0840855065217582, 'eval_iou_VSD': 0.15262300794333705, 'eval_iou_AK': 0.34152361086315813, 'eval_runtime': 4.3077, 'eval_samples_per_second': 18.804, 'eval_steps_per_second': 9.518, 'epoch': 3.25}\n",
+      "{'loss': 0.2922, 'learning_rate': 8.6975e-05, 'epoch': 3.26}\n",
+      "{'loss': 0.6911, 'learning_rate': 8.695000000000001e-05, 'epoch': 3.26}\n",
+      "{'loss': 0.2667, 'learning_rate': 8.6925e-05, 'epoch': 3.27}\n",
+      "{'loss': 0.2364, 'learning_rate': 8.69e-05, 'epoch': 3.27}\n",
+      "{'loss': 0.2767, 'learning_rate': 8.687500000000001e-05, 'epoch': 3.28}\n",
+      "{'loss': 0.2984, 'learning_rate': 8.685000000000001e-05, 'epoch': 3.29}\n",
+      "{'loss': 0.2313, 'learning_rate': 8.6825e-05, 'epoch': 3.29}\n",
+      "{'loss': 0.3067, 'learning_rate': 8.680000000000001e-05, 'epoch': 3.3}\n",
+      "{'loss': 0.3679, 'learning_rate': 8.677500000000001e-05, 'epoch': 3.31}\n",
+      "{'loss': 0.1887, 'learning_rate': 8.675000000000001e-05, 'epoch': 3.31}\n",
+      "{'loss': 0.3371, 'learning_rate': 8.672500000000001e-05, 'epoch': 3.32}\n",
+      "{'loss': 0.3422, 'learning_rate': 8.67e-05, 'epoch': 3.33}\n",
+      "{'loss': 0.3179, 'learning_rate': 8.6675e-05, 'epoch': 3.33}\n",
+      "{'loss': 0.3163, 'learning_rate': 8.665e-05, 'epoch': 3.34}\n",
+      "{'loss': 0.412, 'learning_rate': 8.6625e-05, 'epoch': 3.34}\n",
+      "{'loss': 0.2268, 'learning_rate': 8.66e-05, 'epoch': 3.35}\n",
+      "{'loss': 0.2733, 'learning_rate': 8.6575e-05, 'epoch': 3.36}\n",
+      "{'loss': 0.2772, 'learning_rate': 8.655e-05, 'epoch': 3.36}\n",
+      "{'loss': 0.3303, 'learning_rate': 8.6525e-05, 'epoch': 3.37}\n",
+      "{'loss': 0.2743, 'learning_rate': 8.65e-05, 'epoch': 3.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0c4237bac93a4c308f266f2bf7a4f247",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3368947207927704, 'eval_mean_iou': 0.29113701702551037, 'eval_mean_accuracy': 0.3436049993944616, 'eval_overall_accuracy': 0.6006888620090493, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.8056244984651916, 'eval_accuracy_RV': 0.4218355770824509, 'eval_accuracy_RA': 0.5779639747242017, 'eval_accuracy_LA': 0.6654443293381541, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.2544926385681293, 'eval_accuracy_VSD': 0.3199613158604972, 'eval_accuracy_AK': 0.3907276599059911, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7457548371419045, 'eval_iou_RV': 0.4105846203485584, 'eval_iou_RA': 0.5293874149238726, 'eval_iou_LA': 0.6047981293842557, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2364191012554265, 'eval_iou_VSD': 0.29546272707133364, 'eval_iou_AK': 0.3801003571552631, 'eval_runtime': 4.3672, 'eval_samples_per_second': 18.548, 'eval_steps_per_second': 9.388, 'epoch': 3.38}\n",
+      "{'loss': 0.3881, 'learning_rate': 8.6475e-05, 'epoch': 3.38}\n",
+      "{'loss': 0.4177, 'learning_rate': 8.645000000000001e-05, 'epoch': 3.39}\n",
+      "{'loss': 0.3626, 'learning_rate': 8.6425e-05, 'epoch': 3.39}\n",
+      "{'loss': 0.2583, 'learning_rate': 8.64e-05, 'epoch': 3.4}\n",
+      "{'loss': 0.221, 'learning_rate': 8.637500000000001e-05, 'epoch': 3.41}\n",
+      "{'loss': 0.2868, 'learning_rate': 8.635000000000001e-05, 'epoch': 3.41}\n",
+      "{'loss': 0.256, 'learning_rate': 8.6325e-05, 'epoch': 3.42}\n",
+      "{'loss': 0.3198, 'learning_rate': 8.63e-05, 'epoch': 3.42}\n",
+      "{'loss': 0.3022, 'learning_rate': 8.627500000000001e-05, 'epoch': 3.43}\n",
+      "{'loss': 0.4857, 'learning_rate': 8.625000000000001e-05, 'epoch': 3.44}\n",
+      "{'loss': 0.3148, 'learning_rate': 8.6225e-05, 'epoch': 3.44}\n",
+      "{'loss': 0.3721, 'learning_rate': 8.620000000000001e-05, 'epoch': 3.45}\n",
+      "{'loss': 0.4546, 'learning_rate': 8.617500000000001e-05, 'epoch': 3.46}\n",
+      "{'loss': 0.3506, 'learning_rate': 8.615000000000001e-05, 'epoch': 3.46}\n",
+      "{'loss': 0.2477, 'learning_rate': 8.6125e-05, 'epoch': 3.47}\n",
+      "{'loss': 0.2558, 'learning_rate': 8.61e-05, 'epoch': 3.48}\n",
+      "{'loss': 0.3054, 'learning_rate': 8.6075e-05, 'epoch': 3.48}\n",
+      "{'loss': 0.3435, 'learning_rate': 8.605e-05, 'epoch': 3.49}\n",
+      "{'loss': 0.307, 'learning_rate': 8.6025e-05, 'epoch': 3.49}\n",
+      "{'loss': 0.3697, 'learning_rate': 8.6e-05, 'epoch': 3.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f01b1059d6f64d7aa55181e2a30d7337",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.32972225546836853, 'eval_mean_iou': 0.3029759564154746, 'eval_mean_accuracy': 0.359331087951212, 'eval_overall_accuracy': 0.6413419447395697, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.8349685729712637, 'eval_accuracy_RV': 0.5395096287838327, 'eval_accuracy_RA': 0.574463534899486, 'eval_accuracy_LA': 0.6800935105207911, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.22139325923787528, 'eval_accuracy_VSD': 0.19845863196089603, 'eval_accuracy_AK': 0.5444237411379749, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7708035428449472, 'eval_iou_RV': 0.520807838977401, 'eval_iou_RA': 0.5245149690891808, 'eval_iou_LA': 0.61422390757806, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2065792907228297, 'eval_iou_VSD': 0.18757705879852046, 'eval_iou_AK': 0.5082289125592812, 'eval_runtime': 4.3682, 'eval_samples_per_second': 18.543, 'eval_steps_per_second': 9.386, 'epoch': 3.5}\n",
+      "{'loss': 0.2393, 'learning_rate': 8.5975e-05, 'epoch': 3.51}\n",
+      "{'loss': 0.3452, 'learning_rate': 8.595e-05, 'epoch': 3.51}\n",
+      "{'loss': 0.2883, 'learning_rate': 8.5925e-05, 'epoch': 3.52}\n",
+      "{'loss': 0.2405, 'learning_rate': 8.59e-05, 'epoch': 3.52}\n",
+      "{'loss': 0.6067, 'learning_rate': 8.5875e-05, 'epoch': 3.53}\n",
+      "{'loss': 0.1794, 'learning_rate': 8.585000000000001e-05, 'epoch': 3.54}\n",
+      "{'loss': 0.3548, 'learning_rate': 8.5825e-05, 'epoch': 3.54}\n",
+      "{'loss': 0.3048, 'learning_rate': 8.58e-05, 'epoch': 3.55}\n",
+      "{'loss': 0.5544, 'learning_rate': 8.577500000000001e-05, 'epoch': 3.56}\n",
+      "{'loss': 0.2838, 'learning_rate': 8.575000000000001e-05, 'epoch': 3.56}\n",
+      "{'loss': 0.4499, 'learning_rate': 8.5725e-05, 'epoch': 3.57}\n",
+      "{'loss': 0.2866, 'learning_rate': 8.57e-05, 'epoch': 3.58}\n",
+      "{'loss': 0.3087, 'learning_rate': 8.567500000000001e-05, 'epoch': 3.58}\n",
+      "{'loss': 0.2184, 'learning_rate': 8.565000000000001e-05, 'epoch': 3.59}\n",
+      "{'loss': 0.2853, 'learning_rate': 8.5625e-05, 'epoch': 3.59}\n",
+      "{'loss': 0.3391, 'learning_rate': 8.560000000000001e-05, 'epoch': 3.6}\n",
+      "{'loss': 0.6617, 'learning_rate': 8.5575e-05, 'epoch': 3.61}\n",
+      "{'loss': 0.2192, 'learning_rate': 8.555e-05, 'epoch': 3.61}\n",
+      "{'loss': 0.3129, 'learning_rate': 8.5525e-05, 'epoch': 3.62}\n",
+      "{'loss': 0.238, 'learning_rate': 8.55e-05, 'epoch': 3.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "491d77b472624594a560afbfb6cc550d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3479980230331421, 'eval_mean_iou': 0.19623105801426355, 'eval_mean_accuracy': 0.22496110889114082, 'eval_overall_accuracy': 0.4145863041206217, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.5486089773612035, 'eval_accuracy_RV': 0.2977847965278673, 'eval_accuracy_RA': 0.46552218088497577, 'eval_accuracy_LA': 0.47038776336281124, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.13764795034642033, 'eval_accuracy_VSD': 0.10696614388100878, 'eval_accuracy_AK': 0.22269327654712132, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.5282736086175942, 'eval_iou_RV': 0.2923526619908241, 'eval_iou_RA': 0.4420867286038086, 'eval_iou_LA': 0.4435030943806306, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.12993383235827607, 'eval_iou_VSD': 0.1030232574931585, 'eval_iou_AK': 0.21936845471260694, 'eval_runtime': 4.3791, 'eval_samples_per_second': 18.497, 'eval_steps_per_second': 9.363, 'epoch': 3.62}\n",
+      "{'loss': 0.7509, 'learning_rate': 8.5475e-05, 'epoch': 3.63}\n",
+      "{'loss': 0.3258, 'learning_rate': 8.545e-05, 'epoch': 3.64}\n",
+      "{'loss': 0.1804, 'learning_rate': 8.5425e-05, 'epoch': 3.64}\n",
+      "{'loss': 0.2488, 'learning_rate': 8.54e-05, 'epoch': 3.65}\n",
+      "{'loss': 0.2387, 'learning_rate': 8.5375e-05, 'epoch': 3.66}\n",
+      "{'loss': 0.3187, 'learning_rate': 8.535e-05, 'epoch': 3.66}\n",
+      "{'loss': 0.2364, 'learning_rate': 8.5325e-05, 'epoch': 3.67}\n",
+      "{'loss': 0.3429, 'learning_rate': 8.53e-05, 'epoch': 3.67}\n",
+      "{'loss': 0.2382, 'learning_rate': 8.5275e-05, 'epoch': 3.68}\n",
+      "{'loss': 0.2742, 'learning_rate': 8.525000000000001e-05, 'epoch': 3.69}\n",
+      "{'loss': 0.4123, 'learning_rate': 8.5225e-05, 'epoch': 3.69}\n",
+      "{'loss': 0.4898, 'learning_rate': 8.52e-05, 'epoch': 3.7}\n",
+      "{'loss': 0.2099, 'learning_rate': 8.517500000000001e-05, 'epoch': 3.71}\n",
+      "{'loss': 0.3889, 'learning_rate': 8.515000000000001e-05, 'epoch': 3.71}\n",
+      "{'loss': 0.3733, 'learning_rate': 8.5125e-05, 'epoch': 3.72}\n",
+      "{'loss': 0.2977, 'learning_rate': 8.510000000000001e-05, 'epoch': 3.73}\n",
+      "{'loss': 0.2746, 'learning_rate': 8.507500000000001e-05, 'epoch': 3.73}\n",
+      "{'loss': 0.3086, 'learning_rate': 8.505000000000001e-05, 'epoch': 3.74}\n",
+      "{'loss': 0.3713, 'learning_rate': 8.502499999999999e-05, 'epoch': 3.74}\n",
+      "{'loss': 0.3002, 'learning_rate': 8.5e-05, 'epoch': 3.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "46c2f0d28b484e2c88a40ce7b5d3153f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.35211557149887085, 'eval_mean_iou': 0.36926221872376286, 'eval_mean_accuracy': 0.4506885224431472, 'eval_overall_accuracy': 0.7161598025702224, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.8298107815441157, 'eval_accuracy_RV': 0.5896041670503447, 'eval_accuracy_RA': 0.7604508808599582, 'eval_accuracy_LA': 0.7990449989366009, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4433368215935335, 'eval_accuracy_VSD': 0.430525984346418, 'eval_accuracy_AK': 0.6541115901005012, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7667579276835115, 'eval_iou_RV': 0.5574258345158604, 'eval_iou_RA': 0.6505950685688148, 'eval_iou_LA': 0.7037596529179305, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3842989747960931, 'eval_iou_VSD': 0.3818766998490501, 'eval_iou_AK': 0.6171702476301322, 'eval_runtime': 4.3157, 'eval_samples_per_second': 18.769, 'eval_steps_per_second': 9.5, 'epoch': 3.75}\n",
+      "{'loss': 0.3663, 'learning_rate': 8.4975e-05, 'epoch': 3.76}\n",
+      "{'loss': 0.2785, 'learning_rate': 8.495e-05, 'epoch': 3.76}\n",
+      "{'loss': 0.303, 'learning_rate': 8.4925e-05, 'epoch': 3.77}\n",
+      "{'loss': 0.3177, 'learning_rate': 8.49e-05, 'epoch': 3.77}\n",
+      "{'loss': 0.2953, 'learning_rate': 8.4875e-05, 'epoch': 3.78}\n",
+      "{'loss': 0.3381, 'learning_rate': 8.485e-05, 'epoch': 3.79}\n",
+      "{'loss': 0.2893, 'learning_rate': 8.4825e-05, 'epoch': 3.79}\n",
+      "{'loss': 0.3661, 'learning_rate': 8.48e-05, 'epoch': 3.8}\n",
+      "{'loss': 0.2717, 'learning_rate': 8.4775e-05, 'epoch': 3.81}\n",
+      "{'loss': 0.2083, 'learning_rate': 8.475000000000001e-05, 'epoch': 3.81}\n",
+      "{'loss': 0.3275, 'learning_rate': 8.4725e-05, 'epoch': 3.82}\n",
+      "{'loss': 0.4176, 'learning_rate': 8.47e-05, 'epoch': 3.83}\n",
+      "{'loss': 0.2469, 'learning_rate': 8.4675e-05, 'epoch': 3.83}\n",
+      "{'loss': 0.2414, 'learning_rate': 8.465000000000001e-05, 'epoch': 3.84}\n",
+      "{'loss': 0.6318, 'learning_rate': 8.4625e-05, 'epoch': 3.84}\n",
+      "{'loss': 0.4499, 'learning_rate': 8.46e-05, 'epoch': 3.85}\n",
+      "{'loss': 0.9291, 'learning_rate': 8.457500000000001e-05, 'epoch': 3.86}\n",
+      "{'loss': 0.32, 'learning_rate': 8.455000000000001e-05, 'epoch': 3.86}\n",
+      "{'loss': 0.2897, 'learning_rate': 8.4525e-05, 'epoch': 3.87}\n",
+      "{'loss': 0.3223, 'learning_rate': 8.450000000000001e-05, 'epoch': 3.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c52844b4efa547168713eb2a6766caf5",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3379614055156708, 'eval_mean_iou': 0.20594097822942875, 'eval_mean_accuracy': 0.23589997249580744, 'eval_overall_accuracy': 0.4452924336617338, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6356135206326573, 'eval_accuracy_RV': 0.3027188959894903, 'eval_accuracy_RA': 0.37355241177277604, 'eval_accuracy_LA': 0.5003035833121797, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.13203666281755197, 'eval_accuracy_VSD': 0.12877470237202746, 'eval_accuracy_AK': 0.28599994806139145, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6037373909101212, 'eval_iou_RV': 0.29807927704652953, 'eval_iou_RA': 0.3641133449098429, 'eval_iou_LA': 0.47007624164621364, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.12425713994634428, 'eval_iou_VSD': 0.12287189905290566, 'eval_iou_AK': 0.282215467011759, 'eval_runtime': 4.351, 'eval_samples_per_second': 18.616, 'eval_steps_per_second': 9.423, 'epoch': 3.88}\n",
+      "{'loss': 0.2256, 'learning_rate': 8.447500000000001e-05, 'epoch': 3.88}\n",
+      "{'loss': 0.2234, 'learning_rate': 8.445e-05, 'epoch': 3.89}\n",
+      "{'loss': 0.495, 'learning_rate': 8.442499999999999e-05, 'epoch': 3.89}\n",
+      "{'loss': 0.2397, 'learning_rate': 8.44e-05, 'epoch': 3.9}\n",
+      "{'loss': 0.2782, 'learning_rate': 8.4375e-05, 'epoch': 3.91}\n",
+      "{'loss': 0.2632, 'learning_rate': 8.435e-05, 'epoch': 3.91}\n",
+      "{'loss': 0.2748, 'learning_rate': 8.4325e-05, 'epoch': 3.92}\n",
+      "{'loss': 0.3433, 'learning_rate': 8.43e-05, 'epoch': 3.92}\n",
+      "{'loss': 0.2521, 'learning_rate': 8.4275e-05, 'epoch': 3.93}\n",
+      "{'loss': 0.3816, 'learning_rate': 8.425e-05, 'epoch': 3.94}\n",
+      "{'loss': 0.2341, 'learning_rate': 8.422500000000001e-05, 'epoch': 3.94}\n",
+      "{'loss': 0.227, 'learning_rate': 8.42e-05, 'epoch': 3.95}\n",
+      "{'loss': 0.2502, 'learning_rate': 8.4175e-05, 'epoch': 3.96}\n",
+      "{'loss': 0.2587, 'learning_rate': 8.415000000000001e-05, 'epoch': 3.96}\n",
+      "{'loss': 0.2642, 'learning_rate': 8.412500000000001e-05, 'epoch': 3.97}\n",
+      "{'loss': 0.1812, 'learning_rate': 8.41e-05, 'epoch': 3.98}\n",
+      "{'loss': 0.2512, 'learning_rate': 8.4075e-05, 'epoch': 3.98}\n",
+      "{'loss': 0.2497, 'learning_rate': 8.405000000000001e-05, 'epoch': 3.99}\n",
+      "{'loss': 0.3293, 'learning_rate': 8.402500000000001e-05, 'epoch': 3.99}\n",
+      "{'loss': 0.2222, 'learning_rate': 8.4e-05, 'epoch': 4.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "84dbaf63bd6540c586ee908c45e6e605",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.32455816864967346, 'eval_mean_iou': 0.27266821346582903, 'eval_mean_accuracy': 0.3171556734372646, 'eval_overall_accuracy': 0.5466006980583764, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7352545037452904, 'eval_accuracy_RV': 0.3043272742898887, 'eval_accuracy_RA': 0.5282052730544817, 'eval_accuracy_LA': 0.6103653976769874, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.20499242205542725, 'eval_accuracy_VSD': 0.2668605871592647, 'eval_accuracy_AK': 0.5215512763913055, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6901712527993179, 'eval_iou_RV': 0.2990583167940543, 'eval_iou_RA': 0.5001642977227572, 'eval_iou_LA': 0.5642354642359398, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.1896427975296278, 'eval_iou_VSD': 0.24783295852508894, 'eval_iou_AK': 0.5082452605173335, 'eval_runtime': 4.3216, 'eval_samples_per_second': 18.743, 'eval_steps_per_second': 9.487, 'epoch': 4.0}\n",
+      "{'loss': 0.3092, 'learning_rate': 8.397500000000001e-05, 'epoch': 4.01}\n",
+      "{'loss': 0.1761, 'learning_rate': 8.395000000000001e-05, 'epoch': 4.01}\n",
+      "{'loss': 0.3936, 'learning_rate': 8.392500000000001e-05, 'epoch': 4.02}\n",
+      "{'loss': 0.5002, 'learning_rate': 8.39e-05, 'epoch': 4.03}\n",
+      "{'loss': 0.1449, 'learning_rate': 8.3875e-05, 'epoch': 4.03}\n",
+      "{'loss': 0.4488, 'learning_rate': 8.385e-05, 'epoch': 4.04}\n",
+      "{'loss': 0.2447, 'learning_rate': 8.3825e-05, 'epoch': 4.04}\n",
+      "{'loss': 0.2419, 'learning_rate': 8.38e-05, 'epoch': 4.05}\n",
+      "{'loss': 0.3567, 'learning_rate': 8.3775e-05, 'epoch': 4.06}\n",
+      "{'loss': 0.2805, 'learning_rate': 8.375e-05, 'epoch': 4.06}\n",
+      "{'loss': 0.1778, 'learning_rate': 8.3725e-05, 'epoch': 4.07}\n",
+      "{'loss': 0.3077, 'learning_rate': 8.37e-05, 'epoch': 4.08}\n",
+      "{'loss': 0.2587, 'learning_rate': 8.3675e-05, 'epoch': 4.08}\n",
+      "{'loss': 0.251, 'learning_rate': 8.365e-05, 'epoch': 4.09}\n",
+      "{'loss': 0.245, 'learning_rate': 8.362500000000001e-05, 'epoch': 4.09}\n",
+      "{'loss': 0.314, 'learning_rate': 8.36e-05, 'epoch': 4.1}\n",
+      "{'loss': 0.2829, 'learning_rate': 8.3575e-05, 'epoch': 4.11}\n",
+      "{'loss': 0.4327, 'learning_rate': 8.355000000000001e-05, 'epoch': 4.11}\n",
+      "{'loss': 0.367, 'learning_rate': 8.352500000000001e-05, 'epoch': 4.12}\n",
+      "{'loss': 0.3673, 'learning_rate': 8.35e-05, 'epoch': 4.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "dd9d1e0b753e4c3993ef60e71449ba51",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.33214759826660156, 'eval_mean_iou': 0.23842838985536338, 'eval_mean_accuracy': 0.27526672780677497, 'eval_overall_accuracy': 0.4744551963803098, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6298024288454482, 'eval_accuracy_RV': 0.2919897235676532, 'eval_accuracy_RA': 0.3667573216692357, 'eval_accuracy_LA': 0.5894112884967652, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.13267717956120093, 'eval_accuracy_VSD': 0.2825966353794944, 'eval_accuracy_AK': 0.4594327005479523, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6052217985111904, 'eval_iou_RV': 0.28677132241557324, 'eval_iou_RA': 0.3572735545165278, 'eval_iou_LA': 0.5455596126369265, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.1281209164561373, 'eval_iou_VSD': 0.25841857021416625, 'eval_iou_AK': 0.4413465136584757, 'eval_runtime': 4.3315, 'eval_samples_per_second': 18.7, 'eval_steps_per_second': 9.465, 'epoch': 4.12}\n",
+      "{'loss': 0.3329, 'learning_rate': 8.347500000000001e-05, 'epoch': 4.13}\n",
+      "{'loss': 0.2044, 'learning_rate': 8.345000000000001e-05, 'epoch': 4.14}\n",
+      "{'loss': 0.2874, 'learning_rate': 8.342500000000001e-05, 'epoch': 4.14}\n",
+      "{'loss': 0.2373, 'learning_rate': 8.34e-05, 'epoch': 4.15}\n",
+      "{'loss': 0.2156, 'learning_rate': 8.337500000000001e-05, 'epoch': 4.16}\n",
+      "{'loss': 0.2352, 'learning_rate': 8.335e-05, 'epoch': 4.16}\n",
+      "{'loss': 0.2471, 'learning_rate': 8.3325e-05, 'epoch': 4.17}\n",
+      "{'loss': 0.3619, 'learning_rate': 8.33e-05, 'epoch': 4.17}\n",
+      "{'loss': 0.5428, 'learning_rate': 8.3275e-05, 'epoch': 4.18}\n",
+      "{'loss': 0.2628, 'learning_rate': 8.325e-05, 'epoch': 4.19}\n",
+      "{'loss': 0.2867, 'learning_rate': 8.3225e-05, 'epoch': 4.19}\n",
+      "{'loss': 0.1326, 'learning_rate': 8.32e-05, 'epoch': 4.2}\n",
+      "{'loss': 0.2261, 'learning_rate': 8.3175e-05, 'epoch': 4.21}\n",
+      "{'loss': 0.2625, 'learning_rate': 8.315e-05, 'epoch': 4.21}\n",
+      "{'loss': 0.2123, 'learning_rate': 8.312500000000001e-05, 'epoch': 4.22}\n",
+      "{'loss': 0.2511, 'learning_rate': 8.31e-05, 'epoch': 4.22}\n",
+      "{'loss': 0.6347, 'learning_rate': 8.3075e-05, 'epoch': 4.23}\n",
+      "{'loss': 0.3432, 'learning_rate': 8.305e-05, 'epoch': 4.24}\n",
+      "{'loss': 0.1932, 'learning_rate': 8.302500000000001e-05, 'epoch': 4.24}\n",
+      "{'loss': 0.5374, 'learning_rate': 8.3e-05, 'epoch': 4.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8ea919544da646e98dc439b4e630f0be",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.296, 'learning_rate': 8.2975e-05, 'epoch': 4.26}\n",
+      "{'loss': 0.3766, 'learning_rate': 8.295000000000001e-05, 'epoch': 4.26}\n",
+      "{'loss': 0.2216, 'learning_rate': 8.292500000000001e-05, 'epoch': 4.27}\n",
+      "{'loss': 0.3161, 'learning_rate': 8.29e-05, 'epoch': 4.28}\n",
+      "{'loss': 0.4472, 'learning_rate': 8.287500000000001e-05, 'epoch': 4.28}\n",
+      "{'loss': 0.3197, 'learning_rate': 8.285000000000001e-05, 'epoch': 4.29}\n",
+      "{'loss': 0.2166, 'learning_rate': 8.282500000000001e-05, 'epoch': 4.29}\n",
+      "{'loss': 0.4352, 'learning_rate': 8.28e-05, 'epoch': 4.3}\n",
+      "{'loss': 0.2753, 'learning_rate': 8.2775e-05, 'epoch': 4.31}\n",
+      "{'loss': 0.1984, 'learning_rate': 8.275e-05, 'epoch': 4.31}\n",
+      "{'loss': 0.3302, 'learning_rate': 8.2725e-05, 'epoch': 4.32}\n",
+      "{'loss': 0.2668, 'learning_rate': 8.27e-05, 'epoch': 4.33}\n",
+      "{'loss': 0.1739, 'learning_rate': 8.2675e-05, 'epoch': 4.33}\n",
+      "{'loss': 0.4057, 'learning_rate': 8.265e-05, 'epoch': 4.34}\n",
+      "{'loss': 0.2717, 'learning_rate': 8.2625e-05, 'epoch': 4.34}\n",
+      "{'loss': 0.3238, 'learning_rate': 8.26e-05, 'epoch': 4.35}\n",
+      "{'loss': 0.2637, 'learning_rate': 8.2575e-05, 'epoch': 4.36}\n",
+      "{'loss': 0.4214, 'learning_rate': 8.255e-05, 'epoch': 4.36}\n",
+      "{'loss': 0.2339, 'learning_rate': 8.252500000000001e-05, 'epoch': 4.37}\n",
+      "{'loss': 0.2427, 'learning_rate': 8.25e-05, 'epoch': 4.38}\n"
+     ]
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+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "b9ac8fb4fc924348b8b8768da3cb1f16",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.501, 'learning_rate': 8.2475e-05, 'epoch': 4.38}\n",
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+      "{'loss': 0.2953, 'learning_rate': 8.227500000000001e-05, 'epoch': 4.43}\n",
+      "{'loss': 0.1937, 'learning_rate': 8.225000000000001e-05, 'epoch': 4.44}\n",
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+      "{'loss': 0.365, 'learning_rate': 8.2125e-05, 'epoch': 4.47}\n",
+      "{'loss': 0.4011, 'learning_rate': 8.21e-05, 'epoch': 4.47}\n",
+      "{'loss': 0.2544, 'learning_rate': 8.2075e-05, 'epoch': 4.48}\n",
+      "{'loss': 0.137, 'learning_rate': 8.205e-05, 'epoch': 4.49}\n",
+      "{'loss': 0.294, 'learning_rate': 8.2025e-05, 'epoch': 4.49}\n",
+      "{'loss': 0.6031, 'learning_rate': 8.2e-05, 'epoch': 4.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "eeb65ac502a54d578de595b14283ee24",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.32673004269599915, 'eval_mean_iou': 0.23417898365027756, 'eval_mean_accuracy': 0.2687907810373651, 'eval_overall_accuracy': 0.46150535877733756, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6092861127435334, 'eval_accuracy_RV': 0.3110968894454778, 'eval_accuracy_RA': 0.4576759500617369, 'eval_accuracy_LA': 0.4812087075240637, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.18233978060046188, 'eval_accuracy_VSD': 0.22998320688517707, 'eval_accuracy_AK': 0.4163171631132002, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.5864085168203181, 'eval_iou_RV': 0.30609850383855713, 'eval_iou_RA': 0.43619582355882014, 'eval_iou_LA': 0.4545545863414255, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.17139562098265013, 'eval_iou_VSD': 0.2162042159716398, 'eval_iou_AK': 0.40511155263964216, 'eval_runtime': 4.4128, 'eval_samples_per_second': 18.356, 'eval_steps_per_second': 9.291, 'epoch': 4.5}\n",
+      "{'loss': 0.314, 'learning_rate': 8.1975e-05, 'epoch': 4.51}\n",
+      "{'loss': 0.27, 'learning_rate': 8.195e-05, 'epoch': 4.51}\n",
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+      "{'loss': 0.3888, 'learning_rate': 8.19e-05, 'epoch': 4.53}\n",
+      "{'loss': 0.231, 'learning_rate': 8.1875e-05, 'epoch': 4.53}\n",
+      "{'loss': 0.6652, 'learning_rate': 8.185000000000001e-05, 'epoch': 4.54}\n",
+      "{'loss': 0.2273, 'learning_rate': 8.182500000000001e-05, 'epoch': 4.54}\n",
+      "{'loss': 0.1873, 'learning_rate': 8.18e-05, 'epoch': 4.55}\n",
+      "{'loss': 0.2924, 'learning_rate': 8.1775e-05, 'epoch': 4.56}\n",
+      "{'loss': 0.3234, 'learning_rate': 8.175000000000001e-05, 'epoch': 4.56}\n",
+      "{'loss': 0.3377, 'learning_rate': 8.172500000000001e-05, 'epoch': 4.57}\n",
+      "{'loss': 0.2202, 'learning_rate': 8.17e-05, 'epoch': 4.58}\n",
+      "{'loss': 0.2321, 'learning_rate': 8.1675e-05, 'epoch': 4.58}\n",
+      "{'loss': 0.2649, 'learning_rate': 8.165e-05, 'epoch': 4.59}\n",
+      "{'loss': 0.3171, 'learning_rate': 8.1625e-05, 'epoch': 4.59}\n",
+      "{'loss': 0.4985, 'learning_rate': 8.16e-05, 'epoch': 4.6}\n",
+      "{'loss': 0.2193, 'learning_rate': 8.1575e-05, 'epoch': 4.61}\n",
+      "{'loss': 0.2703, 'learning_rate': 8.155e-05, 'epoch': 4.61}\n",
+      "{'loss': 0.3003, 'learning_rate': 8.1525e-05, 'epoch': 4.62}\n",
+      "{'loss': 0.4573, 'learning_rate': 8.15e-05, 'epoch': 4.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1a4df19326814b14aed1e8316b75c21a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.31444498896598816, 'eval_mean_iou': 0.3046253345229009, 'eval_mean_accuracy': 0.357360096425582, 'eval_overall_accuracy': 0.6319508308106435, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.8510102290727609, 'eval_accuracy_RV': 0.5012108878616549, 'eval_accuracy_RA': 0.5467364199075158, 'eval_accuracy_LA': 0.6669227972200688, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.21090141454965358, 'eval_accuracy_VSD': 0.34333673193990466, 'eval_accuracy_AK': 0.4534824837042616, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7889436465860789, 'eval_iou_RV': 0.48205698192413626, 'eval_iou_RA': 0.5132065109320405, 'eval_iou_LA': 0.6114634457012472, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.19850387616645865, 'eval_iou_VSD': 0.31568680163506146, 'eval_iou_AK': 0.44101741680688716, 'eval_runtime': 4.363, 'eval_samples_per_second': 18.565, 'eval_steps_per_second': 9.397, 'epoch': 4.62}\n",
+      "{'loss': 0.2323, 'learning_rate': 8.1475e-05, 'epoch': 4.63}\n",
+      "{'loss': 0.1866, 'learning_rate': 8.145e-05, 'epoch': 4.64}\n",
+      "{'loss': 0.3951, 'learning_rate': 8.1425e-05, 'epoch': 4.64}\n",
+      "{'loss': 0.269, 'learning_rate': 8.14e-05, 'epoch': 4.65}\n",
+      "{'loss': 0.373, 'learning_rate': 8.1375e-05, 'epoch': 4.66}\n",
+      "{'loss': 0.2747, 'learning_rate': 8.135e-05, 'epoch': 4.66}\n",
+      "{'loss': 0.2789, 'learning_rate': 8.132500000000001e-05, 'epoch': 4.67}\n",
+      "{'loss': 0.2103, 'learning_rate': 8.13e-05, 'epoch': 4.67}\n",
+      "{'loss': 0.3098, 'learning_rate': 8.1275e-05, 'epoch': 4.68}\n",
+      "{'loss': 0.1787, 'learning_rate': 8.125000000000001e-05, 'epoch': 4.69}\n",
+      "{'loss': 0.2199, 'learning_rate': 8.122500000000001e-05, 'epoch': 4.69}\n",
+      "{'loss': 0.2627, 'learning_rate': 8.120000000000001e-05, 'epoch': 4.7}\n",
+      "{'loss': 0.1812, 'learning_rate': 8.1175e-05, 'epoch': 4.71}\n",
+      "{'loss': 0.3126, 'learning_rate': 8.115000000000001e-05, 'epoch': 4.71}\n",
+      "{'loss': 0.3361, 'learning_rate': 8.112500000000001e-05, 'epoch': 4.72}\n",
+      "{'loss': 0.2158, 'learning_rate': 8.11e-05, 'epoch': 4.72}\n",
+      "{'loss': 0.1643, 'learning_rate': 8.1075e-05, 'epoch': 4.73}\n",
+      "{'loss': 0.746, 'learning_rate': 8.105e-05, 'epoch': 4.74}\n",
+      "{'loss': 0.2492, 'learning_rate': 8.1025e-05, 'epoch': 4.74}\n",
+      "{'loss': 0.132, 'learning_rate': 8.1e-05, 'epoch': 4.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "123045869bc243e5b2744f8727d1969f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.4079526364803314, 'eval_mean_iou': 0.13630956541720132, 'eval_mean_accuracy': 0.15293319803004968, 'eval_overall_accuracy': 0.2520056195213994, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.264014635121308, 'eval_accuracy_RV': 0.20669349343450155, 'eval_accuracy_RA': 0.34877696448314544, 'eval_accuracy_LA': 0.3485273636619351, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.0749314376443418, 'eval_accuracy_VSD': 0.16949050889135456, 'eval_accuracy_AK': 0.11689757706391046, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.26201428295467244, 'eval_iou_RV': 0.20429712801734143, 'eval_iou_RA': 0.3422963907523424, 'eval_iou_LA': 0.3369526285767348, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.0740140079485306, 'eval_iou_VSD': 0.16335968322326114, 'eval_iou_AK': 0.11647109811633202, 'eval_runtime': 4.3333, 'eval_samples_per_second': 18.693, 'eval_steps_per_second': 9.462, 'epoch': 4.75}\n",
+      "{'loss': 0.3313, 'learning_rate': 8.0975e-05, 'epoch': 4.76}\n",
+      "{'loss': 0.3696, 'learning_rate': 8.095e-05, 'epoch': 4.76}\n",
+      "{'loss': 0.4445, 'learning_rate': 8.0925e-05, 'epoch': 4.77}\n",
+      "{'loss': 0.6093, 'learning_rate': 8.090000000000001e-05, 'epoch': 4.78}\n",
+      "{'loss': 0.2504, 'learning_rate': 8.0875e-05, 'epoch': 4.78}\n",
+      "{'loss': 0.211, 'learning_rate': 8.085e-05, 'epoch': 4.79}\n",
+      "{'loss': 0.2759, 'learning_rate': 8.082500000000001e-05, 'epoch': 4.79}\n",
+      "{'loss': 0.3107, 'learning_rate': 8.080000000000001e-05, 'epoch': 4.8}\n",
+      "{'loss': 0.2639, 'learning_rate': 8.0775e-05, 'epoch': 4.81}\n",
+      "{'loss': 0.1828, 'learning_rate': 8.075e-05, 'epoch': 4.81}\n",
+      "{'loss': 0.5641, 'learning_rate': 8.072500000000001e-05, 'epoch': 4.82}\n",
+      "{'loss': 0.2447, 'learning_rate': 8.070000000000001e-05, 'epoch': 4.83}\n",
+      "{'loss': 0.3497, 'learning_rate': 8.0675e-05, 'epoch': 4.83}\n",
+      "{'loss': 0.2534, 'learning_rate': 8.065000000000001e-05, 'epoch': 4.84}\n",
+      "{'loss': 0.3257, 'learning_rate': 8.062500000000001e-05, 'epoch': 4.84}\n",
+      "{'loss': 0.2342, 'learning_rate': 8.060000000000001e-05, 'epoch': 4.85}\n",
+      "{'loss': 0.3662, 'learning_rate': 8.057500000000001e-05, 'epoch': 4.86}\n",
+      "{'loss': 0.5188, 'learning_rate': 8.055e-05, 'epoch': 4.86}\n",
+      "{'loss': 0.5506, 'learning_rate': 8.0525e-05, 'epoch': 4.87}\n",
+      "{'loss': 0.1884, 'learning_rate': 8.05e-05, 'epoch': 4.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "275d31d5da2d45f0957ce75a4da3e25e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3223598599433899, 'eval_mean_iou': 0.3076832914296856, 'eval_mean_accuracy': 0.3650079074192528, 'eval_overall_accuracy': 0.610604168875598, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7701464108752136, 'eval_accuracy_RV': 0.44444495601515066, 'eval_accuracy_RA': 0.6484307538353522, 'eval_accuracy_LA': 0.6579147771321153, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.31780456120092376, 'eval_accuracy_VSD': 0.31459351665817015, 'eval_accuracy_AK': 0.49674409847560186, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7106408572197338, 'eval_iou_RV': 0.4326633608782501, 'eval_iou_RA': 0.5890419243986255, 'eval_iou_LA': 0.6041298195271072, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2781567809993052, 'eval_iou_VSD': 0.28922447066607854, 'eval_iou_AK': 0.4806589920374413, 'eval_runtime': 4.3677, 'eval_samples_per_second': 18.545, 'eval_steps_per_second': 9.387, 'epoch': 4.88}\n",
+      "{'loss': 0.2902, 'learning_rate': 8.0475e-05, 'epoch': 4.88}\n",
+      "{'loss': 0.2982, 'learning_rate': 8.045e-05, 'epoch': 4.89}\n",
+      "{'loss': 0.4155, 'learning_rate': 8.0425e-05, 'epoch': 4.89}\n",
+      "{'loss': 0.2626, 'learning_rate': 8.04e-05, 'epoch': 4.9}\n",
+      "{'loss': 0.2871, 'learning_rate': 8.0375e-05, 'epoch': 4.91}\n",
+      "{'loss': 0.2311, 'learning_rate': 8.035e-05, 'epoch': 4.91}\n",
+      "{'loss': 0.3255, 'learning_rate': 8.0325e-05, 'epoch': 4.92}\n",
+      "{'loss': 0.2764, 'learning_rate': 8.030000000000001e-05, 'epoch': 4.92}\n",
+      "{'loss': 0.1666, 'learning_rate': 8.0275e-05, 'epoch': 4.93}\n",
+      "{'loss': 0.2431, 'learning_rate': 8.025e-05, 'epoch': 4.94}\n",
+      "{'loss': 0.2549, 'learning_rate': 8.022500000000001e-05, 'epoch': 4.94}\n",
+      "{'loss': 0.3289, 'learning_rate': 8.020000000000001e-05, 'epoch': 4.95}\n",
+      "{'loss': 0.2307, 'learning_rate': 8.0175e-05, 'epoch': 4.96}\n",
+      "{'loss': 0.2709, 'learning_rate': 8.015e-05, 'epoch': 4.96}\n",
+      "{'loss': 0.2851, 'learning_rate': 8.012500000000001e-05, 'epoch': 4.97}\n",
+      "{'loss': 0.2124, 'learning_rate': 8.010000000000001e-05, 'epoch': 4.97}\n",
+      "{'loss': 0.3041, 'learning_rate': 8.0075e-05, 'epoch': 4.98}\n",
+      "{'loss': 0.3229, 'learning_rate': 8.005000000000001e-05, 'epoch': 4.99}\n",
+      "{'loss': 0.2081, 'learning_rate': 8.002500000000001e-05, 'epoch': 4.99}\n",
+      "{'loss': 0.3418, 'learning_rate': 8e-05, 'epoch': 5.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "068d37a49ab940f296896aa097c9ccbf",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3292044997215271, 'eval_mean_iou': 0.2551225318475758, 'eval_mean_accuracy': 0.29818620547725355, 'eval_overall_accuracy': 0.5041010388649303, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.66167841513509, 'eval_accuracy_RV': 0.2642820309766294, 'eval_accuracy_RA': 0.5348127315132392, 'eval_accuracy_LA': 0.6188382878587257, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.28508407909930716, 'eval_accuracy_VSD': 0.24805829609859958, 'eval_accuracy_AK': 0.3691082140909445, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.632987125284127, 'eval_iou_RV': 0.26039088194155674, 'eval_iou_RA': 0.49289884715507626, 'eval_iou_LA': 0.5648274544919442, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2589566671037105, 'eval_iou_VSD': 0.23260456942003516, 'eval_iou_AK': 0.3636823049268836, 'eval_runtime': 4.3256, 'eval_samples_per_second': 18.726, 'eval_steps_per_second': 9.478, 'epoch': 5.0}\n",
+      "{'loss': 0.3168, 'learning_rate': 7.9975e-05, 'epoch': 5.01}\n",
+      "{'loss': 0.2924, 'learning_rate': 7.995e-05, 'epoch': 5.01}\n",
+      "{'loss': 0.3877, 'learning_rate': 7.9925e-05, 'epoch': 5.02}\n",
+      "{'loss': 0.4761, 'learning_rate': 7.99e-05, 'epoch': 5.03}\n",
+      "{'loss': 0.2289, 'learning_rate': 7.9875e-05, 'epoch': 5.03}\n",
+      "{'loss': 0.3842, 'learning_rate': 7.985e-05, 'epoch': 5.04}\n",
+      "{'loss': 0.3, 'learning_rate': 7.9825e-05, 'epoch': 5.04}\n",
+      "{'loss': 0.1963, 'learning_rate': 7.98e-05, 'epoch': 5.05}\n",
+      "{'loss': 0.188, 'learning_rate': 7.9775e-05, 'epoch': 5.06}\n",
+      "{'loss': 0.287, 'learning_rate': 7.975e-05, 'epoch': 5.06}\n",
+      "{'loss': 0.1881, 'learning_rate': 7.9725e-05, 'epoch': 5.07}\n",
+      "{'loss': 0.444, 'learning_rate': 7.970000000000001e-05, 'epoch': 5.08}\n",
+      "{'loss': 0.1982, 'learning_rate': 7.9675e-05, 'epoch': 5.08}\n",
+      "{'loss': 0.6074, 'learning_rate': 7.965e-05, 'epoch': 5.09}\n",
+      "{'loss': 0.4236, 'learning_rate': 7.962500000000001e-05, 'epoch': 5.09}\n",
+      "{'loss': 0.2115, 'learning_rate': 7.960000000000001e-05, 'epoch': 5.1}\n",
+      "{'loss': 0.3584, 'learning_rate': 7.9575e-05, 'epoch': 5.11}\n",
+      "{'loss': 0.3865, 'learning_rate': 7.955e-05, 'epoch': 5.11}\n",
+      "{'loss': 0.189, 'learning_rate': 7.952500000000001e-05, 'epoch': 5.12}\n",
+      "{'loss': 0.2362, 'learning_rate': 7.950000000000001e-05, 'epoch': 5.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9191124c81e2420b95fe1cd8caf5bf90",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3230230212211609, 'eval_mean_iou': 0.23599584816656097, 'eval_mean_accuracy': 0.2704926215135724, 'eval_overall_accuracy': 0.4927678685417158, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6949437833548614, 'eval_accuracy_RV': 0.30046747331135626, 'eval_accuracy_RA': 0.42330102571965816, 'eval_accuracy_LA': 0.5636976104391496, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.1465069284064665, 'eval_accuracy_VSD': 0.21727591687408163, 'eval_accuracy_AK': 0.35873347703015035, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6617291157146631, 'eval_iou_RV': 0.29646404305354285, 'eval_iou_RA': 0.4105549467752035, 'eval_iou_LA': 0.5270740985457415, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.13946378578912114, 'eval_iou_VSD': 0.20581906500110075, 'eval_iou_AK': 0.35484927495279805, 'eval_runtime': 4.3626, 'eval_samples_per_second': 18.567, 'eval_steps_per_second': 9.398, 'epoch': 5.12}\n",
+      "{'loss': 0.3598, 'learning_rate': 7.9475e-05, 'epoch': 5.13}\n",
+      "{'loss': 0.2417, 'learning_rate': 7.945e-05, 'epoch': 5.14}\n",
+      "{'loss': 0.204, 'learning_rate': 7.9425e-05, 'epoch': 5.14}\n",
+      "{'loss': 0.2803, 'learning_rate': 7.94e-05, 'epoch': 5.15}\n",
+      "{'loss': 0.2815, 'learning_rate': 7.9375e-05, 'epoch': 5.16}\n",
+      "{'loss': 0.2489, 'learning_rate': 7.935e-05, 'epoch': 5.16}\n",
+      "{'loss': 0.2394, 'learning_rate': 7.9325e-05, 'epoch': 5.17}\n",
+      "{'loss': 0.3254, 'learning_rate': 7.93e-05, 'epoch': 5.17}\n",
+      "{'loss': 0.3362, 'learning_rate': 7.9275e-05, 'epoch': 5.18}\n",
+      "{'loss': 0.3385, 'learning_rate': 7.925e-05, 'epoch': 5.19}\n",
+      "{'loss': 0.524, 'learning_rate': 7.9225e-05, 'epoch': 5.19}\n",
+      "{'loss': 0.2251, 'learning_rate': 7.920000000000001e-05, 'epoch': 5.2}\n",
+      "{'loss': 0.3082, 'learning_rate': 7.9175e-05, 'epoch': 5.21}\n",
+      "{'loss': 0.1704, 'learning_rate': 7.915e-05, 'epoch': 5.21}\n",
+      "{'loss': 0.2871, 'learning_rate': 7.9125e-05, 'epoch': 5.22}\n",
+      "{'loss': 0.3827, 'learning_rate': 7.910000000000001e-05, 'epoch': 5.22}\n",
+      "{'loss': 0.376, 'learning_rate': 7.9075e-05, 'epoch': 5.23}\n",
+      "{'loss': 0.262, 'learning_rate': 7.905e-05, 'epoch': 5.24}\n",
+      "{'loss': 0.3247, 'learning_rate': 7.902500000000001e-05, 'epoch': 5.24}\n",
+      "{'loss': 0.2219, 'learning_rate': 7.900000000000001e-05, 'epoch': 5.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "45e6c083029943958684da183434af80",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.31353962421417236, 'eval_mean_iou': 0.31182561897144534, 'eval_mean_accuracy': 0.366355865420619, 'eval_overall_accuracy': 0.6044274558087502, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7101270505129452, 'eval_accuracy_RV': 0.5676316936469057, 'eval_accuracy_RA': 0.6115076707044459, 'eval_accuracy_LA': 0.6194128664439246, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.2686832419168591, 'eval_accuracy_VSD': 0.3116772123429394, 'eval_accuracy_AK': 0.5745189186381697, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6759174274480407, 'eval_iou_RV': 0.5432029502519493, 'eval_iou_RA': 0.5666672275474739, 'eval_iou_LA': 0.5726381885643611, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.24827235518210086, 'eval_iou_VSD': 0.2876675362058109, 'eval_iou_AK': 0.5357161234861625, 'eval_runtime': 4.2703, 'eval_samples_per_second': 18.968, 'eval_steps_per_second': 9.601, 'epoch': 5.25}\n",
+      "{'loss': 0.3487, 'learning_rate': 7.8975e-05, 'epoch': 5.26}\n",
+      "{'loss': 0.543, 'learning_rate': 7.895000000000001e-05, 'epoch': 5.26}\n",
+      "{'loss': 0.4075, 'learning_rate': 7.892500000000001e-05, 'epoch': 5.27}\n",
+      "{'loss': 0.3203, 'learning_rate': 7.890000000000001e-05, 'epoch': 5.28}\n",
+      "{'loss': 0.2733, 'learning_rate': 7.887499999999999e-05, 'epoch': 5.28}\n",
+      "{'loss': 0.2164, 'learning_rate': 7.885e-05, 'epoch': 5.29}\n",
+      "{'loss': 0.1651, 'learning_rate': 7.8825e-05, 'epoch': 5.29}\n",
+      "{'loss': 0.2718, 'learning_rate': 7.88e-05, 'epoch': 5.3}\n",
+      "{'loss': 0.3241, 'learning_rate': 7.8775e-05, 'epoch': 5.31}\n",
+      "{'loss': 0.3131, 'learning_rate': 7.875e-05, 'epoch': 5.31}\n",
+      "{'loss': 0.4114, 'learning_rate': 7.8725e-05, 'epoch': 5.32}\n",
+      "{'loss': 0.2013, 'learning_rate': 7.87e-05, 'epoch': 5.33}\n",
+      "{'loss': 0.4068, 'learning_rate': 7.8675e-05, 'epoch': 5.33}\n",
+      "{'loss': 0.1947, 'learning_rate': 7.865e-05, 'epoch': 5.34}\n",
+      "{'loss': 0.242, 'learning_rate': 7.8625e-05, 'epoch': 5.34}\n",
+      "{'loss': 0.2552, 'learning_rate': 7.860000000000001e-05, 'epoch': 5.35}\n",
+      "{'loss': 0.244, 'learning_rate': 7.8575e-05, 'epoch': 5.36}\n",
+      "{'loss': 0.2363, 'learning_rate': 7.855e-05, 'epoch': 5.36}\n",
+      "{'loss': 0.3827, 'learning_rate': 7.8525e-05, 'epoch': 5.37}\n",
+      "{'loss': 0.1984, 'learning_rate': 7.850000000000001e-05, 'epoch': 5.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "4f75e6654cc74607822f8156c392c5ea",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.357186496257782, 'eval_mean_iou': 0.2040820843734367, 'eval_mean_accuracy': 0.23543997530427668, 'eval_overall_accuracy': 0.42822045964525823, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6304870518255121, 'eval_accuracy_RV': 0.13902496669674702, 'eval_accuracy_RA': 0.43386488907539966, 'eval_accuracy_LA': 0.5503433750231547, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.1910273527713626, 'eval_accuracy_VSD': 0.20670525084715266, 'eval_accuracy_AK': 0.20294686680343835, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6023201948718606, 'eval_iou_RV': 0.13789549796399894, 'eval_iou_RA': 0.41925427694107326, 'eval_iou_LA': 0.5171210634124801, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.1781597590320898, 'eval_iou_VSD': 0.19259166125325677, 'eval_iou_AK': 0.1975604746330442, 'eval_runtime': 4.3198, 'eval_samples_per_second': 18.751, 'eval_steps_per_second': 9.491, 'epoch': 5.38}\n",
+      "{'loss': 0.2585, 'learning_rate': 7.8475e-05, 'epoch': 5.38}\n",
+      "{'loss': 0.3253, 'learning_rate': 7.845e-05, 'epoch': 5.39}\n",
+      "{'loss': 0.331, 'learning_rate': 7.842500000000001e-05, 'epoch': 5.39}\n",
+      "{'loss': 0.6223, 'learning_rate': 7.840000000000001e-05, 'epoch': 5.4}\n",
+      "{'loss': 0.2411, 'learning_rate': 7.8375e-05, 'epoch': 5.41}\n",
+      "{'loss': 0.4733, 'learning_rate': 7.835000000000001e-05, 'epoch': 5.41}\n",
+      "{'loss': 0.1882, 'learning_rate': 7.8325e-05, 'epoch': 5.42}\n",
+      "{'loss': 0.2423, 'learning_rate': 7.83e-05, 'epoch': 5.42}\n",
+      "{'loss': 0.3745, 'learning_rate': 7.827499999999999e-05, 'epoch': 5.43}\n",
+      "{'loss': 0.2189, 'learning_rate': 7.825e-05, 'epoch': 5.44}\n",
+      "{'loss': 0.2288, 'learning_rate': 7.8225e-05, 'epoch': 5.44}\n",
+      "{'loss': 0.2838, 'learning_rate': 7.82e-05, 'epoch': 5.45}\n",
+      "{'loss': 0.226, 'learning_rate': 7.8175e-05, 'epoch': 5.46}\n",
+      "{'loss': 0.2247, 'learning_rate': 7.815e-05, 'epoch': 5.46}\n",
+      "{'loss': 0.5352, 'learning_rate': 7.8125e-05, 'epoch': 5.47}\n",
+      "{'loss': 0.1813, 'learning_rate': 7.81e-05, 'epoch': 5.47}\n",
+      "{'loss': 0.1922, 'learning_rate': 7.807500000000001e-05, 'epoch': 5.48}\n",
+      "{'loss': 0.5477, 'learning_rate': 7.805e-05, 'epoch': 5.49}\n",
+      "{'loss': 0.2289, 'learning_rate': 7.8025e-05, 'epoch': 5.49}\n",
+      "{'loss': 0.4754, 'learning_rate': 7.800000000000001e-05, 'epoch': 5.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "13122a705441425098e913c2ea55bb88",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3094979226589203, 'eval_mean_iou': 0.30815848135172114, 'eval_mean_accuracy': 0.3617799883962288, 'eval_overall_accuracy': 0.5946479306009663, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7175542403369717, 'eval_accuracy_RV': 0.4894595971687631, 'eval_accuracy_RA': 0.595302752737808, 'eval_accuracy_LA': 0.6631117117982424, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.32622149249422633, 'eval_accuracy_VSD': 0.31457102587938945, 'eval_accuracy_AK': 0.5115790635468875, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6830353054593444, 'eval_iou_RV': 0.4767005267343071, 'eval_iou_RA': 0.5516361399697506, 'eval_iou_LA': 0.6041784196766092, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2881744937561263, 'eval_iou_VSD': 0.2897249822201661, 'eval_iou_AK': 0.4962934270526289, 'eval_runtime': 4.3701, 'eval_samples_per_second': 18.535, 'eval_steps_per_second': 9.382, 'epoch': 5.5}\n",
+      "{'loss': 0.2412, 'learning_rate': 7.797500000000001e-05, 'epoch': 5.51}\n",
+      "{'loss': 0.373, 'learning_rate': 7.795e-05, 'epoch': 5.51}\n",
+      "{'loss': 0.32, 'learning_rate': 7.792500000000001e-05, 'epoch': 5.52}\n",
+      "{'loss': 0.1921, 'learning_rate': 7.790000000000001e-05, 'epoch': 5.53}\n",
+      "{'loss': 0.2145, 'learning_rate': 7.787500000000001e-05, 'epoch': 5.53}\n",
+      "{'loss': 0.1557, 'learning_rate': 7.785e-05, 'epoch': 5.54}\n",
+      "{'loss': 0.1945, 'learning_rate': 7.782500000000001e-05, 'epoch': 5.54}\n",
+      "{'loss': 0.1833, 'learning_rate': 7.780000000000001e-05, 'epoch': 5.55}\n",
+      "{'loss': 0.3183, 'learning_rate': 7.7775e-05, 'epoch': 5.56}\n",
+      "{'loss': 0.2355, 'learning_rate': 7.775e-05, 'epoch': 5.56}\n",
+      "{'loss': 0.172, 'learning_rate': 7.7725e-05, 'epoch': 5.57}\n",
+      "{'loss': 0.3243, 'learning_rate': 7.77e-05, 'epoch': 5.58}\n",
+      "{'loss': 0.295, 'learning_rate': 7.7675e-05, 'epoch': 5.58}\n",
+      "{'loss': 0.314, 'learning_rate': 7.765e-05, 'epoch': 5.59}\n",
+      "{'loss': 0.1493, 'learning_rate': 7.7625e-05, 'epoch': 5.59}\n",
+      "{'loss': 0.2241, 'learning_rate': 7.76e-05, 'epoch': 5.6}\n",
+      "{'loss': 0.3932, 'learning_rate': 7.757500000000002e-05, 'epoch': 5.61}\n",
+      "{'loss': 0.3878, 'learning_rate': 7.755e-05, 'epoch': 5.61}\n",
+      "{'loss': 0.3105, 'learning_rate': 7.7525e-05, 'epoch': 5.62}\n",
+      "{'loss': 0.2421, 'learning_rate': 7.75e-05, 'epoch': 5.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2384a244d0cc45d381e7f88ba8ddea9c",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.33591312170028687, 'eval_mean_iou': 0.24221466713462333, 'eval_mean_accuracy': 0.2792253900561723, 'eval_overall_accuracy': 0.4918209131884563, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6354837554926451, 'eval_accuracy_RV': 0.33695064979711103, 'eval_accuracy_RA': 0.47855350124684254, 'eval_accuracy_LA': 0.5971638114970602, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.14139181581986143, 'eval_accuracy_VSD': 0.22930098659549586, 'eval_accuracy_AK': 0.3734093801127068, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6139253730267945, 'eval_iou_RV': 0.33014992255755554, 'eval_iou_RA': 0.46219918548685673, 'eval_iou_LA': 0.5514501843615768, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.13545889043499304, 'eval_iou_VSD': 0.21452568823426266, 'eval_iou_AK': 0.35665209437881745, 'eval_runtime': 4.303, 'eval_samples_per_second': 18.824, 'eval_steps_per_second': 9.528, 'epoch': 5.62}\n",
+      "{'loss': 0.2797, 'learning_rate': 7.747500000000001e-05, 'epoch': 5.63}\n",
+      "{'loss': 0.3021, 'learning_rate': 7.745e-05, 'epoch': 5.64}\n",
+      "{'loss': 0.1627, 'learning_rate': 7.7425e-05, 'epoch': 5.64}\n",
+      "{'loss': 0.3689, 'learning_rate': 7.740000000000001e-05, 'epoch': 5.65}\n",
+      "{'loss': 0.5635, 'learning_rate': 7.737500000000001e-05, 'epoch': 5.66}\n",
+      "{'loss': 0.2615, 'learning_rate': 7.735e-05, 'epoch': 5.66}\n",
+      "{'loss': 0.2061, 'learning_rate': 7.732500000000001e-05, 'epoch': 5.67}\n",
+      "{'loss': 0.2528, 'learning_rate': 7.730000000000001e-05, 'epoch': 5.67}\n",
+      "{'loss': 0.3246, 'learning_rate': 7.727500000000001e-05, 'epoch': 5.68}\n",
+      "{'loss': 0.288, 'learning_rate': 7.725e-05, 'epoch': 5.69}\n",
+      "{'loss': 0.1898, 'learning_rate': 7.722500000000001e-05, 'epoch': 5.69}\n",
+      "{'loss': 0.1935, 'learning_rate': 7.72e-05, 'epoch': 5.7}\n",
+      "{'loss': 0.3441, 'learning_rate': 7.7175e-05, 'epoch': 5.71}\n",
+      "{'loss': 0.1584, 'learning_rate': 7.715e-05, 'epoch': 5.71}\n",
+      "{'loss': 0.2121, 'learning_rate': 7.7125e-05, 'epoch': 5.72}\n",
+      "{'loss': 0.2096, 'learning_rate': 7.71e-05, 'epoch': 5.72}\n",
+      "{'loss': 0.1898, 'learning_rate': 7.7075e-05, 'epoch': 5.73}\n",
+      "{'loss': 0.224, 'learning_rate': 7.705e-05, 'epoch': 5.74}\n",
+      "{'loss': 0.1428, 'learning_rate': 7.7025e-05, 'epoch': 5.74}\n",
+      "{'loss': 0.254, 'learning_rate': 7.7e-05, 'epoch': 5.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "044084e31cea41b8942d29e83dc00f17",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.36405181884765625, 'eval_mean_iou': 0.2074885036598059, 'eval_mean_accuracy': 0.23645677857947436, 'eval_overall_accuracy': 0.38101604712002235, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.48566095202866166, 'eval_accuracy_RV': 0.256283111413961, 'eval_accuracy_RA': 0.3728846045209139, 'eval_accuracy_LA': 0.3985500037733519, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.2397246680138568, 'eval_accuracy_VSD': 0.23859717515818515, 'eval_accuracy_AK': 0.37286727088581295, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.4754792833220283, 'eval_iou_RV': 0.253006699736071, 'eval_iou_RA': 0.36138578045961955, 'eval_iou_LA': 0.38077985071569614, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.22018477855574428, 'eval_iou_VSD': 0.22380995914234078, 'eval_iou_AK': 0.3677271883263649, 'eval_runtime': 4.3632, 'eval_samples_per_second': 18.564, 'eval_steps_per_second': 9.397, 'epoch': 5.75}\n",
+      "{'loss': 0.3107, 'learning_rate': 7.697500000000001e-05, 'epoch': 5.76}\n",
+      "{'loss': 0.2481, 'learning_rate': 7.695e-05, 'epoch': 5.76}\n",
+      "{'loss': 0.2789, 'learning_rate': 7.6925e-05, 'epoch': 5.77}\n",
+      "{'loss': 0.3919, 'learning_rate': 7.69e-05, 'epoch': 5.78}\n",
+      "{'loss': 0.529, 'learning_rate': 7.687500000000001e-05, 'epoch': 5.78}\n",
+      "{'loss': 0.2346, 'learning_rate': 7.685e-05, 'epoch': 5.79}\n",
+      "{'loss': 0.2976, 'learning_rate': 7.6825e-05, 'epoch': 5.79}\n",
+      "{'loss': 0.2632, 'learning_rate': 7.680000000000001e-05, 'epoch': 5.8}\n",
+      "{'loss': 0.2358, 'learning_rate': 7.677500000000001e-05, 'epoch': 5.81}\n",
+      "{'loss': 0.4938, 'learning_rate': 7.675e-05, 'epoch': 5.81}\n",
+      "{'loss': 0.2197, 'learning_rate': 7.672500000000001e-05, 'epoch': 5.82}\n",
+      "{'loss': 0.2382, 'learning_rate': 7.670000000000001e-05, 'epoch': 5.83}\n",
+      "{'loss': 0.3363, 'learning_rate': 7.667500000000001e-05, 'epoch': 5.83}\n",
+      "{'loss': 0.2161, 'learning_rate': 7.664999999999999e-05, 'epoch': 5.84}\n",
+      "{'loss': 0.2772, 'learning_rate': 7.6625e-05, 'epoch': 5.84}\n",
+      "{'loss': 0.3395, 'learning_rate': 7.66e-05, 'epoch': 5.85}\n",
+      "{'loss': 0.2862, 'learning_rate': 7.6575e-05, 'epoch': 5.86}\n",
+      "{'loss': 0.2622, 'learning_rate': 7.655e-05, 'epoch': 5.86}\n",
+      "{'loss': 0.2276, 'learning_rate': 7.6525e-05, 'epoch': 5.87}\n",
+      "{'loss': 0.2093, 'learning_rate': 7.65e-05, 'epoch': 5.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "366cfb68f9a94489b6c12d651434628f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3277250826358795, 'eval_mean_iou': 0.2282588496976943, 'eval_mean_accuracy': 0.26246521716540105, 'eval_overall_accuracy': 0.47517684073406485, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6677430709889893, 'eval_accuracy_RV': 0.3610394912122384, 'eval_accuracy_RA': 0.4567055111247407, 'eval_accuracy_LA': 0.501399570523947, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.24081625288683603, 'eval_accuracy_VSD': 0.23765256244939575, 'eval_accuracy_AK': 0.15929571246786298, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6439721514981516, 'eval_iou_RV': 0.35500494971810753, 'eval_iou_RA': 0.4364651962740799, 'eval_iou_LA': 0.47086243331701155, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.22393543840810712, 'eval_iou_VSD': 0.22213813207758717, 'eval_iou_AK': 0.15846904538159226, 'eval_runtime': 4.3257, 'eval_samples_per_second': 18.725, 'eval_steps_per_second': 9.478, 'epoch': 5.88}\n",
+      "{'loss': 0.278, 'learning_rate': 7.6475e-05, 'epoch': 5.88}\n",
+      "{'loss': 0.2165, 'learning_rate': 7.645e-05, 'epoch': 5.89}\n",
+      "{'loss': 0.3524, 'learning_rate': 7.6425e-05, 'epoch': 5.89}\n",
+      "{'loss': 0.1897, 'learning_rate': 7.64e-05, 'epoch': 5.9}\n",
+      "{'loss': 0.216, 'learning_rate': 7.637500000000001e-05, 'epoch': 5.91}\n",
+      "{'loss': 0.4182, 'learning_rate': 7.635e-05, 'epoch': 5.91}\n",
+      "{'loss': 0.198, 'learning_rate': 7.6325e-05, 'epoch': 5.92}\n",
+      "{'loss': 0.092, 'learning_rate': 7.630000000000001e-05, 'epoch': 5.92}\n",
+      "{'loss': 0.2737, 'learning_rate': 7.627500000000001e-05, 'epoch': 5.93}\n",
+      "{'loss': 0.3056, 'learning_rate': 7.625e-05, 'epoch': 5.94}\n",
+      "{'loss': 0.5434, 'learning_rate': 7.6225e-05, 'epoch': 5.94}\n",
+      "{'loss': 0.3101, 'learning_rate': 7.620000000000001e-05, 'epoch': 5.95}\n",
+      "{'loss': 0.2817, 'learning_rate': 7.617500000000001e-05, 'epoch': 5.96}\n",
+      "{'loss': 0.2006, 'learning_rate': 7.615e-05, 'epoch': 5.96}\n",
+      "{'loss': 0.442, 'learning_rate': 7.612500000000001e-05, 'epoch': 5.97}\n",
+      "{'loss': 0.1978, 'learning_rate': 7.61e-05, 'epoch': 5.97}\n",
+      "{'loss': 0.2261, 'learning_rate': 7.6075e-05, 'epoch': 5.98}\n",
+      "{'loss': 0.3183, 'learning_rate': 7.605e-05, 'epoch': 5.99}\n",
+      "{'loss': 0.231, 'learning_rate': 7.6025e-05, 'epoch': 5.99}\n",
+      "{'loss': 0.2196, 'learning_rate': 7.6e-05, 'epoch': 6.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "cf72e8f8f2de448a87421d3c4d60d24f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3089461922645569, 'eval_mean_iou': 0.3433908544126889, 'eval_mean_accuracy': 0.40962236032547095, 'eval_overall_accuracy': 0.674169730319233, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.8290538182273783, 'eval_accuracy_RV': 0.5298271300269496, 'eval_accuracy_RA': 0.6833988362802934, 'eval_accuracy_LA': 0.7399182897797049, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3856361864896074, 'eval_accuracy_VSD': 0.3623039553782949, 'eval_accuracy_AK': 0.5660853870724804, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.770154583073247, 'eval_iou_RV': 0.5114124879638545, 'eval_iou_RA': 0.6198326388927011, 'eval_iou_LA': 0.6640125599328905, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3398147780118447, 'eval_iou_VSD': 0.32707522588068083, 'eval_iou_AK': 0.5449971247843588, 'eval_runtime': 4.3849, 'eval_samples_per_second': 18.473, 'eval_steps_per_second': 9.35, 'epoch': 6.0}\n",
+      "{'loss': 0.2419, 'learning_rate': 7.5975e-05, 'epoch': 6.01}\n",
+      "{'loss': 0.2539, 'learning_rate': 7.595e-05, 'epoch': 6.01}\n",
+      "{'loss': 0.2831, 'learning_rate': 7.5925e-05, 'epoch': 6.02}\n",
+      "{'loss': 0.2236, 'learning_rate': 7.59e-05, 'epoch': 6.03}\n",
+      "{'loss': 0.2302, 'learning_rate': 7.5875e-05, 'epoch': 6.03}\n",
+      "{'loss': 0.1656, 'learning_rate': 7.585e-05, 'epoch': 6.04}\n",
+      "{'loss': 0.2497, 'learning_rate': 7.5825e-05, 'epoch': 6.04}\n",
+      "{'loss': 0.325, 'learning_rate': 7.58e-05, 'epoch': 6.05}\n",
+      "{'loss': 0.1982, 'learning_rate': 7.577500000000001e-05, 'epoch': 6.06}\n",
+      "{'loss': 0.2452, 'learning_rate': 7.575e-05, 'epoch': 6.06}\n",
+      "{'loss': 0.3149, 'learning_rate': 7.5725e-05, 'epoch': 6.07}\n",
+      "{'loss': 0.189, 'learning_rate': 7.570000000000001e-05, 'epoch': 6.08}\n",
+      "{'loss': 0.22, 'learning_rate': 7.567500000000001e-05, 'epoch': 6.08}\n",
+      "{'loss': 0.1543, 'learning_rate': 7.565e-05, 'epoch': 6.09}\n",
+      "{'loss': 0.3252, 'learning_rate': 7.5625e-05, 'epoch': 6.09}\n",
+      "{'loss': 0.2716, 'learning_rate': 7.560000000000001e-05, 'epoch': 6.1}\n",
+      "{'loss': 0.3872, 'learning_rate': 7.557500000000001e-05, 'epoch': 6.11}\n",
+      "{'loss': 0.3479, 'learning_rate': 7.555e-05, 'epoch': 6.11}\n",
+      "{'loss': 0.1754, 'learning_rate': 7.5525e-05, 'epoch': 6.12}\n",
+      "{'loss': 0.3027, 'learning_rate': 7.55e-05, 'epoch': 6.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9bbd8278b7c14bb3a1088229c8ce8fe7",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3159933090209961, 'eval_mean_iou': 0.27740147333331716, 'eval_mean_accuracy': 0.32375931478890974, 'eval_overall_accuracy': 0.5554051378481366, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7416614710892218, 'eval_accuracy_RV': 0.3943765078546566, 'eval_accuracy_RA': 0.49713306916949795, 'eval_accuracy_LA': 0.6526320844681975, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.40947062644341803, 'eval_accuracy_VSD': 0.21426215251746783, 'eval_accuracy_AK': 0.32805723634663825, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7116247018743009, 'eval_iou_RV': 0.3855442113080726, 'eval_iou_RA': 0.47781149710584747, 'eval_iou_LA': 0.6016079432713819, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3489904504144305, 'eval_iou_VSD': 0.20213879537160154, 'eval_iou_AK': 0.3236986073208543, 'eval_runtime': 4.393, 'eval_samples_per_second': 18.439, 'eval_steps_per_second': 9.333, 'epoch': 6.12}\n",
+      "{'loss': 0.2449, 'learning_rate': 7.5475e-05, 'epoch': 6.13}\n",
+      "{'loss': 0.1582, 'learning_rate': 7.545e-05, 'epoch': 6.14}\n",
+      "{'loss': 0.2563, 'learning_rate': 7.5425e-05, 'epoch': 6.14}\n",
+      "{'loss': 0.1046, 'learning_rate': 7.54e-05, 'epoch': 6.15}\n",
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+      "{'loss': 0.2985, 'learning_rate': 7.535e-05, 'epoch': 6.16}\n",
+      "{'loss': 0.1731, 'learning_rate': 7.5325e-05, 'epoch': 6.17}\n",
+      "{'loss': 0.3016, 'learning_rate': 7.53e-05, 'epoch': 6.17}\n",
+      "{'loss': 0.251, 'learning_rate': 7.5275e-05, 'epoch': 6.18}\n",
+      "{'loss': 0.1338, 'learning_rate': 7.525e-05, 'epoch': 6.19}\n",
+      "{'loss': 0.2788, 'learning_rate': 7.5225e-05, 'epoch': 6.19}\n",
+      "{'loss': 0.3165, 'learning_rate': 7.52e-05, 'epoch': 6.2}\n",
+      "{'loss': 0.1848, 'learning_rate': 7.517500000000001e-05, 'epoch': 6.21}\n",
+      "{'loss': 0.3485, 'learning_rate': 7.515e-05, 'epoch': 6.21}\n",
+      "{'loss': 0.2584, 'learning_rate': 7.5125e-05, 'epoch': 6.22}\n",
+      "{'loss': 0.3357, 'learning_rate': 7.510000000000001e-05, 'epoch': 6.22}\n",
+      "{'loss': 0.4641, 'learning_rate': 7.507500000000001e-05, 'epoch': 6.23}\n",
+      "{'loss': 0.2869, 'learning_rate': 7.505e-05, 'epoch': 6.24}\n",
+      "{'loss': 0.135, 'learning_rate': 7.502500000000001e-05, 'epoch': 6.24}\n",
+      "{'loss': 0.1408, 'learning_rate': 7.500000000000001e-05, 'epoch': 6.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "887b9277ad7a47a183daa7e2c90e7453",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3215813934803009, 'eval_mean_iou': 0.28588517702201205, 'eval_mean_accuracy': 0.33255244141406665, 'eval_overall_accuracy': 0.5338155836231091, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6770719913131934, 'eval_accuracy_RV': 0.35560507559991894, 'eval_accuracy_RA': 0.48609306529581237, 'eval_accuracy_LA': 0.6083346482892995, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3364156322170901, 'eval_accuracy_VSD': 0.3690286982337242, 'eval_accuracy_AK': 0.4929753031916275, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6525808165140055, 'eval_iou_RV': 0.34928186389783294, 'eval_iou_RA': 0.4676140587183812, 'eval_iou_LA': 0.5661625150646884, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2995116701203155, 'eval_iou_VSD': 0.3330198699690821, 'eval_iou_AK': 0.4765661529578269, 'eval_runtime': 4.3557, 'eval_samples_per_second': 18.596, 'eval_steps_per_second': 9.413, 'epoch': 6.25}\n",
+      "{'loss': 0.2244, 'learning_rate': 7.4975e-05, 'epoch': 6.26}\n",
+      "{'loss': 0.1663, 'learning_rate': 7.495e-05, 'epoch': 6.26}\n",
+      "{'loss': 0.2529, 'learning_rate': 7.4925e-05, 'epoch': 6.27}\n",
+      "{'loss': 0.1468, 'learning_rate': 7.49e-05, 'epoch': 6.28}\n",
+      "{'loss': 0.2475, 'learning_rate': 7.4875e-05, 'epoch': 6.28}\n",
+      "{'loss': 0.1888, 'learning_rate': 7.485e-05, 'epoch': 6.29}\n",
+      "{'loss': 0.1969, 'learning_rate': 7.4825e-05, 'epoch': 6.29}\n",
+      "{'loss': 0.3915, 'learning_rate': 7.48e-05, 'epoch': 6.3}\n",
+      "{'loss': 0.1908, 'learning_rate': 7.4775e-05, 'epoch': 6.31}\n",
+      "{'loss': 0.2693, 'learning_rate': 7.475000000000001e-05, 'epoch': 6.31}\n",
+      "{'loss': 0.1091, 'learning_rate': 7.4725e-05, 'epoch': 6.32}\n",
+      "{'loss': 0.1812, 'learning_rate': 7.47e-05, 'epoch': 6.33}\n",
+      "{'loss': 0.209, 'learning_rate': 7.467500000000001e-05, 'epoch': 6.33}\n",
+      "{'loss': 0.1842, 'learning_rate': 7.465000000000001e-05, 'epoch': 6.34}\n",
+      "{'loss': 0.2096, 'learning_rate': 7.4625e-05, 'epoch': 6.34}\n",
+      "{'loss': 0.1557, 'learning_rate': 7.46e-05, 'epoch': 6.35}\n",
+      "{'loss': 0.322, 'learning_rate': 7.457500000000001e-05, 'epoch': 6.36}\n",
+      "{'loss': 0.3101, 'learning_rate': 7.455000000000001e-05, 'epoch': 6.36}\n",
+      "{'loss': 0.3982, 'learning_rate': 7.4525e-05, 'epoch': 6.37}\n",
+      "{'loss': 0.2496, 'learning_rate': 7.450000000000001e-05, 'epoch': 6.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8524d9935ef54a9b9108f7317dbd515d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3185799717903137, 'eval_mean_iou': 0.3470336040093634, 'eval_mean_accuracy': 0.4141231863168561, 'eval_overall_accuracy': 0.6648873499098756, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.8227691582567918, 'eval_accuracy_RV': 0.5588485361915811, 'eval_accuracy_RA': 0.6644561103354774, 'eval_accuracy_LA': 0.6491828977970485, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.44658451212471134, 'eval_accuracy_VSD': 0.4260728101478394, 'eval_accuracy_AK': 0.5733178383151115, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.77713011338862, 'eval_iou_RV': 0.5377134343080837, 'eval_iou_RA': 0.6062182937334796, 'eval_iou_LA': 0.5997417208049437, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3781279599132268, 'eval_iou_VSD': 0.37428545085745896, 'eval_iou_AK': 0.5441526710971849, 'eval_runtime': 4.3431, 'eval_samples_per_second': 18.65, 'eval_steps_per_second': 9.44, 'epoch': 6.38}\n",
+      "{'loss': 0.2774, 'learning_rate': 7.447500000000001e-05, 'epoch': 6.38}\n",
+      "{'loss': 0.5096, 'learning_rate': 7.445000000000001e-05, 'epoch': 6.39}\n",
+      "{'loss': 0.2312, 'learning_rate': 7.4425e-05, 'epoch': 6.39}\n",
+      "{'loss': 0.4509, 'learning_rate': 7.44e-05, 'epoch': 6.4}\n",
+      "{'loss': 0.2698, 'learning_rate': 7.4375e-05, 'epoch': 6.41}\n",
+      "{'loss': 0.4505, 'learning_rate': 7.435e-05, 'epoch': 6.41}\n",
+      "{'loss': 0.3808, 'learning_rate': 7.4325e-05, 'epoch': 6.42}\n",
+      "{'loss': 0.4196, 'learning_rate': 7.43e-05, 'epoch': 6.42}\n",
+      "{'loss': 0.3374, 'learning_rate': 7.4275e-05, 'epoch': 6.43}\n",
+      "{'loss': 0.2112, 'learning_rate': 7.425e-05, 'epoch': 6.44}\n",
+      "{'loss': 0.2746, 'learning_rate': 7.4225e-05, 'epoch': 6.44}\n",
+      "{'loss': 0.1972, 'learning_rate': 7.42e-05, 'epoch': 6.45}\n",
+      "{'loss': 0.3406, 'learning_rate': 7.4175e-05, 'epoch': 6.46}\n",
+      "{'loss': 0.286, 'learning_rate': 7.415000000000001e-05, 'epoch': 6.46}\n",
+      "{'loss': 0.2179, 'learning_rate': 7.4125e-05, 'epoch': 6.47}\n",
+      "{'loss': 0.2475, 'learning_rate': 7.41e-05, 'epoch': 6.47}\n",
+      "{'loss': 0.1934, 'learning_rate': 7.407500000000001e-05, 'epoch': 6.48}\n",
+      "{'loss': 0.2934, 'learning_rate': 7.405000000000001e-05, 'epoch': 6.49}\n",
+      "{'loss': 0.3201, 'learning_rate': 7.4025e-05, 'epoch': 6.49}\n",
+      "{'loss': 0.2732, 'learning_rate': 7.4e-05, 'epoch': 6.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "eca41f464002463c8f40c41e9a6c58d2",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.31273359060287476, 'eval_mean_iou': 0.2832712706760393, 'eval_mean_accuracy': 0.33096411294788736, 'eval_overall_accuracy': 0.5559506988157242, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6974876275650989, 'eval_accuracy_RV': 0.42733905474011186, 'eval_accuracy_RA': 0.6111888986627715, 'eval_accuracy_LA': 0.5931674888000055, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3356578377598152, 'eval_accuracy_VSD': 0.245629291990284, 'eval_accuracy_AK': 0.39917092996078635, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6710135766799374, 'eval_iou_RV': 0.41397053357715236, 'eval_iou_RA': 0.5752936886842975, 'eval_iou_LA': 0.5569525257389117, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2868940311051824, 'eval_iou_VSD': 0.22601785295456742, 'eval_iou_AK': 0.3858417686963834, 'eval_runtime': 4.3723, 'eval_samples_per_second': 18.526, 'eval_steps_per_second': 9.377, 'epoch': 6.5}\n",
+      "{'loss': 0.356, 'learning_rate': 7.397500000000001e-05, 'epoch': 6.51}\n",
+      "{'loss': 0.2315, 'learning_rate': 7.395000000000001e-05, 'epoch': 6.51}\n",
+      "{'loss': 0.3012, 'learning_rate': 7.3925e-05, 'epoch': 6.52}\n",
+      "{'loss': 0.2497, 'learning_rate': 7.390000000000001e-05, 'epoch': 6.53}\n",
+      "{'loss': 0.1906, 'learning_rate': 7.3875e-05, 'epoch': 6.53}\n",
+      "{'loss': 0.2124, 'learning_rate': 7.385e-05, 'epoch': 6.54}\n",
+      "{'loss': 0.2104, 'learning_rate': 7.3825e-05, 'epoch': 6.54}\n",
+      "{'loss': 0.2449, 'learning_rate': 7.38e-05, 'epoch': 6.55}\n",
+      "{'loss': 0.5157, 'learning_rate': 7.3775e-05, 'epoch': 6.56}\n",
+      "{'loss': 0.4212, 'learning_rate': 7.375e-05, 'epoch': 6.56}\n",
+      "{'loss': 0.3194, 'learning_rate': 7.3725e-05, 'epoch': 6.57}\n",
+      "{'loss': 0.2449, 'learning_rate': 7.37e-05, 'epoch': 6.58}\n",
+      "{'loss': 0.3064, 'learning_rate': 7.3675e-05, 'epoch': 6.58}\n",
+      "{'loss': 0.2498, 'learning_rate': 7.365e-05, 'epoch': 6.59}\n",
+      "{'loss': 0.44, 'learning_rate': 7.3625e-05, 'epoch': 6.59}\n",
+      "{'loss': 0.3803, 'learning_rate': 7.36e-05, 'epoch': 6.6}\n",
+      "{'loss': 0.2283, 'learning_rate': 7.3575e-05, 'epoch': 6.61}\n",
+      "{'loss': 0.2201, 'learning_rate': 7.355000000000001e-05, 'epoch': 6.61}\n",
+      "{'loss': 0.2826, 'learning_rate': 7.3525e-05, 'epoch': 6.62}\n",
+      "{'loss': 0.3288, 'learning_rate': 7.35e-05, 'epoch': 6.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "bf8df18029e2404892fd08b00183cde6",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.31431928277015686, 'eval_mean_iou': 0.3643638968678223, 'eval_mean_accuracy': 0.43874712320126125, 'eval_overall_accuracy': 0.6950062643490379, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.8221270445467319, 'eval_accuracy_RV': 0.5633130137448817, 'eval_accuracy_RA': 0.7005035791240628, 'eval_accuracy_LA': 0.7582996590262008, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4342703521939954, 'eval_accuracy_VSD': 0.4522295858697934, 'eval_accuracy_AK': 0.6567279975069468, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7712327808754906, 'eval_iou_RV': 0.544583218347829, 'eval_iou_RA': 0.6396290510368001, 'eval_iou_LA': 0.6802600927495915, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.370757180156658, 'eval_iou_VSD': 0.3952586263383438, 'eval_iou_AK': 0.606281916041332, 'eval_runtime': 4.4204, 'eval_samples_per_second': 18.324, 'eval_steps_per_second': 9.275, 'epoch': 6.62}\n",
+      "{'loss': 0.222, 'learning_rate': 7.347500000000001e-05, 'epoch': 6.63}\n",
+      "{'loss': 0.2313, 'learning_rate': 7.345000000000001e-05, 'epoch': 6.64}\n",
+      "{'loss': 0.2423, 'learning_rate': 7.3425e-05, 'epoch': 6.64}\n",
+      "{'loss': 0.3335, 'learning_rate': 7.340000000000001e-05, 'epoch': 6.65}\n",
+      "{'loss': 0.4322, 'learning_rate': 7.337500000000001e-05, 'epoch': 6.66}\n",
+      "{'loss': 0.2119, 'learning_rate': 7.335000000000001e-05, 'epoch': 6.66}\n",
+      "{'loss': 0.2535, 'learning_rate': 7.3325e-05, 'epoch': 6.67}\n",
+      "{'loss': 0.2442, 'learning_rate': 7.33e-05, 'epoch': 6.67}\n",
+      "{'loss': 0.2793, 'learning_rate': 7.3275e-05, 'epoch': 6.68}\n",
+      "{'loss': 0.2421, 'learning_rate': 7.325e-05, 'epoch': 6.69}\n",
+      "{'loss': 0.1802, 'learning_rate': 7.3225e-05, 'epoch': 6.69}\n",
+      "{'loss': 0.1332, 'learning_rate': 7.32e-05, 'epoch': 6.7}\n",
+      "{'loss': 0.3973, 'learning_rate': 7.3175e-05, 'epoch': 6.71}\n",
+      "{'loss': 0.1852, 'learning_rate': 7.315e-05, 'epoch': 6.71}\n",
+      "{'loss': 0.1845, 'learning_rate': 7.3125e-05, 'epoch': 6.72}\n",
+      "{'loss': 0.3115, 'learning_rate': 7.31e-05, 'epoch': 6.72}\n",
+      "{'loss': 0.1445, 'learning_rate': 7.3075e-05, 'epoch': 6.73}\n",
+      "{'loss': 0.2293, 'learning_rate': 7.305000000000001e-05, 'epoch': 6.74}\n",
+      "{'loss': 0.1103, 'learning_rate': 7.3025e-05, 'epoch': 6.74}\n",
+      "{'loss': 0.3941, 'learning_rate': 7.3e-05, 'epoch': 6.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "11a5b3658ef4401e90e0d2937b19eb9a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.36069461703300476, 'eval_mean_iou': 0.21626372589904228, 'eval_mean_accuracy': 0.2478831729217633, 'eval_overall_accuracy': 0.39689628012351263, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.46885711217375997, 'eval_accuracy_RV': 0.27489609998956394, 'eval_accuracy_RA': 0.45913059969494724, 'eval_accuracy_LA': 0.4564057794029871, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.2229810190531178, 'eval_accuracy_VSD': 0.24385252046660869, 'eval_accuracy_AK': 0.35270859843664787, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.4622285060138386, 'eval_iou_RV': 0.26941102858672733, 'eval_iou_RA': 0.4347524572782241, 'eval_iou_LA': 0.43303872923708336, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.20628442663995994, 'eval_iou_VSD': 0.2264527941964814, 'eval_iou_AK': 0.34673304293714996, 'eval_runtime': 4.3863, 'eval_samples_per_second': 18.467, 'eval_steps_per_second': 9.347, 'epoch': 6.75}\n",
+      "{'loss': 0.2379, 'learning_rate': 7.2975e-05, 'epoch': 6.76}\n",
+      "{'loss': 0.158, 'learning_rate': 7.295000000000001e-05, 'epoch': 6.76}\n",
+      "{'loss': 0.2954, 'learning_rate': 7.2925e-05, 'epoch': 6.77}\n",
+      "{'loss': 0.2753, 'learning_rate': 7.29e-05, 'epoch': 6.78}\n",
+      "{'loss': 0.2189, 'learning_rate': 7.287500000000001e-05, 'epoch': 6.78}\n",
+      "{'loss': 0.6421, 'learning_rate': 7.285000000000001e-05, 'epoch': 6.79}\n",
+      "{'loss': 0.1658, 'learning_rate': 7.2825e-05, 'epoch': 6.79}\n",
+      "{'loss': 0.3031, 'learning_rate': 7.280000000000001e-05, 'epoch': 6.8}\n",
+      "{'loss': 0.2914, 'learning_rate': 7.277500000000001e-05, 'epoch': 6.81}\n",
+      "{'loss': 0.4917, 'learning_rate': 7.275e-05, 'epoch': 6.81}\n",
+      "{'loss': 0.2052, 'learning_rate': 7.272499999999999e-05, 'epoch': 6.82}\n",
+      "{'loss': 0.2867, 'learning_rate': 7.27e-05, 'epoch': 6.83}\n",
+      "{'loss': 0.2781, 'learning_rate': 7.2675e-05, 'epoch': 6.83}\n",
+      "{'loss': 0.1587, 'learning_rate': 7.265e-05, 'epoch': 6.84}\n",
+      "{'loss': 0.2175, 'learning_rate': 7.2625e-05, 'epoch': 6.84}\n",
+      "{'loss': 0.225, 'learning_rate': 7.26e-05, 'epoch': 6.85}\n",
+      "{'loss': 0.2705, 'learning_rate': 7.2575e-05, 'epoch': 6.86}\n",
+      "{'loss': 0.4251, 'learning_rate': 7.255e-05, 'epoch': 6.86}\n",
+      "{'loss': 0.5338, 'learning_rate': 7.2525e-05, 'epoch': 6.87}\n",
+      "{'loss': 0.3086, 'learning_rate': 7.25e-05, 'epoch': 6.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "88fd3e2dbaf146559bec908d631a366f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.32130372524261475, 'eval_mean_iou': 0.29696685589245225, 'eval_mean_accuracy': 0.3490248016765864, 'eval_overall_accuracy': 0.5742693215677535, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6860802276707009, 'eval_accuracy_RV': 0.44536731799848983, 'eval_accuracy_RA': 0.6278074132657591, 'eval_accuracy_LA': 0.6799237096851652, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.24097863741339492, 'eval_accuracy_VSD': 0.4057486430563469, 'eval_accuracy_AK': 0.40434206767600694, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6602494863073917, 'eval_iou_RV': 0.43494604316546764, 'eval_iou_RA': 0.5757012319777692, 'eval_iou_LA': 0.619351089043632, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2238667124814576, 'eval_iou_VSD': 0.3619183908199703, 'eval_iou_AK': 0.3906024610212862, 'eval_runtime': 4.3815, 'eval_samples_per_second': 18.487, 'eval_steps_per_second': 9.358, 'epoch': 6.88}\n",
+      "{'loss': 0.1834, 'learning_rate': 7.2475e-05, 'epoch': 6.88}\n",
+      "{'loss': 0.1688, 'learning_rate': 7.245000000000001e-05, 'epoch': 6.89}\n",
+      "{'loss': 0.607, 'learning_rate': 7.2425e-05, 'epoch': 6.89}\n",
+      "{'loss': 0.1787, 'learning_rate': 7.24e-05, 'epoch': 6.9}\n",
+      "{'loss': 0.1898, 'learning_rate': 7.2375e-05, 'epoch': 6.91}\n",
+      "{'loss': 0.1437, 'learning_rate': 7.235000000000001e-05, 'epoch': 6.91}\n",
+      "{'loss': 0.1581, 'learning_rate': 7.2325e-05, 'epoch': 6.92}\n",
+      "{'loss': 0.317, 'learning_rate': 7.23e-05, 'epoch': 6.92}\n",
+      "{'loss': 0.2702, 'learning_rate': 7.227500000000001e-05, 'epoch': 6.93}\n",
+      "{'loss': 0.2458, 'learning_rate': 7.225000000000001e-05, 'epoch': 6.94}\n",
+      "{'loss': 0.2605, 'learning_rate': 7.2225e-05, 'epoch': 6.94}\n",
+      "{'loss': 0.1723, 'learning_rate': 7.22e-05, 'epoch': 6.95}\n",
+      "{'loss': 0.1946, 'learning_rate': 7.2175e-05, 'epoch': 6.96}\n",
+      "{'loss': 0.1746, 'learning_rate': 7.215e-05, 'epoch': 6.96}\n",
+      "{'loss': 0.073, 'learning_rate': 7.2125e-05, 'epoch': 6.97}\n",
+      "{'loss': 0.2766, 'learning_rate': 7.21e-05, 'epoch': 6.97}\n",
+      "{'loss': 0.1248, 'learning_rate': 7.2075e-05, 'epoch': 6.98}\n",
+      "{'loss': 0.1624, 'learning_rate': 7.205e-05, 'epoch': 6.99}\n",
+      "{'loss': 0.3097, 'learning_rate': 7.2025e-05, 'epoch': 6.99}\n",
+      "{'loss': 0.4078, 'learning_rate': 7.2e-05, 'epoch': 7.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "83900fc24935426697251c8b85095935",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3620806932449341, 'eval_mean_iou': 0.22149433346373826, 'eval_mean_accuracy': 0.25360159557038386, 'eval_overall_accuracy': 0.42504527858501445, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.5593973826222104, 'eval_accuracy_RV': 0.2791595302553147, 'eval_accuracy_RA': 0.3686376732062011, 'eval_accuracy_LA': 0.45328933376326674, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.15698073036951501, 'eval_accuracy_VSD': 0.26506882178306895, 'eval_accuracy_AK': 0.4534824837042616, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.5457230100335908, 'eval_iou_RV': 0.2749221242656405, 'eval_iou_RA': 0.35792838924780895, 'eval_iou_LA': 0.4276626972375816, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.15164534458116918, 'eval_iou_VSD': 0.24648127879983547, 'eval_iou_AK': 0.43207482393549407, 'eval_runtime': 4.3422, 'eval_samples_per_second': 18.654, 'eval_steps_per_second': 9.442, 'epoch': 7.0}\n",
+      "{'loss': 0.2279, 'learning_rate': 7.1975e-05, 'epoch': 7.01}\n",
+      "{'loss': 0.3091, 'learning_rate': 7.195e-05, 'epoch': 7.01}\n",
+      "{'loss': 0.2797, 'learning_rate': 7.1925e-05, 'epoch': 7.02}\n",
+      "{'loss': 0.1283, 'learning_rate': 7.19e-05, 'epoch': 7.03}\n",
+      "{'loss': 0.2604, 'learning_rate': 7.1875e-05, 'epoch': 7.03}\n",
+      "{'loss': 0.2558, 'learning_rate': 7.185000000000001e-05, 'epoch': 7.04}\n",
+      "{'loss': 0.1946, 'learning_rate': 7.182500000000001e-05, 'epoch': 7.04}\n",
+      "{'loss': 0.136, 'learning_rate': 7.18e-05, 'epoch': 7.05}\n",
+      "{'loss': 0.3577, 'learning_rate': 7.177500000000001e-05, 'epoch': 7.06}\n",
+      "{'loss': 0.1281, 'learning_rate': 7.175000000000001e-05, 'epoch': 7.06}\n",
+      "{'loss': 0.3021, 'learning_rate': 7.172500000000001e-05, 'epoch': 7.07}\n",
+      "{'loss': 0.2347, 'learning_rate': 7.17e-05, 'epoch': 7.08}\n",
+      "{'loss': 0.2911, 'learning_rate': 7.167500000000001e-05, 'epoch': 7.08}\n",
+      "{'loss': 0.3347, 'learning_rate': 7.165000000000001e-05, 'epoch': 7.09}\n",
+      "{'loss': 0.2132, 'learning_rate': 7.1625e-05, 'epoch': 7.09}\n",
+      "{'loss': 0.1886, 'learning_rate': 7.16e-05, 'epoch': 7.1}\n",
+      "{'loss': 0.2374, 'learning_rate': 7.1575e-05, 'epoch': 7.11}\n",
+      "{'loss': 0.2477, 'learning_rate': 7.155e-05, 'epoch': 7.11}\n",
+      "{'loss': 0.2862, 'learning_rate': 7.1525e-05, 'epoch': 7.12}\n",
+      "{'loss': 0.2701, 'learning_rate': 7.15e-05, 'epoch': 7.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a84b40f17fb34bad93772a6549f77eff",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3277438282966614, 'eval_mean_iou': 0.2852333429180309, 'eval_mean_accuracy': 0.3329843484572609, 'eval_overall_accuracy': 0.5456534722237248, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6563431288612587, 'eval_accuracy_RV': 0.39018674377060353, 'eval_accuracy_RA': 0.5654390580487922, 'eval_accuracy_LA': 0.6771091321976688, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3036500433025404, 'eval_accuracy_VSD': 0.30200617746723846, 'eval_accuracy_AK': 0.4351092009245072, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6324940134134036, 'eval_iou_RV': 0.38150151105455704, 'eval_iou_RA': 0.5325483027529909, 'eval_iou_LA': 0.6251775627229926, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2723748948015796, 'eval_iou_VSD': 0.27965289829920165, 'eval_iou_AK': 0.4138175890536143, 'eval_runtime': 4.3401, 'eval_samples_per_second': 18.663, 'eval_steps_per_second': 9.447, 'epoch': 7.12}\n",
+      "{'loss': 0.1408, 'learning_rate': 7.1475e-05, 'epoch': 7.13}\n",
+      "{'loss': 0.2084, 'learning_rate': 7.145e-05, 'epoch': 7.14}\n",
+      "{'loss': 0.2595, 'learning_rate': 7.142500000000001e-05, 'epoch': 7.14}\n",
+      "{'loss': 0.0834, 'learning_rate': 7.14e-05, 'epoch': 7.15}\n",
+      "{'loss': 0.5614, 'learning_rate': 7.1375e-05, 'epoch': 7.16}\n",
+      "{'loss': 0.2147, 'learning_rate': 7.135e-05, 'epoch': 7.16}\n",
+      "{'loss': 0.1797, 'learning_rate': 7.132500000000001e-05, 'epoch': 7.17}\n",
+      "{'loss': 0.0978, 'learning_rate': 7.13e-05, 'epoch': 7.17}\n",
+      "{'loss': 0.2303, 'learning_rate': 7.1275e-05, 'epoch': 7.18}\n",
+      "{'loss': 0.3608, 'learning_rate': 7.125000000000001e-05, 'epoch': 7.19}\n",
+      "{'loss': 0.1881, 'learning_rate': 7.122500000000001e-05, 'epoch': 7.19}\n",
+      "{'loss': 0.2411, 'learning_rate': 7.12e-05, 'epoch': 7.2}\n",
+      "{'loss': 0.2445, 'learning_rate': 7.117500000000001e-05, 'epoch': 7.21}\n",
+      "{'loss': 0.3315, 'learning_rate': 7.115000000000001e-05, 'epoch': 7.21}\n",
+      "{'loss': 0.1932, 'learning_rate': 7.112500000000001e-05, 'epoch': 7.22}\n",
+      "{'loss': 0.3246, 'learning_rate': 7.11e-05, 'epoch': 7.22}\n",
+      "{'loss': 0.3802, 'learning_rate': 7.1075e-05, 'epoch': 7.23}\n",
+      "{'loss': 0.3139, 'learning_rate': 7.105e-05, 'epoch': 7.24}\n",
+      "{'loss': 0.2679, 'learning_rate': 7.1025e-05, 'epoch': 7.24}\n",
+      "{'loss': 0.3182, 'learning_rate': 7.1e-05, 'epoch': 7.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "04f49932454942ddaf67d6e74e5ce5e6",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.31722491979599, 'eval_mean_iou': 0.35673685365488084, 'eval_mean_accuracy': 0.43004669869678525, 'eval_overall_accuracy': 0.6901256981124727, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.8272967684005477, 'eval_accuracy_RV': 0.5780416459480531, 'eval_accuracy_RA': 0.6892779611501618, 'eval_accuracy_LA': 0.734316577364005, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4382126876443418, 'eval_accuracy_VSD': 0.40736048220229704, 'eval_accuracy_AK': 0.6259608642584465, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.770743661200705, 'eval_iou_RV': 0.5506707116488175, 'eval_iou_RA': 0.6214000152784498, 'eval_iou_LA': 0.6599922305432145, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3688782910474397, 'eval_iou_VSD': 0.3625608861012878, 'eval_iou_AK': 0.5898595943837753, 'eval_runtime': 4.4036, 'eval_samples_per_second': 18.394, 'eval_steps_per_second': 9.311, 'epoch': 7.25}\n",
+      "{'loss': 0.2031, 'learning_rate': 7.0975e-05, 'epoch': 7.26}\n",
+      "{'loss': 0.2047, 'learning_rate': 7.095e-05, 'epoch': 7.26}\n",
+      "{'loss': 0.4939, 'learning_rate': 7.0925e-05, 'epoch': 7.27}\n",
+      "{'loss': 0.4212, 'learning_rate': 7.09e-05, 'epoch': 7.28}\n",
+      "{'loss': 0.1684, 'learning_rate': 7.0875e-05, 'epoch': 7.28}\n",
+      "{'loss': 0.2588, 'learning_rate': 7.085e-05, 'epoch': 7.29}\n",
+      "{'loss': 0.2388, 'learning_rate': 7.082500000000001e-05, 'epoch': 7.29}\n",
+      "{'loss': 0.1579, 'learning_rate': 7.08e-05, 'epoch': 7.3}\n",
+      "{'loss': 0.3481, 'learning_rate': 7.0775e-05, 'epoch': 7.31}\n",
+      "{'loss': 0.2332, 'learning_rate': 7.075e-05, 'epoch': 7.31}\n",
+      "{'loss': 0.1759, 'learning_rate': 7.072500000000001e-05, 'epoch': 7.32}\n",
+      "{'loss': 0.2235, 'learning_rate': 7.07e-05, 'epoch': 7.33}\n",
+      "{'loss': 0.1912, 'learning_rate': 7.0675e-05, 'epoch': 7.33}\n",
+      "{'loss': 0.45, 'learning_rate': 7.065000000000001e-05, 'epoch': 7.34}\n",
+      "{'loss': 0.1573, 'learning_rate': 7.062500000000001e-05, 'epoch': 7.34}\n",
+      "{'loss': 0.1221, 'learning_rate': 7.06e-05, 'epoch': 7.35}\n",
+      "{'loss': 0.6564, 'learning_rate': 7.057500000000001e-05, 'epoch': 7.36}\n",
+      "{'loss': 0.1579, 'learning_rate': 7.055000000000001e-05, 'epoch': 7.36}\n",
+      "{'loss': 0.232, 'learning_rate': 7.0525e-05, 'epoch': 7.37}\n",
+      "{'loss': 0.2771, 'learning_rate': 7.05e-05, 'epoch': 7.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0fca3b9b0bd842c3a763d00cfeb73184",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.36101964116096497, 'eval_mean_iou': 0.20724581150028126, 'eval_mean_accuracy': 0.23717062318238874, 'eval_overall_accuracy': 0.41014364725764324, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.5632716924059054, 'eval_accuracy_RV': 0.20137878536744078, 'eval_accuracy_RA': 0.4207326914851549, 'eval_accuracy_LA': 0.483103959275242, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.1796965213625866, 'eval_accuracy_VSD': 0.2378699733109425, 'eval_accuracy_AK': 0.2856526086166152, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.5491170876688904, 'eval_iou_RV': 0.19882266483828687, 'eval_iou_RA': 0.39964392965215106, 'eval_iou_LA': 0.45642620326228217, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.17225157602538935, 'eval_iou_VSD': 0.22297572699546023, 'eval_iou_AK': 0.2804667380606339, 'eval_runtime': 4.3126, 'eval_samples_per_second': 18.782, 'eval_steps_per_second': 9.507, 'epoch': 7.38}\n",
+      "{'loss': 0.3009, 'learning_rate': 7.0475e-05, 'epoch': 7.38}\n",
+      "{'loss': 0.2982, 'learning_rate': 7.045e-05, 'epoch': 7.39}\n",
+      "{'loss': 0.1571, 'learning_rate': 7.0425e-05, 'epoch': 7.39}\n",
+      "{'loss': 0.1538, 'learning_rate': 7.04e-05, 'epoch': 7.4}\n",
+      "{'loss': 0.1715, 'learning_rate': 7.0375e-05, 'epoch': 7.41}\n",
+      "{'loss': 0.1213, 'learning_rate': 7.035e-05, 'epoch': 7.41}\n",
+      "{'loss': 0.103, 'learning_rate': 7.0325e-05, 'epoch': 7.42}\n",
+      "{'loss': 0.307, 'learning_rate': 7.03e-05, 'epoch': 7.42}\n",
+      "{'loss': 0.5833, 'learning_rate': 7.0275e-05, 'epoch': 7.43}\n",
+      "{'loss': 0.1249, 'learning_rate': 7.025e-05, 'epoch': 7.44}\n",
+      "{'loss': 0.0823, 'learning_rate': 7.022500000000001e-05, 'epoch': 7.44}\n",
+      "{'loss': 0.2912, 'learning_rate': 7.02e-05, 'epoch': 7.45}\n",
+      "{'loss': 0.4326, 'learning_rate': 7.0175e-05, 'epoch': 7.46}\n",
+      "{'loss': 0.3482, 'learning_rate': 7.015000000000001e-05, 'epoch': 7.46}\n",
+      "{'loss': 0.1189, 'learning_rate': 7.012500000000001e-05, 'epoch': 7.47}\n",
+      "{'loss': 0.6243, 'learning_rate': 7.01e-05, 'epoch': 7.47}\n",
+      "{'loss': 0.1721, 'learning_rate': 7.0075e-05, 'epoch': 7.48}\n",
+      "{'loss': 0.4673, 'learning_rate': 7.005000000000001e-05, 'epoch': 7.49}\n",
+      "{'loss': 0.2266, 'learning_rate': 7.002500000000001e-05, 'epoch': 7.49}\n",
+      "{'loss': 0.3286, 'learning_rate': 7e-05, 'epoch': 7.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a0132399ed95446fb65d3c50683206bc",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3387606143951416, 'eval_mean_iou': 0.3797446213522338, 'eval_mean_accuracy': 0.4646057987033657, 'eval_overall_accuracy': 0.722016536150379, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.8359694052580238, 'eval_accuracy_RV': 0.6051523355249022, 'eval_accuracy_RA': 0.731331660116372, 'eval_accuracy_LA': 0.7968770367524476, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.446043230369515, 'eval_accuracy_VSD': 0.581266680660929, 'eval_accuracy_AK': 0.6494176383514686, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7697158760448561, 'eval_iou_RV': 0.5712617567121192, 'eval_iou_RA': 0.655525616217878, 'eval_iou_LA': 0.7044905571687428, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.39025834102910184, 'eval_iou_VSD': 0.48662829742231484, 'eval_iou_AK': 0.5993103902795586, 'eval_runtime': 4.2925, 'eval_samples_per_second': 18.87, 'eval_steps_per_second': 9.552, 'epoch': 7.5}\n",
+      "{'loss': 0.2719, 'learning_rate': 6.997500000000001e-05, 'epoch': 7.51}\n",
+      "{'loss': 0.1335, 'learning_rate': 6.995e-05, 'epoch': 7.51}\n",
+      "{'loss': 0.153, 'learning_rate': 6.9925e-05, 'epoch': 7.52}\n",
+      "{'loss': 0.3778, 'learning_rate': 6.99e-05, 'epoch': 7.53}\n",
+      "{'loss': 0.3103, 'learning_rate': 6.9875e-05, 'epoch': 7.53}\n",
+      "{'loss': 0.2956, 'learning_rate': 6.985e-05, 'epoch': 7.54}\n",
+      "{'loss': 0.1488, 'learning_rate': 6.9825e-05, 'epoch': 7.54}\n",
+      "{'loss': 0.2372, 'learning_rate': 6.98e-05, 'epoch': 7.55}\n",
+      "{'loss': 0.3319, 'learning_rate': 6.9775e-05, 'epoch': 7.56}\n",
+      "{'loss': 0.1954, 'learning_rate': 6.975e-05, 'epoch': 7.56}\n",
+      "{'loss': 0.1347, 'learning_rate': 6.9725e-05, 'epoch': 7.57}\n",
+      "{'loss': 0.2665, 'learning_rate': 6.97e-05, 'epoch': 7.58}\n",
+      "{'loss': 0.1899, 'learning_rate': 6.9675e-05, 'epoch': 7.58}\n",
+      "{'loss': 0.1732, 'learning_rate': 6.965e-05, 'epoch': 7.59}\n",
+      "{'loss': 0.359, 'learning_rate': 6.962500000000001e-05, 'epoch': 7.59}\n",
+      "{'loss': 0.2755, 'learning_rate': 6.96e-05, 'epoch': 7.6}\n",
+      "{'loss': 0.2345, 'learning_rate': 6.9575e-05, 'epoch': 7.61}\n",
+      "{'loss': 0.2871, 'learning_rate': 6.955000000000001e-05, 'epoch': 7.61}\n",
+      "{'loss': 0.2237, 'learning_rate': 6.952500000000001e-05, 'epoch': 7.62}\n",
+      "{'loss': 0.1809, 'learning_rate': 6.95e-05, 'epoch': 7.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3df9cb89eb6e44f18d59f2afc12a7603",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3537389039993286, 'eval_mean_iou': 0.23116999766897164, 'eval_mean_accuracy': 0.2668919186326207, 'eval_overall_accuracy': 0.44820497729038233, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.5858396401180117, 'eval_accuracy_RV': 0.32778534902423, 'eval_accuracy_RA': 0.40149338648890753, 'eval_accuracy_LA': 0.5005814392250221, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.2604738019630485, 'eval_accuracy_VSD': 0.2541383032956488, 'eval_accuracy_AK': 0.3386072662113382, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.5720599512228159, 'eval_iou_RV': 0.32071241729958944, 'eval_iou_RA': 0.38035068539231354, 'eval_iou_LA': 0.4702789540512146, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.23143947288263303, 'eval_iou_VSD': 0.23589133369518323, 'eval_iou_AK': 0.3321371598149381, 'eval_runtime': 4.3307, 'eval_samples_per_second': 18.704, 'eval_steps_per_second': 9.467, 'epoch': 7.62}\n",
+      "{'loss': 0.1716, 'learning_rate': 6.9475e-05, 'epoch': 7.63}\n",
+      "{'loss': 0.1526, 'learning_rate': 6.945000000000001e-05, 'epoch': 7.64}\n",
+      "{'loss': 0.1826, 'learning_rate': 6.942500000000001e-05, 'epoch': 7.64}\n",
+      "{'loss': 0.2989, 'learning_rate': 6.939999999999999e-05, 'epoch': 7.65}\n",
+      "{'loss': 0.1465, 'learning_rate': 6.9375e-05, 'epoch': 7.66}\n",
+      "{'loss': 0.1257, 'learning_rate': 6.935e-05, 'epoch': 7.66}\n",
+      "{'loss': 0.2391, 'learning_rate': 6.9325e-05, 'epoch': 7.67}\n",
+      "{'loss': 0.1103, 'learning_rate': 6.93e-05, 'epoch': 7.67}\n",
+      "{'loss': 0.1599, 'learning_rate': 6.9275e-05, 'epoch': 7.68}\n",
+      "{'loss': 0.0872, 'learning_rate': 6.925e-05, 'epoch': 7.69}\n",
+      "{'loss': 0.275, 'learning_rate': 6.9225e-05, 'epoch': 7.69}\n",
+      "{'loss': 0.2316, 'learning_rate': 6.92e-05, 'epoch': 7.7}\n",
+      "{'loss': 0.1933, 'learning_rate': 6.9175e-05, 'epoch': 7.71}\n",
+      "{'loss': 0.1351, 'learning_rate': 6.915e-05, 'epoch': 7.71}\n",
+      "{'loss': 0.1145, 'learning_rate': 6.9125e-05, 'epoch': 7.72}\n",
+      "{'loss': 0.1846, 'learning_rate': 6.91e-05, 'epoch': 7.72}\n",
+      "{'loss': 0.1251, 'learning_rate': 6.9075e-05, 'epoch': 7.73}\n",
+      "{'loss': 0.1365, 'learning_rate': 6.905e-05, 'epoch': 7.74}\n",
+      "{'loss': 0.3023, 'learning_rate': 6.902500000000001e-05, 'epoch': 7.74}\n",
+      "{'loss': 0.2655, 'learning_rate': 6.9e-05, 'epoch': 7.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "904942481c94422b9d29b2ef15cff79c",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.4182012975215912, 'eval_mean_iou': 0.18672982115508585, 'eval_mean_accuracy': 0.21210399423568999, 'eval_overall_accuracy': 0.3587697640753107, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.45526607819915815, 'eval_accuracy_RV': 0.197654039055354, 'eval_accuracy_RA': 0.3891016277549571, 'eval_accuracy_LA': 0.476253610411707, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.1583429561200924, 'eval_accuracy_VSD': 0.21656370887935947, 'eval_accuracy_AK': 0.22785792193627133, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.4501136604108586, 'eval_iou_RV': 0.19574968043567142, 'eval_iou_RA': 0.37554011188762165, 'eval_iou_LA': 0.45027810660482914, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.15140823808496873, 'eval_iou_VSD': 0.20448801897143667, 'eval_iou_AK': 0.2264502163105581, 'eval_runtime': 4.4463, 'eval_samples_per_second': 18.217, 'eval_steps_per_second': 9.221, 'epoch': 7.75}\n",
+      "{'loss': 0.3803, 'learning_rate': 6.8975e-05, 'epoch': 7.76}\n",
+      "{'loss': 0.3047, 'learning_rate': 6.895000000000001e-05, 'epoch': 7.76}\n",
+      "{'loss': 0.2437, 'learning_rate': 6.892500000000001e-05, 'epoch': 7.77}\n",
+      "{'loss': 0.0488, 'learning_rate': 6.89e-05, 'epoch': 7.78}\n",
+      "{'loss': 0.2673, 'learning_rate': 6.887500000000001e-05, 'epoch': 7.78}\n",
+      "{'loss': 0.0985, 'learning_rate': 6.885e-05, 'epoch': 7.79}\n",
+      "{'loss': 0.46, 'learning_rate': 6.8825e-05, 'epoch': 7.79}\n",
+      "{'loss': 0.2993, 'learning_rate': 6.879999999999999e-05, 'epoch': 7.8}\n",
+      "{'loss': 0.4396, 'learning_rate': 6.8775e-05, 'epoch': 7.81}\n",
+      "{'loss': 0.2601, 'learning_rate': 6.875e-05, 'epoch': 7.81}\n",
+      "{'loss': 0.1549, 'learning_rate': 6.8725e-05, 'epoch': 7.82}\n",
+      "{'loss': 0.3717, 'learning_rate': 6.87e-05, 'epoch': 7.83}\n",
+      "{'loss': 0.2615, 'learning_rate': 6.8675e-05, 'epoch': 7.83}\n",
+      "{'loss': 0.1541, 'learning_rate': 6.865e-05, 'epoch': 7.84}\n",
+      "{'loss': 0.202, 'learning_rate': 6.8625e-05, 'epoch': 7.84}\n",
+      "{'loss': 0.3026, 'learning_rate': 6.860000000000001e-05, 'epoch': 7.85}\n",
+      "{'loss': 0.1142, 'learning_rate': 6.8575e-05, 'epoch': 7.86}\n",
+      "{'loss': 0.2811, 'learning_rate': 6.855e-05, 'epoch': 7.86}\n",
+      "{'loss': 0.3164, 'learning_rate': 6.852500000000001e-05, 'epoch': 7.87}\n",
+      "{'loss': 0.2128, 'learning_rate': 6.850000000000001e-05, 'epoch': 7.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7f4e195007f44690a2de35db05e04b01",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3219994604587555, 'eval_mean_iou': 0.3554273816804262, 'eval_mean_accuracy': 0.4278522738430638, 'eval_overall_accuracy': 0.6905105931332348, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.831291894004254, 'eval_accuracy_RV': 0.5676593184650424, 'eval_accuracy_RA': 0.6957401564000549, 'eval_accuracy_LA': 0.7392356561172895, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.43987261836027713, 'eval_accuracy_VSD': 0.3765256244939575, 'eval_accuracy_AK': 0.6281974705897629, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7753923165160749, 'eval_iou_RV': 0.5424152347880155, 'eval_iou_RA': 0.616310803154785, 'eval_iou_LA': 0.6664589463787859, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.38089397868949787, 'eval_iou_VSD': 0.3412257876035248, 'eval_iou_AK': 0.5870041313540043, 'eval_runtime': 4.3548, 'eval_samples_per_second': 18.6, 'eval_steps_per_second': 9.415, 'epoch': 7.88}\n",
+      "{'loss': 0.25, 'learning_rate': 6.8475e-05, 'epoch': 7.88}\n",
+      "{'loss': 0.1932, 'learning_rate': 6.845e-05, 'epoch': 7.89}\n",
+      "{'loss': 0.1993, 'learning_rate': 6.842500000000001e-05, 'epoch': 7.89}\n",
+      "{'loss': 0.2193, 'learning_rate': 6.840000000000001e-05, 'epoch': 7.9}\n",
+      "{'loss': 0.1572, 'learning_rate': 6.8375e-05, 'epoch': 7.91}\n",
+      "{'loss': 0.2374, 'learning_rate': 6.835000000000001e-05, 'epoch': 7.91}\n",
+      "{'loss': 0.1129, 'learning_rate': 6.832500000000001e-05, 'epoch': 7.92}\n",
+      "{'loss': 0.26, 'learning_rate': 6.83e-05, 'epoch': 7.92}\n",
+      "{'loss': 0.1541, 'learning_rate': 6.8275e-05, 'epoch': 7.93}\n",
+      "{'loss': 0.2783, 'learning_rate': 6.825e-05, 'epoch': 7.94}\n",
+      "{'loss': 0.2495, 'learning_rate': 6.8225e-05, 'epoch': 7.94}\n",
+      "{'loss': 0.2218, 'learning_rate': 6.82e-05, 'epoch': 7.95}\n",
+      "{'loss': 0.1445, 'learning_rate': 6.8175e-05, 'epoch': 7.96}\n",
+      "{'loss': 0.1757, 'learning_rate': 6.815e-05, 'epoch': 7.96}\n",
+      "{'loss': 0.2231, 'learning_rate': 6.8125e-05, 'epoch': 7.97}\n",
+      "{'loss': 0.2359, 'learning_rate': 6.81e-05, 'epoch': 7.97}\n",
+      "{'loss': 0.3037, 'learning_rate': 6.8075e-05, 'epoch': 7.98}\n",
+      "{'loss': 0.152, 'learning_rate': 6.805e-05, 'epoch': 7.99}\n",
+      "{'loss': 0.2211, 'learning_rate': 6.8025e-05, 'epoch': 7.99}\n",
+      "{'loss': 0.2663, 'learning_rate': 6.800000000000001e-05, 'epoch': 8.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d8e290312a1446ea9f131f708db50746",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.32541424036026, 'eval_mean_iou': 0.3097560876580756, 'eval_mean_accuracy': 0.36638864472744653, 'eval_overall_accuracy': 0.5918400632710072, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7264364404378008, 'eval_accuracy_RV': 0.4798062579421352, 'eval_accuracy_RA': 0.6163659180231291, 'eval_accuracy_LA': 0.600257960057355, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3307863019630485, 'eval_accuracy_VSD': 0.40733799142351634, 'eval_accuracy_AK': 0.5028955774274807, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6981703318087891, 'eval_iou_RV': 0.4673938393642023, 'eval_iou_RA': 0.5498277643196781, 'eval_iou_LA': 0.5526068550838371, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2990270834522635, 'eval_iou_VSD': 0.3607739502270856, 'eval_iou_AK': 0.47951713998297607, 'eval_runtime': 4.4264, 'eval_samples_per_second': 18.299, 'eval_steps_per_second': 9.263, 'epoch': 8.0}\n",
+      "{'loss': 0.3722, 'learning_rate': 6.7975e-05, 'epoch': 8.01}\n",
+      "{'loss': 0.2157, 'learning_rate': 6.795e-05, 'epoch': 8.01}\n",
+      "{'loss': 0.3808, 'learning_rate': 6.792500000000001e-05, 'epoch': 8.02}\n",
+      "{'loss': 0.5117, 'learning_rate': 6.790000000000001e-05, 'epoch': 8.03}\n",
+      "{'loss': 0.2142, 'learning_rate': 6.7875e-05, 'epoch': 8.03}\n",
+      "{'loss': 0.1907, 'learning_rate': 6.785e-05, 'epoch': 8.04}\n",
+      "{'loss': 0.3434, 'learning_rate': 6.782500000000001e-05, 'epoch': 8.04}\n",
+      "{'loss': 0.105, 'learning_rate': 6.780000000000001e-05, 'epoch': 8.05}\n",
+      "{'loss': 0.344, 'learning_rate': 6.7775e-05, 'epoch': 8.06}\n",
+      "{'loss': 0.1982, 'learning_rate': 6.775000000000001e-05, 'epoch': 8.06}\n",
+      "{'loss': 0.2038, 'learning_rate': 6.7725e-05, 'epoch': 8.07}\n",
+      "{'loss': 0.2426, 'learning_rate': 6.77e-05, 'epoch': 8.07}\n",
+      "{'loss': 0.2164, 'learning_rate': 6.7675e-05, 'epoch': 8.08}\n",
+      "{'loss': 0.1371, 'learning_rate': 6.765e-05, 'epoch': 8.09}\n",
+      "{'loss': 0.2398, 'learning_rate': 6.7625e-05, 'epoch': 8.09}\n",
+      "{'loss': 0.139, 'learning_rate': 6.76e-05, 'epoch': 8.1}\n",
+      "{'loss': 0.1387, 'learning_rate': 6.7575e-05, 'epoch': 8.11}\n",
+      "{'loss': 0.2279, 'learning_rate': 6.755e-05, 'epoch': 8.11}\n",
+      "{'loss': 0.3186, 'learning_rate': 6.7525e-05, 'epoch': 8.12}\n",
+      "{'loss': 0.2143, 'learning_rate': 6.750000000000001e-05, 'epoch': 8.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3066ad466fd741cda576b61d3ffc4f76",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3444731831550598, 'eval_mean_iou': 0.27840091006912676, 'eval_mean_accuracy': 0.32612558437004857, 'eval_overall_accuracy': 0.5211305473028678, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6549694082411305, 'eval_accuracy_RV': 0.42278249445968924, 'eval_accuracy_RA': 0.4913669267954129, 'eval_accuracy_LA': 0.5234719639953622, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.37240184757505773, 'eval_accuracy_VSD': 0.35704111314361114, 'eval_accuracy_AK': 0.43922208949022257, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6334414027141162, 'eval_iou_RV': 0.412557020867466, 'eval_iou_RA': 0.4599200818820792, 'eval_iou_LA': 0.4928376154774035, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3163097199341021, 'eval_iou_VSD': 0.32476167096272657, 'eval_iou_AK': 0.42258249892250127, 'eval_runtime': 4.4759, 'eval_samples_per_second': 18.097, 'eval_steps_per_second': 9.16, 'epoch': 8.12}\n",
+      "{'loss': 0.3485, 'learning_rate': 6.7475e-05, 'epoch': 8.13}\n",
+      "{'loss': 0.218, 'learning_rate': 6.745e-05, 'epoch': 8.14}\n",
+      "{'loss': 0.1579, 'learning_rate': 6.7425e-05, 'epoch': 8.14}\n",
+      "{'loss': 0.1818, 'learning_rate': 6.740000000000001e-05, 'epoch': 8.15}\n",
+      "{'loss': 0.1815, 'learning_rate': 6.7375e-05, 'epoch': 8.16}\n",
+      "{'loss': 0.286, 'learning_rate': 6.735e-05, 'epoch': 8.16}\n",
+      "{'loss': 0.1377, 'learning_rate': 6.732500000000001e-05, 'epoch': 8.17}\n",
+      "{'loss': 0.1786, 'learning_rate': 6.730000000000001e-05, 'epoch': 8.18}\n",
+      "{'loss': 0.0927, 'learning_rate': 6.7275e-05, 'epoch': 8.18}\n",
+      "{'loss': 0.3408, 'learning_rate': 6.725000000000001e-05, 'epoch': 8.19}\n",
+      "{'loss': 0.2375, 'learning_rate': 6.722500000000001e-05, 'epoch': 8.19}\n",
+      "{'loss': 0.1535, 'learning_rate': 6.720000000000001e-05, 'epoch': 8.2}\n",
+      "{'loss': 0.2243, 'learning_rate': 6.717499999999999e-05, 'epoch': 8.21}\n",
+      "{'loss': 0.1166, 'learning_rate': 6.715e-05, 'epoch': 8.21}\n",
+      "{'loss': 0.172, 'learning_rate': 6.7125e-05, 'epoch': 8.22}\n",
+      "{'loss': 0.2242, 'learning_rate': 6.71e-05, 'epoch': 8.22}\n",
+      "{'loss': 0.2384, 'learning_rate': 6.7075e-05, 'epoch': 8.23}\n",
+      "{'loss': 0.3691, 'learning_rate': 6.705e-05, 'epoch': 8.24}\n",
+      "{'loss': 0.2365, 'learning_rate': 6.7025e-05, 'epoch': 8.24}\n",
+      "{'loss': 0.1551, 'learning_rate': 6.7e-05, 'epoch': 8.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "310cb9d9da224b36ab2c62a1976556ae",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.34310874342918396, 'eval_mean_iou': 0.3662034925593534, 'eval_mean_accuracy': 0.44512530767031444, 'eval_overall_accuracy': 0.7119470548904118, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.8743627338382739, 'eval_accuracy_RV': 0.5733423574405913, 'eval_accuracy_RA': 0.7078171781814661, 'eval_accuracy_LA': 0.7641860879945663, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4977627020785219, 'eval_accuracy_VSD': 0.48017812696794315, 'eval_accuracy_AK': 0.5536038902017815, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.8002630641305847, 'eval_iou_RV': 0.5518587673608547, 'eval_iou_RA': 0.6212818029038993, 'eval_iou_LA': 0.6804264462658463, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.4192928195268745, 'eval_iou_VSD': 0.4189697465249387, 'eval_iou_AK': 0.5361457714398891, 'eval_runtime': 4.3846, 'eval_samples_per_second': 18.474, 'eval_steps_per_second': 9.351, 'epoch': 8.25}\n",
+      "{'loss': 0.2917, 'learning_rate': 6.6975e-05, 'epoch': 8.26}\n",
+      "{'loss': 0.2269, 'learning_rate': 6.695e-05, 'epoch': 8.26}\n",
+      "{'loss': 0.2892, 'learning_rate': 6.6925e-05, 'epoch': 8.27}\n",
+      "{'loss': 0.2273, 'learning_rate': 6.690000000000001e-05, 'epoch': 8.28}\n",
+      "{'loss': 0.1143, 'learning_rate': 6.6875e-05, 'epoch': 8.28}\n",
+      "{'loss': 0.2491, 'learning_rate': 6.685e-05, 'epoch': 8.29}\n",
+      "{'loss': 0.4581, 'learning_rate': 6.6825e-05, 'epoch': 8.29}\n",
+      "{'loss': 0.2773, 'learning_rate': 6.680000000000001e-05, 'epoch': 8.3}\n",
+      "{'loss': 0.4642, 'learning_rate': 6.6775e-05, 'epoch': 8.31}\n",
+      "{'loss': 0.1166, 'learning_rate': 6.675e-05, 'epoch': 8.31}\n",
+      "{'loss': 0.3059, 'learning_rate': 6.672500000000001e-05, 'epoch': 8.32}\n",
+      "{'loss': 0.2969, 'learning_rate': 6.670000000000001e-05, 'epoch': 8.32}\n",
+      "{'loss': 0.1477, 'learning_rate': 6.6675e-05, 'epoch': 8.33}\n",
+      "{'loss': 0.3331, 'learning_rate': 6.665000000000001e-05, 'epoch': 8.34}\n",
+      "{'loss': 0.3976, 'learning_rate': 6.6625e-05, 'epoch': 8.34}\n",
+      "{'loss': 0.1846, 'learning_rate': 6.66e-05, 'epoch': 8.35}\n",
+      "{'loss': 0.2904, 'learning_rate': 6.657499999999999e-05, 'epoch': 8.36}\n",
+      "{'loss': 0.2576, 'learning_rate': 6.655e-05, 'epoch': 8.36}\n",
+      "{'loss': 0.3237, 'learning_rate': 6.6525e-05, 'epoch': 8.37}\n",
+      "{'loss': 0.1824, 'learning_rate': 6.65e-05, 'epoch': 8.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "ed67f98e36594b93b5b7d90beafbfa72",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3123089671134949, 'eval_mean_iou': 0.32974938956939925, 'eval_mean_accuracy': 0.3922163093127187, 'eval_overall_accuracy': 0.6215500098455227, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7419001196225773, 'eval_accuracy_RV': 0.5098712683474834, 'eval_accuracy_RA': 0.6051080193361471, 'eval_accuracy_LA': 0.6732757496964167, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4096420323325635, 'eval_accuracy_VSD': 0.39839415839505804, 'eval_accuracy_AK': 0.5839717453969409, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7094974617044737, 'eval_iou_RV': 0.49371975794466966, 'eval_iou_RA': 0.5628266405448059, 'eval_iou_LA': 0.6185087495391247, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.35608811235972676, 'eval_iou_VSD': 0.3550876677179665, 'eval_iou_AK': 0.531514895452625, 'eval_runtime': 4.46, 'eval_samples_per_second': 18.161, 'eval_steps_per_second': 9.193, 'epoch': 8.38}\n",
+      "{'loss': 0.3009, 'learning_rate': 6.6475e-05, 'epoch': 8.38}\n",
+      "{'loss': 0.3229, 'learning_rate': 6.645e-05, 'epoch': 8.39}\n",
+      "{'loss': 0.1777, 'learning_rate': 6.6425e-05, 'epoch': 8.39}\n",
+      "{'loss': 0.2328, 'learning_rate': 6.64e-05, 'epoch': 8.4}\n",
+      "{'loss': 0.1685, 'learning_rate': 6.6375e-05, 'epoch': 8.41}\n",
+      "{'loss': 0.1477, 'learning_rate': 6.635e-05, 'epoch': 8.41}\n",
+      "{'loss': 0.2356, 'learning_rate': 6.6325e-05, 'epoch': 8.42}\n",
+      "{'loss': 0.0876, 'learning_rate': 6.630000000000001e-05, 'epoch': 8.43}\n",
+      "{'loss': 0.2147, 'learning_rate': 6.6275e-05, 'epoch': 8.43}\n",
+      "{'loss': 0.2207, 'learning_rate': 6.625e-05, 'epoch': 8.44}\n",
+      "{'loss': 0.2535, 'learning_rate': 6.6225e-05, 'epoch': 8.44}\n",
+      "{'loss': 0.2844, 'learning_rate': 6.620000000000001e-05, 'epoch': 8.45}\n",
+      "{'loss': 0.2098, 'learning_rate': 6.6175e-05, 'epoch': 8.46}\n",
+      "{'loss': 0.166, 'learning_rate': 6.615e-05, 'epoch': 8.46}\n",
+      "{'loss': 0.131, 'learning_rate': 6.612500000000001e-05, 'epoch': 8.47}\n",
+      "{'loss': 0.1609, 'learning_rate': 6.610000000000001e-05, 'epoch': 8.47}\n",
+      "{'loss': 0.105, 'learning_rate': 6.6075e-05, 'epoch': 8.48}\n",
+      "{'loss': 0.4412, 'learning_rate': 6.605e-05, 'epoch': 8.49}\n",
+      "{'loss': 0.1719, 'learning_rate': 6.6025e-05, 'epoch': 8.49}\n",
+      "{'loss': 0.1498, 'learning_rate': 6.6e-05, 'epoch': 8.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1d30a1e8ce7e459385737d23b22a975f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3486652970314026, 'eval_mean_iou': 0.28340409926954196, 'eval_mean_accuracy': 0.3306036977182456, 'eval_overall_accuracy': 0.5597615111470792, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7668045856315684, 'eval_accuracy_RV': 0.3998017151942639, 'eval_accuracy_RA': 0.4495835788012557, 'eval_accuracy_LA': 0.6017038399001091, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.39125649538106233, 'eval_accuracy_VSD': 0.29142801451404926, 'eval_accuracy_AK': 0.4054587477601475, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7274417538475253, 'eval_iou_RV': 0.3913034988186061, 'eval_iou_RA': 0.4343674161574223, 'eval_iou_LA': 0.5614621077295366, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3351959625000966, 'eval_iou_VSD': 0.27007704973841995, 'eval_iou_AK': 0.3975973031733552, 'eval_runtime': 4.448, 'eval_samples_per_second': 18.21, 'eval_steps_per_second': 9.218, 'epoch': 8.5}\n",
+      "{'loss': 0.3012, 'learning_rate': 6.5975e-05, 'epoch': 8.51}\n",
+      "{'loss': 0.1993, 'learning_rate': 6.595e-05, 'epoch': 8.51}\n",
+      "{'loss': 0.2582, 'learning_rate': 6.5925e-05, 'epoch': 8.52}\n",
+      "{'loss': 0.5774, 'learning_rate': 6.59e-05, 'epoch': 8.53}\n",
+      "{'loss': 0.1555, 'learning_rate': 6.5875e-05, 'epoch': 8.53}\n",
+      "{'loss': 0.124, 'learning_rate': 6.585e-05, 'epoch': 8.54}\n",
+      "{'loss': 0.1276, 'learning_rate': 6.5825e-05, 'epoch': 8.54}\n",
+      "{'loss': 0.1354, 'learning_rate': 6.58e-05, 'epoch': 8.55}\n",
+      "{'loss': 0.1662, 'learning_rate': 6.5775e-05, 'epoch': 8.56}\n",
+      "{'loss': 0.2179, 'learning_rate': 6.575e-05, 'epoch': 8.56}\n",
+      "{'loss': 0.1213, 'learning_rate': 6.5725e-05, 'epoch': 8.57}\n",
+      "{'loss': 0.2474, 'learning_rate': 6.570000000000001e-05, 'epoch': 8.57}\n",
+      "{'loss': 0.149, 'learning_rate': 6.5675e-05, 'epoch': 8.58}\n",
+      "{'loss': 0.331, 'learning_rate': 6.565e-05, 'epoch': 8.59}\n",
+      "{'loss': 0.2374, 'learning_rate': 6.562500000000001e-05, 'epoch': 8.59}\n",
+      "{'loss': 0.199, 'learning_rate': 6.560000000000001e-05, 'epoch': 8.6}\n",
+      "{'loss': 0.118, 'learning_rate': 6.557500000000001e-05, 'epoch': 8.61}\n",
+      "{'loss': 0.2923, 'learning_rate': 6.555e-05, 'epoch': 8.61}\n",
+      "{'loss': 0.2751, 'learning_rate': 6.552500000000001e-05, 'epoch': 8.62}\n",
+      "{'loss': 0.2182, 'learning_rate': 6.55e-05, 'epoch': 8.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "64f2ca48904946ce90b8cf44e59dc2b2",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.34380170702934265, 'eval_mean_iou': 0.36483878154303556, 'eval_mean_accuracy': 0.44614546118356324, 'eval_overall_accuracy': 0.6935856960784526, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.8259469126337551, 'eval_accuracy_RV': 0.610554522182729, 'eval_accuracy_RA': 0.703745773244131, 'eval_accuracy_LA': 0.6566627103643686, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.5209385825635104, 'eval_accuracy_VSD': 0.4739031996881279, 'eval_accuracy_AK': 0.66970291115901, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7803217817422152, 'eval_iou_RV': 0.5812047474623516, 'eval_iou_RA': 0.601508543758633, 'eval_iou_LA': 0.6029848583641237, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.42587634872521035, 'eval_iou_VSD': 0.40230770209895245, 'eval_iou_AK': 0.6190226148219049, 'eval_runtime': 4.4633, 'eval_samples_per_second': 18.148, 'eval_steps_per_second': 9.186, 'epoch': 8.62}\n",
+      "{'loss': 0.4212, 'learning_rate': 6.5475e-05, 'epoch': 8.63}\n",
+      "{'loss': 0.1409, 'learning_rate': 6.545e-05, 'epoch': 8.64}\n",
+      "{'loss': 0.2284, 'learning_rate': 6.5425e-05, 'epoch': 8.64}\n",
+      "{'loss': 0.1733, 'learning_rate': 6.54e-05, 'epoch': 8.65}\n",
+      "{'loss': 0.2025, 'learning_rate': 6.5375e-05, 'epoch': 8.66}\n",
+      "{'loss': 0.2517, 'learning_rate': 6.535e-05, 'epoch': 8.66}\n",
+      "{'loss': 0.1575, 'learning_rate': 6.5325e-05, 'epoch': 8.67}\n",
+      "{'loss': 0.519, 'learning_rate': 6.53e-05, 'epoch': 8.68}\n",
+      "{'loss': 0.193, 'learning_rate': 6.527500000000001e-05, 'epoch': 8.68}\n",
+      "{'loss': 0.3529, 'learning_rate': 6.525e-05, 'epoch': 8.69}\n",
+      "{'loss': 0.2046, 'learning_rate': 6.5225e-05, 'epoch': 8.69}\n",
+      "{'loss': 0.1135, 'learning_rate': 6.52e-05, 'epoch': 8.7}\n",
+      "{'loss': 0.1058, 'learning_rate': 6.517500000000001e-05, 'epoch': 8.71}\n",
+      "{'loss': 0.2294, 'learning_rate': 6.515e-05, 'epoch': 8.71}\n",
+      "{'loss': 0.4184, 'learning_rate': 6.5125e-05, 'epoch': 8.72}\n",
+      "{'loss': 0.1201, 'learning_rate': 6.510000000000001e-05, 'epoch': 8.72}\n",
+      "{'loss': 0.09, 'learning_rate': 6.507500000000001e-05, 'epoch': 8.73}\n",
+      "{'loss': 0.2168, 'learning_rate': 6.505e-05, 'epoch': 8.74}\n",
+      "{'loss': 0.2813, 'learning_rate': 6.502500000000001e-05, 'epoch': 8.74}\n",
+      "{'loss': 0.2837, 'learning_rate': 6.500000000000001e-05, 'epoch': 8.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "80fc43b98e984ba9a3206ef1b8f85ac4",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.35371628403663635, 'eval_mean_iou': 0.27077984934682003, 'eval_mean_accuracy': 0.31745265453377514, 'eval_overall_accuracy': 0.517004083187093, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6092495696868633, 'eval_accuracy_RV': 0.44599961939139454, 'eval_accuracy_RA': 0.5789404662949005, 'eval_accuracy_LA': 0.5699956777969113, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3322477627020785, 'eval_accuracy_VSD': 0.2793729570875941, 'eval_accuracy_AK': 0.3587204923780092, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.5946602842811191, 'eval_iou_RV': 0.4312823990870006, 'eval_iou_RA': 0.5342467283664453, 'eval_iou_LA': 0.5296544865430007, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.28917469515307126, 'eval_iou_VSD': 0.2590383639535935, 'eval_iou_AK': 0.3405213854307901, 'eval_runtime': 4.3774, 'eval_samples_per_second': 18.504, 'eval_steps_per_second': 9.366, 'epoch': 8.75}\n",
+      "{'loss': 0.3871, 'learning_rate': 6.497500000000001e-05, 'epoch': 8.76}\n",
+      "{'loss': 0.1785, 'learning_rate': 6.494999999999999e-05, 'epoch': 8.76}\n",
+      "{'loss': 0.2731, 'learning_rate': 6.4925e-05, 'epoch': 8.77}\n",
+      "{'loss': 0.1169, 'learning_rate': 6.49e-05, 'epoch': 8.78}\n",
+      "{'loss': 0.1946, 'learning_rate': 6.4875e-05, 'epoch': 8.78}\n",
+      "{'loss': 0.1673, 'learning_rate': 6.485e-05, 'epoch': 8.79}\n",
+      "{'loss': 0.1052, 'learning_rate': 6.4825e-05, 'epoch': 8.79}\n",
+      "{'loss': 0.2248, 'learning_rate': 6.48e-05, 'epoch': 8.8}\n",
+      "{'loss': 0.1758, 'learning_rate': 6.4775e-05, 'epoch': 8.81}\n",
+      "{'loss': 0.2132, 'learning_rate': 6.475e-05, 'epoch': 8.81}\n",
+      "{'loss': 0.1394, 'learning_rate': 6.4725e-05, 'epoch': 8.82}\n",
+      "{'loss': 0.5533, 'learning_rate': 6.47e-05, 'epoch': 8.82}\n",
+      "{'loss': 0.1564, 'learning_rate': 6.467500000000001e-05, 'epoch': 8.83}\n",
+      "{'loss': 0.177, 'learning_rate': 6.465e-05, 'epoch': 8.84}\n",
+      "{'loss': 0.527, 'learning_rate': 6.4625e-05, 'epoch': 8.84}\n",
+      "{'loss': 0.2008, 'learning_rate': 6.460000000000001e-05, 'epoch': 8.85}\n",
+      "{'loss': 0.2297, 'learning_rate': 6.457500000000001e-05, 'epoch': 8.86}\n",
+      "{'loss': 0.1128, 'learning_rate': 6.455e-05, 'epoch': 8.86}\n",
+      "{'loss': 0.1317, 'learning_rate': 6.4525e-05, 'epoch': 8.87}\n",
+      "{'loss': 0.4371, 'learning_rate': 6.450000000000001e-05, 'epoch': 8.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "dfe8b2cef9784ba1bba30d413f619bd6",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3187980651855469, 'eval_mean_iou': 0.29042493667527636, 'eval_mean_accuracy': 0.3381351567807852, 'eval_overall_accuracy': 0.5742390276518536, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7239984965142399, 'eval_accuracy_RV': 0.4785493287169193, 'eval_accuracy_RA': 0.5373205394107156, 'eval_accuracy_LA': 0.6333519714048532, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.2457599595842956, 'eval_accuracy_VSD': 0.3279080576963445, 'eval_accuracy_AK': 0.4344632144804841, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6937770046895078, 'eval_iou_RV': 0.4650091490557906, 'eval_iou_RA': 0.5134966296987552, 'eval_iou_LA': 0.5830866086528121, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.22555992548126683, 'eval_iou_VSD': 0.3017856403604399, 'eval_iou_AK': 0.411959345489467, 'eval_runtime': 4.3484, 'eval_samples_per_second': 18.628, 'eval_steps_per_second': 9.429, 'epoch': 8.88}\n",
+      "{'loss': 0.2683, 'learning_rate': 6.447500000000001e-05, 'epoch': 8.88}\n",
+      "{'loss': 0.2035, 'learning_rate': 6.445e-05, 'epoch': 8.89}\n",
+      "{'loss': 0.1017, 'learning_rate': 6.442500000000001e-05, 'epoch': 8.89}\n",
+      "{'loss': 0.1656, 'learning_rate': 6.440000000000001e-05, 'epoch': 8.9}\n",
+      "{'loss': 0.1387, 'learning_rate': 6.4375e-05, 'epoch': 8.91}\n",
+      "{'loss': 0.142, 'learning_rate': 6.435e-05, 'epoch': 8.91}\n",
+      "{'loss': 0.0831, 'learning_rate': 6.4325e-05, 'epoch': 8.92}\n",
+      "{'loss': 0.2503, 'learning_rate': 6.43e-05, 'epoch': 8.93}\n",
+      "{'loss': 0.1459, 'learning_rate': 6.4275e-05, 'epoch': 8.93}\n",
+      "{'loss': 0.2725, 'learning_rate': 6.425e-05, 'epoch': 8.94}\n",
+      "{'loss': 0.1229, 'learning_rate': 6.4225e-05, 'epoch': 8.94}\n",
+      "{'loss': 0.2656, 'learning_rate': 6.42e-05, 'epoch': 8.95}\n",
+      "{'loss': 0.1712, 'learning_rate': 6.4175e-05, 'epoch': 8.96}\n",
+      "{'loss': 0.1025, 'learning_rate': 6.415e-05, 'epoch': 8.96}\n",
+      "{'loss': 0.1791, 'learning_rate': 6.4125e-05, 'epoch': 8.97}\n",
+      "{'loss': 0.3154, 'learning_rate': 6.41e-05, 'epoch': 8.97}\n",
+      "{'loss': 0.129, 'learning_rate': 6.407500000000001e-05, 'epoch': 8.98}\n",
+      "{'loss': 0.0906, 'learning_rate': 6.405e-05, 'epoch': 8.99}\n",
+      "{'loss': 0.2655, 'learning_rate': 6.4025e-05, 'epoch': 8.99}\n",
+      "{'loss': 0.3297, 'learning_rate': 6.400000000000001e-05, 'epoch': 9.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1d107c58f47e42d4b34f3a9c71d9a98a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.325215220451355, 'eval_mean_iou': 0.33954333636743317, 'eval_mean_accuracy': 0.4085204275271629, 'eval_overall_accuracy': 0.6467707767576422, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7670820145515943, 'eval_accuracy_RV': 0.5065302000650718, 'eval_accuracy_RA': 0.6724334815556076, 'eval_accuracy_LA': 0.7057111396208811, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0004870832731995959, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3931690242494226, 'eval_accuracy_VSD': 0.4357063603922392, 'eval_accuracy_AK': 0.6040849715636118, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7274239437844903, 'eval_iou_RV': 0.4883234055648767, 'eval_iou_RA': 0.6155063583345337, 'eval_iou_LA': 0.6393560056312991, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.00048420939366223707, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3294927043169275, 'eval_iou_VSD': 0.3834830059451149, 'eval_iou_AK': 0.5509070670708601, 'eval_runtime': 4.4236, 'eval_samples_per_second': 18.311, 'eval_steps_per_second': 9.269, 'epoch': 9.0}\n",
+      "{'loss': 0.1888, 'learning_rate': 6.397500000000001e-05, 'epoch': 9.01}\n",
+      "{'loss': 0.1746, 'learning_rate': 6.395e-05, 'epoch': 9.01}\n",
+      "{'loss': 0.2282, 'learning_rate': 6.3925e-05, 'epoch': 9.02}\n",
+      "{'loss': 0.2267, 'learning_rate': 6.390000000000001e-05, 'epoch': 9.03}\n",
+      "{'loss': 0.2045, 'learning_rate': 6.387500000000001e-05, 'epoch': 9.03}\n",
+      "{'loss': 0.1329, 'learning_rate': 6.385e-05, 'epoch': 9.04}\n",
+      "{'loss': 0.1285, 'learning_rate': 6.3825e-05, 'epoch': 9.04}\n",
+      "{'loss': 0.082, 'learning_rate': 6.38e-05, 'epoch': 9.05}\n",
+      "{'loss': 0.1492, 'learning_rate': 6.3775e-05, 'epoch': 9.06}\n",
+      "{'loss': 0.2109, 'learning_rate': 6.375e-05, 'epoch': 9.06}\n",
+      "{'loss': 0.1786, 'learning_rate': 6.3725e-05, 'epoch': 9.07}\n",
+      "{'loss': 0.158, 'learning_rate': 6.37e-05, 'epoch': 9.07}\n",
+      "{'loss': 0.1528, 'learning_rate': 6.3675e-05, 'epoch': 9.08}\n",
+      "{'loss': 0.1064, 'learning_rate': 6.365e-05, 'epoch': 9.09}\n",
+      "{'loss': 0.2029, 'learning_rate': 6.3625e-05, 'epoch': 9.09}\n",
+      "{'loss': 0.2059, 'learning_rate': 6.36e-05, 'epoch': 9.1}\n",
+      "{'loss': 0.2803, 'learning_rate': 6.3575e-05, 'epoch': 9.11}\n",
+      "{'loss': 0.3202, 'learning_rate': 6.355e-05, 'epoch': 9.11}\n",
+      "{'loss': 0.3254, 'learning_rate': 6.3525e-05, 'epoch': 9.12}\n",
+      "{'loss': 0.1795, 'learning_rate': 6.35e-05, 'epoch': 9.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "509f6e0de7a1483db3c57ac2d1250d7a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.334203839302063, 'eval_mean_iou': 0.30025671833646, 'eval_mean_accuracy': 0.35497517016225705, 'eval_overall_accuracy': 0.5769698077851036, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7005266674820492, 'eval_accuracy_RV': 0.44912736268930675, 'eval_accuracy_RA': 0.6096636349696964, 'eval_accuracy_LA': 0.6396380326429243, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.36549148383371827, 'eval_accuracy_VSD': 0.3228626263232075, 'eval_accuracy_AK': 0.46244189368166827, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6719437851325039, 'eval_iou_RV': 0.4376492686304449, 'eval_iou_RA': 0.551829992074478, 'eval_iou_LA': 0.5831116948503257, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3131662144717823, 'eval_iou_VSD': 0.29777906848102664, 'eval_iou_AK': 0.44734387806049875, 'eval_runtime': 4.4467, 'eval_samples_per_second': 18.216, 'eval_steps_per_second': 9.22, 'epoch': 9.12}\n",
+      "{'loss': 0.1597, 'learning_rate': 6.347500000000001e-05, 'epoch': 9.13}\n",
+      "{'loss': 0.4385, 'learning_rate': 6.345e-05, 'epoch': 9.14}\n",
+      "{'loss': 0.1057, 'learning_rate': 6.3425e-05, 'epoch': 9.14}\n",
+      "{'loss': 0.0852, 'learning_rate': 6.340000000000001e-05, 'epoch': 9.15}\n",
+      "{'loss': 0.094, 'learning_rate': 6.337500000000001e-05, 'epoch': 9.16}\n",
+      "{'loss': 0.1217, 'learning_rate': 6.335e-05, 'epoch': 9.16}\n",
+      "{'loss': 0.3075, 'learning_rate': 6.3325e-05, 'epoch': 9.17}\n",
+      "{'loss': 0.1492, 'learning_rate': 6.330000000000001e-05, 'epoch': 9.18}\n",
+      "{'loss': 0.2664, 'learning_rate': 6.3275e-05, 'epoch': 9.18}\n",
+      "{'loss': 0.1216, 'learning_rate': 6.324999999999999e-05, 'epoch': 9.19}\n",
+      "{'loss': 0.1345, 'learning_rate': 6.3225e-05, 'epoch': 9.19}\n",
+      "{'loss': 0.1423, 'learning_rate': 6.32e-05, 'epoch': 9.2}\n",
+      "{'loss': 0.0561, 'learning_rate': 6.3175e-05, 'epoch': 9.21}\n",
+      "{'loss': 0.278, 'learning_rate': 6.315e-05, 'epoch': 9.21}\n",
+      "{'loss': 0.1012, 'learning_rate': 6.3125e-05, 'epoch': 9.22}\n",
+      "{'loss': 0.187, 'learning_rate': 6.31e-05, 'epoch': 9.22}\n",
+      "{'loss': 0.1931, 'learning_rate': 6.3075e-05, 'epoch': 9.23}\n",
+      "{'loss': 0.0904, 'learning_rate': 6.305e-05, 'epoch': 9.24}\n",
+      "{'loss': 0.1419, 'learning_rate': 6.3025e-05, 'epoch': 9.24}\n",
+      "{'loss': 0.071, 'learning_rate': 6.3e-05, 'epoch': 9.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0db7e554e8d34cfbaaccb5e1304cc193",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.35430482029914856, 'eval_mean_iou': 0.2918067038240984, 'eval_mean_accuracy': 0.3400506418761699, 'eval_overall_accuracy': 0.560677361140263, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6806539566435277, 'eval_accuracy_RV': 0.47357686145232875, 'eval_accuracy_RA': 0.502185000766667, 'eval_accuracy_LA': 0.6572424344294349, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.00018040121229614663, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.30862983545034645, 'eval_accuracy_VSD': 0.3112948691036675, 'eval_accuracy_AK': 0.46674305970343055, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6629254697499823, 'eval_iou_RV': 0.4603050531418982, 'eval_iou_RA': 0.48237336945673426, 'eval_iou_LA': 0.6072394088545051, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.00017934967806732788, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.27518057946300734, 'eval_iou_VSD': 0.28597501342993703, 'eval_iou_AK': 0.4356954982909505, 'eval_runtime': 4.7869, 'eval_samples_per_second': 16.921, 'eval_steps_per_second': 8.565, 'epoch': 9.25}\n",
+      "{'loss': 0.2153, 'learning_rate': 6.297500000000001e-05, 'epoch': 9.26}\n",
+      "{'loss': 0.2567, 'learning_rate': 6.295e-05, 'epoch': 9.26}\n",
+      "{'loss': 0.0957, 'learning_rate': 6.2925e-05, 'epoch': 9.27}\n",
+      "{'loss': 0.2714, 'learning_rate': 6.29e-05, 'epoch': 9.28}\n",
+      "{'loss': 0.2481, 'learning_rate': 6.287500000000001e-05, 'epoch': 9.28}\n",
+      "{'loss': 0.1923, 'learning_rate': 6.285e-05, 'epoch': 9.29}\n",
+      "{'loss': 0.1794, 'learning_rate': 6.2825e-05, 'epoch': 9.29}\n",
+      "{'loss': 0.1568, 'learning_rate': 6.280000000000001e-05, 'epoch': 9.3}\n",
+      "{'loss': 0.3887, 'learning_rate': 6.277500000000001e-05, 'epoch': 9.31}\n",
+      "{'loss': 0.1102, 'learning_rate': 6.275e-05, 'epoch': 9.31}\n",
+      "{'loss': 0.0954, 'learning_rate': 6.2725e-05, 'epoch': 9.32}\n",
+      "{'loss': 0.198, 'learning_rate': 6.27e-05, 'epoch': 9.32}\n",
+      "{'loss': 0.1203, 'learning_rate': 6.2675e-05, 'epoch': 9.33}\n",
+      "{'loss': 0.2377, 'learning_rate': 6.264999999999999e-05, 'epoch': 9.34}\n",
+      "{'loss': 0.0972, 'learning_rate': 6.2625e-05, 'epoch': 9.34}\n",
+      "{'loss': 0.1567, 'learning_rate': 6.26e-05, 'epoch': 9.35}\n",
+      "{'loss': 0.2056, 'learning_rate': 6.2575e-05, 'epoch': 9.36}\n",
+      "{'loss': 0.1081, 'learning_rate': 6.255e-05, 'epoch': 9.36}\n",
+      "{'loss': 0.172, 'learning_rate': 6.2525e-05, 'epoch': 9.37}\n",
+      "{'loss': 0.5247, 'learning_rate': 6.25e-05, 'epoch': 9.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "5ae621844fc34fa3b5b0a6ffb7eeb5f1",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.34273090958595276, 'eval_mean_iou': 0.31552314644147716, 'eval_mean_accuracy': 0.371065586619059, 'eval_overall_accuracy': 0.6093304720008482, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7370279606587893, 'eval_accuracy_RV': 0.4837121002842287, 'eval_accuracy_RA': 0.588368452059106, 'eval_accuracy_LA': 0.7127861744386281, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0007216048491845865, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.30835919457274824, 'eval_accuracy_VSD': 0.36128437340690317, 'eval_accuracy_AK': 0.5183960059210013, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7057259643605421, 'eval_iou_RV': 0.4671763622969506, 'eval_iou_RA': 0.5519393753572335, 'eval_iou_LA': 0.643586666150451, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.000718920181886806, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.27930902048587564, 'eval_iou_VSD': 0.33029931254754935, 'eval_iou_AK': 0.49199898947575976, 'eval_runtime': 4.8247, 'eval_samples_per_second': 16.788, 'eval_steps_per_second': 8.498, 'epoch': 9.38}\n",
+      "{'loss': 0.1585, 'learning_rate': 6.2475e-05, 'epoch': 9.38}\n",
+      "{'loss': 0.2087, 'learning_rate': 6.245000000000001e-05, 'epoch': 9.39}\n",
+      "{'loss': 0.1825, 'learning_rate': 6.2425e-05, 'epoch': 9.39}\n",
+      "{'loss': 0.1076, 'learning_rate': 6.24e-05, 'epoch': 9.4}\n",
+      "{'loss': 0.1367, 'learning_rate': 6.237500000000001e-05, 'epoch': 9.41}\n",
+      "{'loss': 0.2054, 'learning_rate': 6.235000000000001e-05, 'epoch': 9.41}\n",
+      "{'loss': 0.3293, 'learning_rate': 6.2325e-05, 'epoch': 9.42}\n",
+      "{'loss': 0.1282, 'learning_rate': 6.23e-05, 'epoch': 9.43}\n",
+      "{'loss': 0.197, 'learning_rate': 6.227500000000001e-05, 'epoch': 9.43}\n",
+      "{'loss': 0.1615, 'learning_rate': 6.225000000000001e-05, 'epoch': 9.44}\n",
+      "{'loss': 0.1836, 'learning_rate': 6.2225e-05, 'epoch': 9.44}\n",
+      "{'loss': 0.3961, 'learning_rate': 6.220000000000001e-05, 'epoch': 9.45}\n",
+      "{'loss': 0.0398, 'learning_rate': 6.217500000000001e-05, 'epoch': 9.46}\n",
+      "{'loss': 0.4047, 'learning_rate': 6.215e-05, 'epoch': 9.46}\n",
+      "{'loss': 0.356, 'learning_rate': 6.2125e-05, 'epoch': 9.47}\n",
+      "{'loss': 0.1601, 'learning_rate': 6.21e-05, 'epoch': 9.47}\n",
+      "{'loss': 0.2456, 'learning_rate': 6.2075e-05, 'epoch': 9.48}\n",
+      "{'loss': 0.2322, 'learning_rate': 6.205e-05, 'epoch': 9.49}\n",
+      "{'loss': 0.2602, 'learning_rate': 6.2025e-05, 'epoch': 9.49}\n",
+      "{'loss': 0.2141, 'learning_rate': 6.2e-05, 'epoch': 9.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "cdf7b0d0ce0945ed856b63708c65824d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.33262449502944946, 'eval_mean_iou': 0.334271923860598, 'eval_mean_accuracy': 0.3963366790195244, 'eval_overall_accuracy': 0.6458086744464328, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.8073897518353563, 'eval_accuracy_RV': 0.48922478621460186, 'eval_accuracy_RA': 0.623007674739535, 'eval_accuracy_LA': 0.7126335252025604, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.00016236109106653197, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.39313293879907624, 'eval_accuracy_VSD': 0.40382193300746694, 'eval_accuracy_AK': 0.5339938193055808, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7631903224442032, 'eval_iou_RV': 0.473433919334166, 'eval_iou_RA': 0.5715293098597806, 'eval_iou_LA': 0.6466383415818471, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.00016230545887360013, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3451176051318603, 'eval_iou_VSD': 0.36394532543259256, 'eval_iou_AK': 0.5129740332232544, 'eval_runtime': 4.5862, 'eval_samples_per_second': 17.662, 'eval_steps_per_second': 8.94, 'epoch': 9.5}\n",
+      "{'loss': 0.1794, 'learning_rate': 6.1975e-05, 'epoch': 9.51}\n",
+      "{'loss': 0.1494, 'learning_rate': 6.195e-05, 'epoch': 9.51}\n",
+      "{'loss': 0.4168, 'learning_rate': 6.1925e-05, 'epoch': 9.52}\n",
+      "{'loss': 0.1127, 'learning_rate': 6.19e-05, 'epoch': 9.53}\n",
+      "{'loss': 0.1323, 'learning_rate': 6.1875e-05, 'epoch': 9.53}\n",
+      "{'loss': 0.0253, 'learning_rate': 6.185000000000001e-05, 'epoch': 9.54}\n",
+      "{'loss': 0.371, 'learning_rate': 6.1825e-05, 'epoch': 9.54}\n",
+      "{'loss': 0.3188, 'learning_rate': 6.18e-05, 'epoch': 9.55}\n",
+      "{'loss': 0.137, 'learning_rate': 6.177500000000001e-05, 'epoch': 9.56}\n",
+      "{'loss': 0.2613, 'learning_rate': 6.175000000000001e-05, 'epoch': 9.56}\n",
+      "{'loss': 0.3455, 'learning_rate': 6.1725e-05, 'epoch': 9.57}\n",
+      "{'loss': 0.1732, 'learning_rate': 6.170000000000001e-05, 'epoch': 9.57}\n",
+      "{'loss': 0.1874, 'learning_rate': 6.167500000000001e-05, 'epoch': 9.58}\n",
+      "{'loss': 0.1928, 'learning_rate': 6.165000000000001e-05, 'epoch': 9.59}\n",
+      "{'loss': 0.2675, 'learning_rate': 6.1625e-05, 'epoch': 9.59}\n",
+      "{'loss': 0.1584, 'learning_rate': 6.16e-05, 'epoch': 9.6}\n",
+      "{'loss': 0.4152, 'learning_rate': 6.1575e-05, 'epoch': 9.61}\n",
+      "{'loss': 0.2775, 'learning_rate': 6.155e-05, 'epoch': 9.61}\n",
+      "{'loss': 0.248, 'learning_rate': 6.1525e-05, 'epoch': 9.62}\n",
+      "{'loss': 0.2131, 'learning_rate': 6.15e-05, 'epoch': 9.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
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+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.2102, 'learning_rate': 6.1475e-05, 'epoch': 9.63}\n",
+      "{'loss': 0.1369, 'learning_rate': 6.145e-05, 'epoch': 9.64}\n",
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+      "{'loss': 0.1261, 'learning_rate': 6.1275e-05, 'epoch': 9.68}\n",
+      "{'loss': 0.1686, 'learning_rate': 6.125000000000001e-05, 'epoch': 9.69}\n",
+      "{'loss': 0.273, 'learning_rate': 6.1225e-05, 'epoch': 9.69}\n",
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+      "{'loss': 0.2011, 'learning_rate': 6.115000000000001e-05, 'epoch': 9.71}\n",
+      "{'loss': 0.102, 'learning_rate': 6.1125e-05, 'epoch': 9.72}\n",
+      "{'loss': 0.5268, 'learning_rate': 6.110000000000001e-05, 'epoch': 9.72}\n",
+      "{'loss': 0.0794, 'learning_rate': 6.107500000000001e-05, 'epoch': 9.73}\n",
+      "{'loss': 0.2398, 'learning_rate': 6.105e-05, 'epoch': 9.74}\n",
+      "{'loss': 0.2183, 'learning_rate': 6.1025e-05, 'epoch': 9.74}\n",
+      "{'loss': 0.1051, 'learning_rate': 6.1e-05, 'epoch': 9.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2a93cbc3b4754933891704b7053cebe5",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3312787115573883, 'eval_mean_iou': 0.30672735963816966, 'eval_mean_accuracy': 0.3634176604903695, 'eval_overall_accuracy': 0.5750407344976295, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6832835651704398, 'eval_accuracy_RV': 0.47075452586603805, 'eval_accuracy_RA': 0.5645937068749849, 'eval_accuracy_LA': 0.6606967665804513, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 7.216048491845865e-05, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4264578521939954, 'eval_accuracy_VSD': 0.3689762197499025, 'eval_accuracy_AK': 0.45934180798296415, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6551328887144163, 'eval_iou_RV': 0.45586449705812854, 'eval_iou_RA': 0.5274653608297944, 'eval_iou_LA': 0.6111514797668419, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 7.214746942750983e-05, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3548096553380569, 'eval_iou_VSD': 0.334718443960827, 'eval_iou_AK': 0.43478648288237354, 'eval_runtime': 4.5731, 'eval_samples_per_second': 17.712, 'eval_steps_per_second': 8.966, 'epoch': 9.75}\n",
+      "{'loss': 0.2603, 'learning_rate': 6.0975000000000005e-05, 'epoch': 9.76}\n",
+      "{'loss': 0.1477, 'learning_rate': 6.0950000000000004e-05, 'epoch': 9.76}\n",
+      "{'loss': 0.2209, 'learning_rate': 6.0925e-05, 'epoch': 9.77}\n",
+      "{'loss': 0.0857, 'learning_rate': 6.09e-05, 'epoch': 9.78}\n",
+      "{'loss': 0.2183, 'learning_rate': 6.0875e-05, 'epoch': 9.78}\n",
+      "{'loss': 0.1712, 'learning_rate': 6.085000000000001e-05, 'epoch': 9.79}\n",
+      "{'loss': 0.3639, 'learning_rate': 6.0825e-05, 'epoch': 9.79}\n",
+      "{'loss': 0.5077, 'learning_rate': 6.08e-05, 'epoch': 9.8}\n",
+      "{'loss': 0.065, 'learning_rate': 6.077500000000001e-05, 'epoch': 9.81}\n",
+      "{'loss': 0.2395, 'learning_rate': 6.0750000000000006e-05, 'epoch': 9.81}\n",
+      "{'loss': 0.1837, 'learning_rate': 6.0725e-05, 'epoch': 9.82}\n",
+      "{'loss': 0.3095, 'learning_rate': 6.07e-05, 'epoch': 9.82}\n",
+      "{'loss': 0.1254, 'learning_rate': 6.0675000000000004e-05, 'epoch': 9.83}\n",
+      "{'loss': 0.172, 'learning_rate': 6.0650000000000004e-05, 'epoch': 9.84}\n",
+      "{'loss': 0.1209, 'learning_rate': 6.0624999999999996e-05, 'epoch': 9.84}\n",
+      "{'loss': 0.2755, 'learning_rate': 6.06e-05, 'epoch': 9.85}\n",
+      "{'loss': 0.1427, 'learning_rate': 6.0575e-05, 'epoch': 9.86}\n",
+      "{'loss': 0.205, 'learning_rate': 6.055000000000001e-05, 'epoch': 9.86}\n",
+      "{'loss': 0.1687, 'learning_rate': 6.0525e-05, 'epoch': 9.87}\n",
+      "{'loss': 0.2696, 'learning_rate': 6.05e-05, 'epoch': 9.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6e8579c9e84f49b085a47811481070fb",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3364693522453308, 'eval_mean_iou': 0.30904182106010797, 'eval_mean_accuracy': 0.36659195475493206, 'eval_overall_accuracy': 0.6015008471477197, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7938800075174288, 'eval_accuracy_RV': 0.44214595726133693, 'eval_accuracy_RA': 0.5737795872910832, 'eval_accuracy_LA': 0.5900098793213455, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4373105513856813, 'eval_accuracy_VSD': 0.3490268989714217, 'eval_accuracy_AK': 0.4797666658010232, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7515799402831643, 'eval_iou_RV': 0.4313927197041163, 'eval_iou_RA': 0.5189273124055733, 'eval_iou_LA': 0.5511747816111108, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3633426776800036, 'eval_iou_VSD': 0.32146161600817535, 'eval_iou_AK': 0.4615809839690437, 'eval_runtime': 4.5984, 'eval_samples_per_second': 17.615, 'eval_steps_per_second': 8.916, 'epoch': 9.88}\n",
+      "{'loss': 0.7127, 'learning_rate': 6.0475000000000006e-05, 'epoch': 9.88}\n",
+      "{'loss': 0.1751, 'learning_rate': 6.0450000000000006e-05, 'epoch': 9.89}\n",
+      "{'loss': 0.2152, 'learning_rate': 6.0425e-05, 'epoch': 9.89}\n",
+      "{'loss': 0.1479, 'learning_rate': 6.04e-05, 'epoch': 9.9}\n",
+      "{'loss': 0.0704, 'learning_rate': 6.0375000000000004e-05, 'epoch': 9.91}\n",
+      "{'loss': 0.3035, 'learning_rate': 6.035e-05, 'epoch': 9.91}\n",
+      "{'loss': 0.4082, 'learning_rate': 6.0324999999999996e-05, 'epoch': 9.92}\n",
+      "{'loss': 0.3909, 'learning_rate': 6.03e-05, 'epoch': 9.93}\n",
+      "{'loss': 0.4115, 'learning_rate': 6.0275e-05, 'epoch': 9.93}\n",
+      "{'loss': 0.145, 'learning_rate': 6.025000000000001e-05, 'epoch': 9.94}\n",
+      "{'loss': 0.3705, 'learning_rate': 6.0225e-05, 'epoch': 9.94}\n",
+      "{'loss': 0.1449, 'learning_rate': 6.02e-05, 'epoch': 9.95}\n",
+      "{'loss': 0.273, 'learning_rate': 6.0175000000000006e-05, 'epoch': 9.96}\n",
+      "{'loss': 0.0434, 'learning_rate': 6.0150000000000005e-05, 'epoch': 9.96}\n",
+      "{'loss': 0.419, 'learning_rate': 6.0125e-05, 'epoch': 9.97}\n",
+      "{'loss': 0.2089, 'learning_rate': 6.0100000000000004e-05, 'epoch': 9.97}\n",
+      "{'loss': 0.2047, 'learning_rate': 6.0075e-05, 'epoch': 9.98}\n",
+      "{'loss': 0.1807, 'learning_rate': 6.005000000000001e-05, 'epoch': 9.99}\n",
+      "{'loss': 0.223, 'learning_rate': 6.0024999999999995e-05, 'epoch': 9.99}\n",
+      "{'loss': 0.2296, 'learning_rate': 6e-05, 'epoch': 10.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9189eff507214fbe864487e842fd1a5e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.34323519468307495, 'eval_mean_iou': 0.3175110755165862, 'eval_mean_accuracy': 0.38181808327090333, 'eval_overall_accuracy': 0.6085287651550724, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7595123813842212, 'eval_accuracy_RV': 0.5088184558340546, 'eval_accuracy_RA': 0.6520441761558513, 'eval_accuracy_LA': 0.5604834006819476, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.008785539038822341, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4505809757505774, 'eval_accuracy_VSD': 0.4066032926500135, 'eval_accuracy_AK': 0.4713526112135456, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7221726631560884, 'eval_iou_RV': 0.48712900382015867, 'eval_iou_RA': 0.5561345032359313, 'eval_iou_LA': 0.5249636537426605, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.00875489878833639, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3660039717725684, 'eval_iou_VSD': 0.37063156887667936, 'eval_iou_AK': 0.45683156729002544, 'eval_runtime': 4.4542, 'eval_samples_per_second': 18.185, 'eval_steps_per_second': 9.205, 'epoch': 10.0}\n",
+      "{'loss': 0.194, 'learning_rate': 5.9975e-05, 'epoch': 10.01}\n",
+      "{'loss': 0.2172, 'learning_rate': 5.995000000000001e-05, 'epoch': 10.01}\n",
+      "{'loss': 0.4991, 'learning_rate': 5.9925e-05, 'epoch': 10.02}\n",
+      "{'loss': 0.1397, 'learning_rate': 5.99e-05, 'epoch': 10.03}\n",
+      "{'loss': 0.2753, 'learning_rate': 5.9875000000000005e-05, 'epoch': 10.03}\n",
+      "{'loss': 0.0871, 'learning_rate': 5.9850000000000005e-05, 'epoch': 10.04}\n",
+      "{'loss': 0.224, 'learning_rate': 5.9825e-05, 'epoch': 10.04}\n",
+      "{'loss': 0.4427, 'learning_rate': 5.9800000000000003e-05, 'epoch': 10.05}\n",
+      "{'loss': 0.2405, 'learning_rate': 5.9775e-05, 'epoch': 10.06}\n",
+      "{'loss': 0.2675, 'learning_rate': 5.975000000000001e-05, 'epoch': 10.06}\n",
+      "{'loss': 0.0898, 'learning_rate': 5.9724999999999995e-05, 'epoch': 10.07}\n",
+      "{'loss': 0.0156, 'learning_rate': 5.97e-05, 'epoch': 10.07}\n",
+      "{'loss': 0.2461, 'learning_rate': 5.9675e-05, 'epoch': 10.08}\n",
+      "{'loss': 0.1844, 'learning_rate': 5.9650000000000007e-05, 'epoch': 10.09}\n",
+      "{'loss': 0.0959, 'learning_rate': 5.9625e-05, 'epoch': 10.09}\n",
+      "{'loss': 0.1757, 'learning_rate': 5.96e-05, 'epoch': 10.1}\n",
+      "{'loss': 0.1436, 'learning_rate': 5.9575000000000005e-05, 'epoch': 10.11}\n",
+      "{'loss': 0.26, 'learning_rate': 5.9550000000000004e-05, 'epoch': 10.11}\n",
+      "{'loss': 0.0819, 'learning_rate': 5.9525e-05, 'epoch': 10.12}\n",
+      "{'loss': 0.2348, 'learning_rate': 5.95e-05, 'epoch': 10.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f7f9045eb9fe473eb03a341fa5ce2f15",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3716123402118683, 'eval_mean_iou': 0.26695823189612294, 'eval_mean_accuracy': 0.30946311483291555, 'eval_overall_accuracy': 0.5191876794644036, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6638366928086248, 'eval_accuracy_RV': 0.3500785772604775, 'eval_accuracy_RA': 0.5569088796171507, 'eval_accuracy_LA': 0.5832813068146735, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.003535863761004474, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.2721113596997691, 'eval_accuracy_VSD': 0.28640507391969294, 'eval_accuracy_AK': 0.37847339444776273, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6431686167287946, 'eval_iou_RV': 0.3446308136724038, 'eval_iou_RA': 0.5194937423543804, 'eval_iou_LA': 0.5482862527791258, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.003527908274384866, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2451658525087173, 'eval_iou_VSD': 0.2665536344734235, 'eval_iou_AK': 0.3657137300661221, 'eval_runtime': 4.3463, 'eval_samples_per_second': 18.636, 'eval_steps_per_second': 9.433, 'epoch': 10.12}\n",
+      "{'loss': 0.0679, 'learning_rate': 5.9475e-05, 'epoch': 10.13}\n",
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+      "{'loss': 0.5863, 'learning_rate': 5.9325000000000005e-05, 'epoch': 10.17}\n",
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+      "{'loss': 0.236, 'learning_rate': 5.9275000000000004e-05, 'epoch': 10.18}\n",
+      "{'loss': 0.1603, 'learning_rate': 5.9250000000000004e-05, 'epoch': 10.19}\n",
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+      "{'loss': 0.2546, 'learning_rate': 5.9175e-05, 'epoch': 10.21}\n",
+      "{'loss': 0.2435, 'learning_rate': 5.915000000000001e-05, 'epoch': 10.21}\n",
+      "{'loss': 0.2412, 'learning_rate': 5.912500000000001e-05, 'epoch': 10.22}\n",
+      "{'loss': 0.1376, 'learning_rate': 5.91e-05, 'epoch': 10.22}\n",
+      "{'loss': 0.1475, 'learning_rate': 5.9075e-05, 'epoch': 10.23}\n",
+      "{'loss': 0.3314, 'learning_rate': 5.9050000000000006e-05, 'epoch': 10.24}\n",
+      "{'loss': 0.1473, 'learning_rate': 5.9025000000000005e-05, 'epoch': 10.24}\n",
+      "{'loss': 0.2329, 'learning_rate': 5.9e-05, 'epoch': 10.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "33357c766d0a4467a0e516da02c7483f",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3412233889102936, 'eval_mean_iou': 0.32809173825661553, 'eval_mean_accuracy': 0.3922484771662282, 'eval_overall_accuracy': 0.6359336693072863, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.795403629247571, 'eval_accuracy_RV': 0.5027793636469671, 'eval_accuracy_RA': 0.584333362923987, 'eval_accuracy_LA': 0.6668473301820128, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.002417376244768365, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.42922741050808316, 'eval_accuracy_VSD': 0.3388910546675863, 'eval_accuracy_AK': 0.6025852442413068, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7456222280636015, 'eval_iou_RV': 0.485846020602167, 'eval_iou_RA': 0.5339446598344109, 'eval_iou_LA': 0.613689133581358, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.002403415001614234, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3606108837350311, 'eval_iou_VSD': 0.31303625220733355, 'eval_iou_AK': 0.5538565277972545, 'eval_runtime': 4.3725, 'eval_samples_per_second': 18.525, 'eval_steps_per_second': 9.377, 'epoch': 10.25}\n",
+      "{'loss': 0.2551, 'learning_rate': 5.8975000000000004e-05, 'epoch': 10.26}\n",
+      "{'loss': 0.0986, 'learning_rate': 5.895e-05, 'epoch': 10.26}\n",
+      "{'loss': 0.0493, 'learning_rate': 5.892500000000001e-05, 'epoch': 10.27}\n",
+      "{'loss': 0.2406, 'learning_rate': 5.89e-05, 'epoch': 10.28}\n",
+      "{'loss': 0.1571, 'learning_rate': 5.8875e-05, 'epoch': 10.28}\n",
+      "{'loss': 0.1863, 'learning_rate': 5.885000000000001e-05, 'epoch': 10.29}\n",
+      "{'loss': 0.0891, 'learning_rate': 5.882500000000001e-05, 'epoch': 10.29}\n",
+      "{'loss': 0.2278, 'learning_rate': 5.88e-05, 'epoch': 10.3}\n",
+      "{'loss': 0.1708, 'learning_rate': 5.8775000000000006e-05, 'epoch': 10.31}\n",
+      "{'loss': 0.1249, 'learning_rate': 5.8750000000000005e-05, 'epoch': 10.31}\n",
+      "{'loss': 0.131, 'learning_rate': 5.8725000000000004e-05, 'epoch': 10.32}\n",
+      "{'loss': 0.1373, 'learning_rate': 5.87e-05, 'epoch': 10.32}\n",
+      "{'loss': 0.189, 'learning_rate': 5.8675e-05, 'epoch': 10.33}\n",
+      "{'loss': 0.1887, 'learning_rate': 5.865e-05, 'epoch': 10.34}\n",
+      "{'loss': 0.2273, 'learning_rate': 5.862500000000001e-05, 'epoch': 10.34}\n",
+      "{'loss': 0.1718, 'learning_rate': 5.86e-05, 'epoch': 10.35}\n",
+      "{'loss': 0.239, 'learning_rate': 5.8575e-05, 'epoch': 10.36}\n",
+      "{'loss': 0.2634, 'learning_rate': 5.855000000000001e-05, 'epoch': 10.36}\n",
+      "{'loss': 0.185, 'learning_rate': 5.8525000000000006e-05, 'epoch': 10.37}\n",
+      "{'loss': 0.0739, 'learning_rate': 5.85e-05, 'epoch': 10.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0a129d6cbad742c3ac3a3eb28868a669",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3347601592540741, 'eval_mean_iou': 0.3448877812933517, 'eval_mean_accuracy': 0.414006967816045, 'eval_overall_accuracy': 0.646828930256914, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7414340092058672, 'eval_accuracy_RV': 0.5228856271140659, 'eval_accuracy_RA': 0.6984779643782331, 'eval_accuracy_LA': 0.7387211081305443, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0005051233944292105, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.44349920612009236, 'eval_accuracy_VSD': 0.43483671694605214, 'eval_accuracy_AK': 0.5597099228711663, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7095673908342214, 'eval_iou_RV': 0.5043476458763237, 'eval_iou_RA': 0.6236974850472004, 'eval_iou_LA': 0.6589481027938294, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.000504759157773291, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3827277752259652, 'eval_iou_VSD': 0.3908569580247579, 'eval_iou_AK': 0.5231154772667973, 'eval_runtime': 4.3765, 'eval_samples_per_second': 18.508, 'eval_steps_per_second': 9.368, 'epoch': 10.38}\n",
+      "{'loss': 0.0888, 'learning_rate': 5.8475000000000005e-05, 'epoch': 10.38}\n",
+      "{'loss': 0.2656, 'learning_rate': 5.8450000000000005e-05, 'epoch': 10.39}\n",
+      "{'loss': 0.1596, 'learning_rate': 5.842500000000001e-05, 'epoch': 10.39}\n",
+      "{'loss': 0.19, 'learning_rate': 5.8399999999999997e-05, 'epoch': 10.4}\n",
+      "{'loss': 0.1054, 'learning_rate': 5.8375e-05, 'epoch': 10.41}\n",
+      "{'loss': 0.1277, 'learning_rate': 5.835e-05, 'epoch': 10.41}\n",
+      "{'loss': 0.1271, 'learning_rate': 5.832500000000001e-05, 'epoch': 10.42}\n",
+      "{'loss': 0.2422, 'learning_rate': 5.83e-05, 'epoch': 10.43}\n",
+      "{'loss': 0.4286, 'learning_rate': 5.8275e-05, 'epoch': 10.43}\n",
+      "{'loss': 0.187, 'learning_rate': 5.8250000000000006e-05, 'epoch': 10.44}\n",
+      "{'loss': 0.1684, 'learning_rate': 5.8225000000000006e-05, 'epoch': 10.44}\n",
+      "{'loss': 0.0783, 'learning_rate': 5.82e-05, 'epoch': 10.45}\n",
+      "{'loss': 0.219, 'learning_rate': 5.8175000000000005e-05, 'epoch': 10.46}\n",
+      "{'loss': 0.2577, 'learning_rate': 5.8150000000000004e-05, 'epoch': 10.46}\n",
+      "{'loss': 0.1225, 'learning_rate': 5.812500000000001e-05, 'epoch': 10.47}\n",
+      "{'loss': 0.24, 'learning_rate': 5.8099999999999996e-05, 'epoch': 10.47}\n",
+      "{'loss': 0.2087, 'learning_rate': 5.8075e-05, 'epoch': 10.48}\n",
+      "{'loss': 0.2244, 'learning_rate': 5.805e-05, 'epoch': 10.49}\n",
+      "{'loss': 0.2739, 'learning_rate': 5.802500000000001e-05, 'epoch': 10.49}\n",
+      "{'loss': 0.0708, 'learning_rate': 5.8e-05, 'epoch': 10.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d643ad61cb984ec684f0cbd486120562",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.341886967420578, 'eval_mean_iou': 0.358892833568137, 'eval_mean_accuracy': 0.43266900244155676, 'eval_overall_accuracy': 0.6912638838098494, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.8501801796426834, 'eval_accuracy_RV': 0.5736784593945867, 'eval_accuracy_RA': 0.6637822504499125, 'eval_accuracy_LA': 0.7165852537407639, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.005736758551017463, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.45964744515011546, 'eval_accuracy_VSD': 0.46845293429693824, 'eval_accuracy_AK': 0.58862674318955, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7797644412919271, 'eval_iou_RV': 0.5516477029559776, 'eval_iou_RA': 0.5995524381732334, 'eval_iou_LA': 0.6506331991976777, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.005684357292243891, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3882513411363082, 'eval_iou_VSD': 0.41030119572140544, 'eval_iou_AK': 0.5619864934807335, 'eval_runtime': 4.6043, 'eval_samples_per_second': 17.592, 'eval_steps_per_second': 8.905, 'epoch': 10.5}\n",
+      "{'loss': 0.16, 'learning_rate': 5.7975e-05, 'epoch': 10.51}\n",
+      "{'loss': 0.1646, 'learning_rate': 5.7950000000000006e-05, 'epoch': 10.51}\n",
+      "{'loss': 0.1207, 'learning_rate': 5.7925000000000005e-05, 'epoch': 10.52}\n",
+      "{'loss': 0.0984, 'learning_rate': 5.79e-05, 'epoch': 10.53}\n",
+      "{'loss': 0.2687, 'learning_rate': 5.7875000000000004e-05, 'epoch': 10.53}\n",
+      "{'loss': 0.1963, 'learning_rate': 5.7850000000000003e-05, 'epoch': 10.54}\n",
+      "{'loss': 0.2187, 'learning_rate': 5.782500000000001e-05, 'epoch': 10.54}\n",
+      "{'loss': 0.1038, 'learning_rate': 5.7799999999999995e-05, 'epoch': 10.55}\n",
+      "{'loss': 0.2301, 'learning_rate': 5.7775e-05, 'epoch': 10.56}\n",
+      "{'loss': 0.2105, 'learning_rate': 5.775e-05, 'epoch': 10.56}\n",
+      "{'loss': 0.171, 'learning_rate': 5.772500000000001e-05, 'epoch': 10.57}\n",
+      "{'loss': 0.2141, 'learning_rate': 5.77e-05, 'epoch': 10.57}\n",
+      "{'loss': 0.2735, 'learning_rate': 5.7675e-05, 'epoch': 10.58}\n",
+      "{'loss': 0.1335, 'learning_rate': 5.7650000000000005e-05, 'epoch': 10.59}\n",
+      "{'loss': 0.0934, 'learning_rate': 5.7625000000000005e-05, 'epoch': 10.59}\n",
+      "{'loss': 0.2328, 'learning_rate': 5.76e-05, 'epoch': 10.6}\n",
+      "{'loss': 0.2077, 'learning_rate': 5.7575000000000004e-05, 'epoch': 10.61}\n",
+      "{'loss': 0.1867, 'learning_rate': 5.755e-05, 'epoch': 10.61}\n",
+      "{'loss': 0.1932, 'learning_rate': 5.752500000000001e-05, 'epoch': 10.62}\n",
+      "{'loss': 0.1248, 'learning_rate': 5.7499999999999995e-05, 'epoch': 10.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "72a15545738d4b04b2ea21a79fb058e3",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3356002867221832, 'eval_mean_iou': 0.3318604605195785, 'eval_mean_accuracy': 0.39454145435267485, 'eval_overall_accuracy': 0.6269528756499668, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7528160526935962, 'eval_accuracy_RV': 0.5260302522452839, 'eval_accuracy_RA': 0.5823602043369138, 'eval_accuracy_LA': 0.6864396023573158, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0005592437581180545, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4225786662817552, 'eval_accuracy_VSD': 0.40224757849281795, 'eval_accuracy_AK': 0.5723829433609473, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7139091629183286, 'eval_iou_RV': 0.5096046625730386, 'eval_iou_RA': 0.5459456187867875, 'eval_iou_LA': 0.6308681986273514, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0005532849060308055, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3533805090755466, 'eval_iou_VSD': 0.3610699865410498, 'eval_iou_AK': 0.53513364228723, 'eval_runtime': 4.4687, 'eval_samples_per_second': 18.126, 'eval_steps_per_second': 9.175, 'epoch': 10.62}\n",
+      "{'loss': 0.4141, 'learning_rate': 5.7475e-05, 'epoch': 10.63}\n",
+      "{'loss': 0.2019, 'learning_rate': 5.745e-05, 'epoch': 10.64}\n",
+      "{'loss': 0.1119, 'learning_rate': 5.742500000000001e-05, 'epoch': 10.64}\n",
+      "{'loss': 0.1008, 'learning_rate': 5.74e-05, 'epoch': 10.65}\n",
+      "{'loss': 0.246, 'learning_rate': 5.7375e-05, 'epoch': 10.66}\n",
+      "{'loss': 0.2207, 'learning_rate': 5.7350000000000005e-05, 'epoch': 10.66}\n",
+      "{'loss': 0.2617, 'learning_rate': 5.7325000000000004e-05, 'epoch': 10.67}\n",
+      "{'loss': 0.0536, 'learning_rate': 5.73e-05, 'epoch': 10.68}\n",
+      "{'loss': 0.2222, 'learning_rate': 5.7275e-05, 'epoch': 10.68}\n",
+      "{'loss': 0.1495, 'learning_rate': 5.725e-05, 'epoch': 10.69}\n",
+      "{'loss': 0.2192, 'learning_rate': 5.722500000000001e-05, 'epoch': 10.69}\n",
+      "{'loss': 0.0181, 'learning_rate': 5.72e-05, 'epoch': 10.7}\n",
+      "{'loss': 0.1246, 'learning_rate': 5.7175e-05, 'epoch': 10.71}\n",
+      "{'loss': 0.1982, 'learning_rate': 5.715000000000001e-05, 'epoch': 10.71}\n",
+      "{'loss': 0.2142, 'learning_rate': 5.7125000000000006e-05, 'epoch': 10.72}\n",
+      "{'loss': 0.1888, 'learning_rate': 5.71e-05, 'epoch': 10.72}\n",
+      "{'loss': 0.2634, 'learning_rate': 5.7075e-05, 'epoch': 10.73}\n",
+      "{'loss': 0.095, 'learning_rate': 5.7050000000000004e-05, 'epoch': 10.74}\n",
+      "{'loss': 0.1218, 'learning_rate': 5.7025000000000004e-05, 'epoch': 10.74}\n",
+      "{'loss': 0.1589, 'learning_rate': 5.6999999999999996e-05, 'epoch': 10.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f77cd4a149524257b0f4848f6fd65e48",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3670651614665985, 'eval_mean_iou': 0.27531836730516457, 'eval_mean_accuracy': 0.3202531262289723, 'eval_overall_accuracy': 0.5079159084171645, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6035965825530023, 'eval_accuracy_RV': 0.4119735170076797, 'eval_accuracy_RA': 0.5403892246979736, 'eval_accuracy_LA': 0.5439938528667183, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 5.412036368884399e-05, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3179489030023095, 'eval_accuracy_VSD': 0.35450715206765226, 'eval_accuracy_AK': 0.4300679097306983, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.5867993651700505, 'eval_iou_RV': 0.4024210897152409, 'eval_iou_RA': 0.49946854137918173, 'eval_iou_LA': 0.5148998344102081, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 5.4111578073988564e-05, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2883770404614818, 'eval_iou_VSD': 0.32280900563876413, 'eval_iou_AK': 0.4136730520038093, 'eval_runtime': 4.474, 'eval_samples_per_second': 18.105, 'eval_steps_per_second': 9.164, 'epoch': 10.75}\n",
+      "{'loss': 0.1509, 'learning_rate': 5.6975e-05, 'epoch': 10.76}\n",
+      "{'loss': 0.0912, 'learning_rate': 5.695e-05, 'epoch': 10.76}\n",
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+      "{'loss': 0.1739, 'learning_rate': 5.69e-05, 'epoch': 10.78}\n",
+      "{'loss': 0.1756, 'learning_rate': 5.6875e-05, 'epoch': 10.78}\n",
+      "{'loss': 0.2649, 'learning_rate': 5.6850000000000006e-05, 'epoch': 10.79}\n",
+      "{'loss': 0.1581, 'learning_rate': 5.6825000000000006e-05, 'epoch': 10.79}\n",
+      "{'loss': 0.1789, 'learning_rate': 5.68e-05, 'epoch': 10.8}\n",
+      "{'loss': 0.2016, 'learning_rate': 5.6775e-05, 'epoch': 10.81}\n",
+      "{'loss': 0.156, 'learning_rate': 5.6750000000000004e-05, 'epoch': 10.81}\n",
+      "{'loss': 0.1258, 'learning_rate': 5.6725e-05, 'epoch': 10.82}\n",
+      "{'loss': 0.2779, 'learning_rate': 5.6699999999999996e-05, 'epoch': 10.82}\n",
+      "{'loss': 0.1086, 'learning_rate': 5.6675e-05, 'epoch': 10.83}\n",
+      "{'loss': 0.1314, 'learning_rate': 5.665e-05, 'epoch': 10.84}\n",
+      "{'loss': 0.2367, 'learning_rate': 5.662500000000001e-05, 'epoch': 10.84}\n",
+      "{'loss': 0.2058, 'learning_rate': 5.66e-05, 'epoch': 10.85}\n",
+      "{'loss': 0.0358, 'learning_rate': 5.6575e-05, 'epoch': 10.86}\n",
+      "{'loss': 0.1415, 'learning_rate': 5.6550000000000006e-05, 'epoch': 10.86}\n",
+      "{'loss': 0.2701, 'learning_rate': 5.6525000000000005e-05, 'epoch': 10.87}\n",
+      "{'loss': 0.1421, 'learning_rate': 5.65e-05, 'epoch': 10.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1a696fd09590495ba775c6c755351ecf",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.34519684314727783, 'eval_mean_iou': 0.325258521739943, 'eval_mean_accuracy': 0.38403058969464726, 'eval_overall_accuracy': 0.6185392814715919, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7561011989105695, 'eval_accuracy_RV': 0.49574270858272407, 'eval_accuracy_RA': 0.5968905603124773, 'eval_accuracy_LA': 0.6922094004486858, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0009380863039399625, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.444969688221709, 'eval_accuracy_VSD': 0.35367499325276636, 'eval_accuracy_AK': 0.49977926091360014, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7161326278270931, 'eval_iou_RV': 0.48112627218741016, 'eval_iou_RA': 0.5656582265653829, 'eval_iou_LA': 0.6389729770808661, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0009371733410229608, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3767203849385168, 'eval_iou_VSD': 0.322277860134032, 'eval_iou_AK': 0.47601821706504904, 'eval_runtime': 4.6694, 'eval_samples_per_second': 17.347, 'eval_steps_per_second': 8.781, 'epoch': 10.88}\n",
+      "{'loss': 0.0962, 'learning_rate': 5.6475e-05, 'epoch': 10.88}\n",
+      "{'loss': 0.3262, 'learning_rate': 5.645e-05, 'epoch': 10.89}\n",
+      "{'loss': 0.2164, 'learning_rate': 5.6425e-05, 'epoch': 10.89}\n",
+      "{'loss': 0.2647, 'learning_rate': 5.6399999999999995e-05, 'epoch': 10.9}\n",
+      "{'loss': 0.1082, 'learning_rate': 5.6375e-05, 'epoch': 10.91}\n",
+      "{'loss': 0.1202, 'learning_rate': 5.635e-05, 'epoch': 10.91}\n",
+      "{'loss': 0.157, 'learning_rate': 5.632500000000001e-05, 'epoch': 10.92}\n",
+      "{'loss': 0.1772, 'learning_rate': 5.63e-05, 'epoch': 10.93}\n",
+      "{'loss': 0.3458, 'learning_rate': 5.6275e-05, 'epoch': 10.93}\n",
+      "{'loss': 0.1763, 'learning_rate': 5.6250000000000005e-05, 'epoch': 10.94}\n",
+      "{'loss': 0.1259, 'learning_rate': 5.6225000000000005e-05, 'epoch': 10.94}\n",
+      "{'loss': 0.2503, 'learning_rate': 5.620000000000001e-05, 'epoch': 10.95}\n",
+      "{'loss': 0.3903, 'learning_rate': 5.6175e-05, 'epoch': 10.96}\n",
+      "{'loss': 0.2446, 'learning_rate': 5.615e-05, 'epoch': 10.96}\n",
+      "{'loss': 0.3626, 'learning_rate': 5.6125e-05, 'epoch': 10.97}\n",
+      "{'loss': 0.2527, 'learning_rate': 5.610000000000001e-05, 'epoch': 10.97}\n",
+      "{'loss': 0.2113, 'learning_rate': 5.6075e-05, 'epoch': 10.98}\n",
+      "{'loss': 0.3762, 'learning_rate': 5.605e-05, 'epoch': 10.99}\n",
+      "{'loss': 0.0862, 'learning_rate': 5.6025000000000007e-05, 'epoch': 10.99}\n",
+      "{'loss': 0.1966, 'learning_rate': 5.6000000000000006e-05, 'epoch': 11.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9b0b38b63dbe4193a1f7a9df2d6a05d0",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3358387351036072, 'eval_mean_iou': 0.336167502900995, 'eval_mean_accuracy': 0.40540604731614216, 'eval_overall_accuracy': 0.6387975262853817, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7708161183219429, 'eval_accuracy_RV': 0.5298148523299999, 'eval_accuracy_RA': 0.6320987305609581, 'eval_accuracy_LA': 0.6648628901131319, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0026879780632125846, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4850786662817552, 'eval_accuracy_VSD': 0.40283983566737636, 'eval_accuracy_AK': 0.5658614018230451, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7303704656365669, 'eval_iou_RV': 0.5005263035800243, 'eval_iou_RA': 0.5698433254153313, 'eval_iou_LA': 0.6089868364620105, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.002678362783340224, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.40066765523356757, 'eval_iou_VSD': 0.36018607893607896, 'eval_iou_AK': 0.5245835038640249, 'eval_runtime': 4.5778, 'eval_samples_per_second': 17.694, 'eval_steps_per_second': 8.956, 'epoch': 11.0}\n",
+      "{'loss': 0.3513, 'learning_rate': 5.5975e-05, 'epoch': 11.01}\n",
+      "{'loss': 0.1682, 'learning_rate': 5.5950000000000005e-05, 'epoch': 11.01}\n",
+      "{'loss': 0.2157, 'learning_rate': 5.5925000000000004e-05, 'epoch': 11.02}\n",
+      "{'loss': 0.1889, 'learning_rate': 5.590000000000001e-05, 'epoch': 11.03}\n",
+      "{'loss': 0.2085, 'learning_rate': 5.5875e-05, 'epoch': 11.03}\n",
+      "{'loss': 0.2163, 'learning_rate': 5.585e-05, 'epoch': 11.04}\n",
+      "{'loss': 0.2308, 'learning_rate': 5.582500000000001e-05, 'epoch': 11.04}\n",
+      "{'loss': 0.2223, 'learning_rate': 5.580000000000001e-05, 'epoch': 11.05}\n",
+      "{'loss': 0.1055, 'learning_rate': 5.5775e-05, 'epoch': 11.06}\n",
+      "{'loss': 0.0788, 'learning_rate': 5.575e-05, 'epoch': 11.06}\n",
+      "{'loss': 0.1129, 'learning_rate': 5.5725000000000006e-05, 'epoch': 11.07}\n",
+      "{'loss': 0.092, 'learning_rate': 5.5700000000000005e-05, 'epoch': 11.07}\n",
+      "{'loss': 0.0387, 'learning_rate': 5.5675e-05, 'epoch': 11.08}\n",
+      "{'loss': 0.1911, 'learning_rate': 5.5650000000000004e-05, 'epoch': 11.09}\n",
+      "{'loss': 0.3127, 'learning_rate': 5.5625000000000004e-05, 'epoch': 11.09}\n",
+      "{'loss': 0.1189, 'learning_rate': 5.560000000000001e-05, 'epoch': 11.1}\n",
+      "{'loss': 0.1612, 'learning_rate': 5.5575e-05, 'epoch': 11.11}\n",
+      "{'loss': 0.0756, 'learning_rate': 5.555e-05, 'epoch': 11.11}\n",
+      "{'loss': 0.0802, 'learning_rate': 5.552500000000001e-05, 'epoch': 11.12}\n",
+      "{'loss': 0.2338, 'learning_rate': 5.550000000000001e-05, 'epoch': 11.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "26336592d00048e69df3ad33e5aceaf1",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3768455982208252, 'eval_mean_iou': 0.25616576295297805, 'eval_mean_accuracy': 0.2967738649415849, 'eval_overall_accuracy': 0.4889678754660394, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6403641179997673, 'eval_accuracy_RV': 0.33930029405084194, 'eval_accuracy_RA': 0.5068374585394592, 'eval_accuracy_LA': 0.5218425620373356, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0028322990330495023, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.33160724595842955, 'eval_accuracy_VSD': 0.32560650133445285, 'eval_accuracy_AK': 0.29934817046251333, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6175207805040828, 'eval_iou_RV': 0.33307621383503777, 'eval_iou_RA': 0.4868224715617309, 'eval_iou_LA': 0.49469619368160905, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.002831430684052012, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.29017106499206646, 'eval_iou_VSD': 0.300623645940764, 'eval_iou_AK': 0.2920815912834157, 'eval_runtime': 4.5273, 'eval_samples_per_second': 17.892, 'eval_steps_per_second': 9.056, 'epoch': 11.12}\n",
+      "{'loss': 0.2018, 'learning_rate': 5.5475e-05, 'epoch': 11.13}\n",
+      "{'loss': 0.1232, 'learning_rate': 5.545e-05, 'epoch': 11.14}\n",
+      "{'loss': 0.1562, 'learning_rate': 5.5425000000000006e-05, 'epoch': 11.14}\n",
+      "{'loss': 0.0884, 'learning_rate': 5.5400000000000005e-05, 'epoch': 11.15}\n",
+      "{'loss': 0.0452, 'learning_rate': 5.5375e-05, 'epoch': 11.16}\n",
+      "{'loss': 0.2441, 'learning_rate': 5.5350000000000004e-05, 'epoch': 11.16}\n",
+      "{'loss': 0.0811, 'learning_rate': 5.5325e-05, 'epoch': 11.17}\n",
+      "{'loss': 0.1299, 'learning_rate': 5.530000000000001e-05, 'epoch': 11.18}\n",
+      "{'loss': 0.3913, 'learning_rate': 5.5275e-05, 'epoch': 11.18}\n",
+      "{'loss': 0.105, 'learning_rate': 5.525e-05, 'epoch': 11.19}\n",
+      "{'loss': 0.1977, 'learning_rate': 5.522500000000001e-05, 'epoch': 11.19}\n",
+      "{'loss': 0.1079, 'learning_rate': 5.520000000000001e-05, 'epoch': 11.2}\n",
+      "{'loss': 0.2826, 'learning_rate': 5.5175e-05, 'epoch': 11.21}\n",
+      "{'loss': 0.1694, 'learning_rate': 5.515e-05, 'epoch': 11.21}\n",
+      "{'loss': 0.4961, 'learning_rate': 5.5125000000000005e-05, 'epoch': 11.22}\n",
+      "{'loss': 0.0867, 'learning_rate': 5.5100000000000004e-05, 'epoch': 11.22}\n",
+      "{'loss': 0.191, 'learning_rate': 5.5075e-05, 'epoch': 11.23}\n",
+      "{'loss': 0.0916, 'learning_rate': 5.505e-05, 'epoch': 11.24}\n",
+      "{'loss': 0.1781, 'learning_rate': 5.5025e-05, 'epoch': 11.24}\n",
+      "{'loss': 0.1743, 'learning_rate': 5.500000000000001e-05, 'epoch': 11.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "28928eb380114ff5857e128ce6d032ba",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.25, 'learning_rate': 5.4975e-05, 'epoch': 11.26}\n",
+      "{'loss': 0.3438, 'learning_rate': 5.495e-05, 'epoch': 11.26}\n",
+      "{'loss': 0.0748, 'learning_rate': 5.492500000000001e-05, 'epoch': 11.27}\n",
+      "{'loss': 0.1683, 'learning_rate': 5.4900000000000006e-05, 'epoch': 11.28}\n",
+      "{'loss': 0.1866, 'learning_rate': 5.4875e-05, 'epoch': 11.28}\n",
+      "{'loss': 0.1616, 'learning_rate': 5.485e-05, 'epoch': 11.29}\n",
+      "{'loss': 0.253, 'learning_rate': 5.4825000000000004e-05, 'epoch': 11.29}\n",
+      "{'loss': 0.3894, 'learning_rate': 5.4800000000000004e-05, 'epoch': 11.3}\n",
+      "{'loss': 0.3162, 'learning_rate': 5.4774999999999996e-05, 'epoch': 11.31}\n",
+      "{'loss': 0.1843, 'learning_rate': 5.475e-05, 'epoch': 11.31}\n",
+      "{'loss': 0.0907, 'learning_rate': 5.4725e-05, 'epoch': 11.32}\n",
+      "{'loss': 0.0666, 'learning_rate': 5.470000000000001e-05, 'epoch': 11.32}\n",
+      "{'loss': 0.2369, 'learning_rate': 5.4675e-05, 'epoch': 11.33}\n",
+      "{'loss': 0.2213, 'learning_rate': 5.465e-05, 'epoch': 11.34}\n",
+      "{'loss': 0.1067, 'learning_rate': 5.4625000000000006e-05, 'epoch': 11.34}\n",
+      "{'loss': 0.1997, 'learning_rate': 5.4600000000000006e-05, 'epoch': 11.35}\n",
+      "{'loss': 0.1013, 'learning_rate': 5.4575e-05, 'epoch': 11.36}\n",
+      "{'loss': 0.2439, 'learning_rate': 5.455e-05, 'epoch': 11.36}\n",
+      "{'loss': 0.2794, 'learning_rate': 5.4525000000000004e-05, 'epoch': 11.37}\n",
+      "{'loss': 0.2169, 'learning_rate': 5.45e-05, 'epoch': 11.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
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+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.35669392347335815, 'eval_mean_iou': 0.28601065370468715, 'eval_mean_accuracy': 0.33264408489518715, 'eval_overall_accuracy': 0.5583171405140012, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7007078912120661, 'eval_accuracy_RV': 0.40607101419915653, 'eval_accuracy_RA': 0.5093351787140978, 'eval_accuracy_LA': 0.6900757414636489, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.00012628084860730264, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.26407332563510394, 'eval_accuracy_VSD': 0.3261912615827511, 'eval_accuracy_AK': 0.4298601552964396, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6755559901553558, 'eval_iou_RV': 0.39751178603944004, 'eval_iou_RA': 0.4886581175901282, 'eval_iou_LA': 0.6322307426380465, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.00012607614999459674, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.24546956368606865, 'eval_iou_VSD': 0.30056230226164327, 'eval_iou_AK': 0.40600261223088197, 'eval_runtime': 4.6303, 'eval_samples_per_second': 17.493, 'eval_steps_per_second': 8.855, 'epoch': 11.38}\n",
+      "{'loss': 0.0981, 'learning_rate': 5.4474999999999996e-05, 'epoch': 11.38}\n",
+      "{'loss': 0.2699, 'learning_rate': 5.445e-05, 'epoch': 11.39}\n",
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+      "{'loss': 0.2788, 'learning_rate': 5.440000000000001e-05, 'epoch': 11.4}\n",
+      "{'loss': 0.1536, 'learning_rate': 5.4375e-05, 'epoch': 11.41}\n",
+      "{'loss': 0.104, 'learning_rate': 5.435e-05, 'epoch': 11.41}\n",
+      "{'loss': 0.1419, 'learning_rate': 5.4325000000000006e-05, 'epoch': 11.42}\n",
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+      "{'loss': 0.1186, 'learning_rate': 5.4275e-05, 'epoch': 11.43}\n",
+      "{'loss': 0.2474, 'learning_rate': 5.4250000000000004e-05, 'epoch': 11.44}\n",
+      "{'loss': 0.2888, 'learning_rate': 5.4225000000000003e-05, 'epoch': 11.44}\n",
+      "{'loss': 0.1204, 'learning_rate': 5.420000000000001e-05, 'epoch': 11.45}\n",
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+      "{'loss': 0.0649, 'learning_rate': 5.415e-05, 'epoch': 11.46}\n",
+      "{'loss': 0.1144, 'learning_rate': 5.4125e-05, 'epoch': 11.47}\n",
+      "{'loss': 0.1957, 'learning_rate': 5.410000000000001e-05, 'epoch': 11.47}\n",
+      "{'loss': 0.109, 'learning_rate': 5.4075e-05, 'epoch': 11.48}\n",
+      "{'loss': 0.1772, 'learning_rate': 5.405e-05, 'epoch': 11.49}\n",
+      "{'loss': 0.1691, 'learning_rate': 5.4025000000000005e-05, 'epoch': 11.49}\n",
+      "{'loss': 0.0907, 'learning_rate': 5.4000000000000005e-05, 'epoch': 11.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "69b881f1137d42cbb168b9cce1a05d79",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.33764126896858215, 'eval_mean_iou': 0.3380142094207032, 'eval_mean_accuracy': 0.40329439296988107, 'eval_overall_accuracy': 0.6255444790420198, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7233802476575155, 'eval_accuracy_RV': 0.5018984388908329, 'eval_accuracy_RA': 0.6283945187349188, 'eval_accuracy_LA': 0.7191168298355505, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0012086881223841825, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4551187211316397, 'eval_accuracy_VSD': 0.4281194710168831, 'eval_accuracy_AK': 0.5757070143090867, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6968298258444482, 'eval_iou_RV': 0.48770125090223637, 'eval_iou_RA': 0.5865708210842704, 'eval_iou_LA': 0.6580681311644201, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0012047542840702714, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.38255165876777253, 'eval_iou_VSD': 0.38093522780334865, 'eval_iou_AK': 0.5242946337771681, 'eval_runtime': 4.565, 'eval_samples_per_second': 17.744, 'eval_steps_per_second': 8.981, 'epoch': 11.5}\n",
+      "{'loss': 0.1998, 'learning_rate': 5.3975e-05, 'epoch': 11.51}\n",
+      "{'loss': 0.0739, 'learning_rate': 5.3950000000000004e-05, 'epoch': 11.51}\n",
+      "{'loss': 0.1252, 'learning_rate': 5.3925e-05, 'epoch': 11.52}\n",
+      "{'loss': 0.2008, 'learning_rate': 5.390000000000001e-05, 'epoch': 11.53}\n",
+      "{'loss': 0.1608, 'learning_rate': 5.3874999999999995e-05, 'epoch': 11.53}\n",
+      "{'loss': 0.3566, 'learning_rate': 5.385e-05, 'epoch': 11.54}\n",
+      "{'loss': 0.1638, 'learning_rate': 5.3825e-05, 'epoch': 11.54}\n",
+      "{'loss': 0.119, 'learning_rate': 5.380000000000001e-05, 'epoch': 11.55}\n",
+      "{'loss': 0.1408, 'learning_rate': 5.3775e-05, 'epoch': 11.56}\n",
+      "{'loss': 0.1135, 'learning_rate': 5.375e-05, 'epoch': 11.56}\n",
+      "{'loss': 0.1706, 'learning_rate': 5.3725000000000005e-05, 'epoch': 11.57}\n",
+      "{'loss': 0.0755, 'learning_rate': 5.3700000000000004e-05, 'epoch': 11.57}\n",
+      "{'loss': 0.3157, 'learning_rate': 5.3675e-05, 'epoch': 11.58}\n",
+      "{'loss': 0.0116, 'learning_rate': 5.365e-05, 'epoch': 11.59}\n",
+      "{'loss': 0.2325, 'learning_rate': 5.3625e-05, 'epoch': 11.59}\n",
+      "{'loss': 0.0782, 'learning_rate': 5.360000000000001e-05, 'epoch': 11.6}\n",
+      "{'loss': 0.3592, 'learning_rate': 5.3574999999999994e-05, 'epoch': 11.61}\n",
+      "{'loss': 0.1083, 'learning_rate': 5.355e-05, 'epoch': 11.61}\n",
+      "{'loss': 0.0262, 'learning_rate': 5.3525e-05, 'epoch': 11.62}\n",
+      "{'loss': 0.3082, 'learning_rate': 5.3500000000000006e-05, 'epoch': 11.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "dd708eec6c4242cea51b957fd20bdb40",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.4522630572319031, 'eval_mean_iou': 0.20422971997384093, 'eval_mean_accuracy': 0.23074304718184163, 'eval_overall_accuracy': 0.40682484057826757, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.5530657387216195, 'eval_accuracy_RV': 0.31295235639698704, 'eval_accuracy_RA': 0.45378208904634704, 'eval_accuracy_LA': 0.3506129981682092, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0018400923654206956, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.16693129330254042, 'eval_accuracy_VSD': 0.19251356943653103, 'eval_accuracy_AK': 0.27573233438076195, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.5450834974862553, 'eval_iou_RV': 0.3083236312502835, 'eval_iou_RA': 0.43526675130047066, 'eval_iou_LA': 0.3449003109535628, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0018220793140407289, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.15700249452731252, 'eval_iou_VSD': 0.1833860612596142, 'eval_iou_AK': 0.27074209362071056, 'eval_runtime': 4.8879, 'eval_samples_per_second': 16.572, 'eval_steps_per_second': 8.388, 'epoch': 11.62}\n",
+      "{'loss': 0.0929, 'learning_rate': 5.3475e-05, 'epoch': 11.63}\n",
+      "{'loss': 0.1014, 'learning_rate': 5.345e-05, 'epoch': 11.64}\n",
+      "{'loss': 0.2334, 'learning_rate': 5.3425000000000004e-05, 'epoch': 11.64}\n",
+      "{'loss': 0.0784, 'learning_rate': 5.3400000000000004e-05, 'epoch': 11.65}\n",
+      "{'loss': 0.1365, 'learning_rate': 5.3374999999999996e-05, 'epoch': 11.66}\n",
+      "{'loss': 0.2538, 'learning_rate': 5.335e-05, 'epoch': 11.66}\n",
+      "{'loss': 0.0878, 'learning_rate': 5.3325e-05, 'epoch': 11.67}\n",
+      "{'loss': 0.243, 'learning_rate': 5.330000000000001e-05, 'epoch': 11.68}\n",
+      "{'loss': 0.1892, 'learning_rate': 5.3274999999999994e-05, 'epoch': 11.68}\n",
+      "{'loss': 0.3552, 'learning_rate': 5.325e-05, 'epoch': 11.69}\n",
+      "{'loss': 0.0121, 'learning_rate': 5.3225e-05, 'epoch': 11.69}\n",
+      "{'loss': 0.2027, 'learning_rate': 5.3200000000000006e-05, 'epoch': 11.7}\n",
+      "{'loss': 0.2475, 'learning_rate': 5.3175e-05, 'epoch': 11.71}\n",
+      "{'loss': 0.1749, 'learning_rate': 5.315e-05, 'epoch': 11.71}\n",
+      "{'loss': 0.144, 'learning_rate': 5.3125000000000004e-05, 'epoch': 11.72}\n",
+      "{'loss': 0.3019, 'learning_rate': 5.31e-05, 'epoch': 11.72}\n",
+      "{'loss': 0.1251, 'learning_rate': 5.307500000000001e-05, 'epoch': 11.73}\n",
+      "{'loss': 0.2403, 'learning_rate': 5.305e-05, 'epoch': 11.74}\n",
+      "{'loss': 0.2452, 'learning_rate': 5.3025e-05, 'epoch': 11.74}\n",
+      "{'loss': 0.2489, 'learning_rate': 5.300000000000001e-05, 'epoch': 11.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a8941326e63246c8a425805eb22b62bc",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3445111811161041, 'eval_mean_iou': 0.3672929319392759, 'eval_mean_accuracy': 0.4429377165489325, 'eval_overall_accuracy': 0.6865007064973958, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7957422118542693, 'eval_accuracy_RV': 0.5782565056446711, 'eval_accuracy_RA': 0.6980784905538563, 'eval_accuracy_LA': 0.7475387454634019, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.001334968970991485, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4922957563510393, 'eval_accuracy_VSD': 0.4925555522235883, 'eval_accuracy_AK': 0.6235749344275067, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7580506623187016, 'eval_iou_RV': 0.5545939071724741, 'eval_iou_RA': 0.6268949310876502, 'eval_iou_LA': 0.6735571610709732, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0013234136919665213, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.41821539970724153, 'eval_iou_VSD': 0.42878213369706386, 'eval_iou_AK': 0.5788046425859638, 'eval_runtime': 4.5786, 'eval_samples_per_second': 17.691, 'eval_steps_per_second': 8.955, 'epoch': 11.75}\n",
+      "{'loss': 0.2849, 'learning_rate': 5.297500000000001e-05, 'epoch': 11.76}\n",
+      "{'loss': 0.2691, 'learning_rate': 5.295e-05, 'epoch': 11.76}\n",
+      "{'loss': 0.0788, 'learning_rate': 5.2925000000000006e-05, 'epoch': 11.77}\n",
+      "{'loss': 0.1758, 'learning_rate': 5.2900000000000005e-05, 'epoch': 11.78}\n",
+      "{'loss': 0.1984, 'learning_rate': 5.2875000000000005e-05, 'epoch': 11.78}\n",
+      "{'loss': 0.1708, 'learning_rate': 5.285e-05, 'epoch': 11.79}\n",
+      "{'loss': 0.1282, 'learning_rate': 5.2825e-05, 'epoch': 11.79}\n",
+      "{'loss': 0.1162, 'learning_rate': 5.28e-05, 'epoch': 11.8}\n",
+      "{'loss': 0.2513, 'learning_rate': 5.277500000000001e-05, 'epoch': 11.81}\n",
+      "{'loss': 0.2033, 'learning_rate': 5.275e-05, 'epoch': 11.81}\n",
+      "{'loss': 0.216, 'learning_rate': 5.2725e-05, 'epoch': 11.82}\n",
+      "{'loss': 0.251, 'learning_rate': 5.270000000000001e-05, 'epoch': 11.82}\n",
+      "{'loss': 0.1706, 'learning_rate': 5.2675000000000006e-05, 'epoch': 11.83}\n",
+      "{'loss': 0.2912, 'learning_rate': 5.265e-05, 'epoch': 11.84}\n",
+      "{'loss': 0.1727, 'learning_rate': 5.2625000000000005e-05, 'epoch': 11.84}\n",
+      "{'loss': 0.2852, 'learning_rate': 5.2600000000000005e-05, 'epoch': 11.85}\n",
+      "{'loss': 0.2938, 'learning_rate': 5.257500000000001e-05, 'epoch': 11.86}\n",
+      "{'loss': 0.1994, 'learning_rate': 5.255e-05, 'epoch': 11.86}\n",
+      "{'loss': 0.1322, 'learning_rate': 5.2525e-05, 'epoch': 11.87}\n",
+      "{'loss': 0.1404, 'learning_rate': 5.25e-05, 'epoch': 11.88}\n"
+     ]
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+    {
+     "data": {
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+       "model_id": "f7038709de3e4b51b3720340addfb138",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.34463661909103394, 'eval_mean_iou': 0.3304202601558312, 'eval_mean_accuracy': 0.3944404223202768, 'eval_overall_accuracy': 0.6159047927138804, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7216657071006888, 'eval_accuracy_RV': 0.5020657225117713, 'eval_accuracy_RA': 0.6087698627262677, 'eval_accuracy_LA': 0.6916108096241056, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.43885320438799075, 'eval_accuracy_VSD': 0.42192700992593035, 'eval_accuracy_AK': 0.5595119069260135, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.698794241069462, 'eval_iou_RV': 0.48308165754569593, 'eval_iou_RA': 0.5618852535334538, 'eval_iou_LA': 0.6350741802375027, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3535756597835488, 'eval_iou_VSD': 0.37820038975875275, 'eval_iou_AK': 0.5240114797857269, 'eval_runtime': 4.4615, 'eval_samples_per_second': 18.155, 'eval_steps_per_second': 9.19, 'epoch': 11.88}\n",
+      "{'loss': 0.1558, 'learning_rate': 5.247500000000001e-05, 'epoch': 11.88}\n",
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+      "{'loss': 0.3033, 'learning_rate': 5.227500000000001e-05, 'epoch': 11.93}\n",
+      "{'loss': 0.2069, 'learning_rate': 5.2249999999999996e-05, 'epoch': 11.94}\n",
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+      "{'loss': 0.2898, 'learning_rate': 5.217500000000001e-05, 'epoch': 11.96}\n",
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+      "{'loss': 0.1526, 'learning_rate': 5.2125e-05, 'epoch': 11.97}\n",
+      "{'loss': 0.1853, 'learning_rate': 5.2100000000000006e-05, 'epoch': 11.97}\n",
+      "{'loss': 0.1448, 'learning_rate': 5.2075000000000005e-05, 'epoch': 11.98}\n",
+      "{'loss': 0.1833, 'learning_rate': 5.205e-05, 'epoch': 11.99}\n",
+      "{'loss': 0.0775, 'learning_rate': 5.2025000000000004e-05, 'epoch': 11.99}\n",
+      "{'loss': 0.2317, 'learning_rate': 5.2000000000000004e-05, 'epoch': 12.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2abc88879ed940d8a05bbf579006536e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3496910333633423, 'eval_mean_iou': 0.30697019213231874, 'eval_mean_accuracy': 0.3641616987789507, 'eval_overall_accuracy': 0.5736096174527577, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6659390372321543, 'eval_accuracy_RV': 0.4781994143538555, 'eval_accuracy_RA': 0.62445021910534, 'eval_accuracy_LA': 0.6223835234874004, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.01686751334968971, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.39252850750577367, 'eval_accuracy_VSD': 0.34245959156745737, 'eval_accuracy_AK': 0.498789181187836, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6451710093660115, 'eval_iou_RV': 0.46265447726068, 'eval_iou_RA': 0.5598606453293393, 'eval_iou_LA': 0.5799299044136567, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.016749968649791298, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.32884156111127905, 'eval_iou_VSD': 0.3141829386559188, 'eval_iou_AK': 0.469281608668829, 'eval_runtime': 4.5861, 'eval_samples_per_second': 17.662, 'eval_steps_per_second': 8.94, 'epoch': 12.0}\n",
+      "{'loss': 0.1545, 'learning_rate': 5.197500000000001e-05, 'epoch': 12.01}\n",
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+      "{'loss': 0.2135, 'learning_rate': 5.187500000000001e-05, 'epoch': 12.03}\n",
+      "{'loss': 0.0978, 'learning_rate': 5.185e-05, 'epoch': 12.04}\n",
+      "{'loss': 0.2455, 'learning_rate': 5.1825e-05, 'epoch': 12.04}\n",
+      "{'loss': 0.311, 'learning_rate': 5.1800000000000005e-05, 'epoch': 12.05}\n",
+      "{'loss': 0.0601, 'learning_rate': 5.1775000000000005e-05, 'epoch': 12.06}\n",
+      "{'loss': 0.0617, 'learning_rate': 5.175e-05, 'epoch': 12.06}\n",
+      "{'loss': 0.1349, 'learning_rate': 5.1725000000000004e-05, 'epoch': 12.07}\n",
+      "{'loss': 0.1737, 'learning_rate': 5.17e-05, 'epoch': 12.07}\n",
+      "{'loss': 0.1043, 'learning_rate': 5.167500000000001e-05, 'epoch': 12.08}\n",
+      "{'loss': 0.201, 'learning_rate': 5.1649999999999995e-05, 'epoch': 12.09}\n",
+      "{'loss': 0.1891, 'learning_rate': 5.1625e-05, 'epoch': 12.09}\n",
+      "{'loss': 0.1323, 'learning_rate': 5.16e-05, 'epoch': 12.1}\n",
+      "{'loss': 0.1718, 'learning_rate': 5.157500000000001e-05, 'epoch': 12.11}\n",
+      "{'loss': 0.0553, 'learning_rate': 5.155e-05, 'epoch': 12.11}\n",
+      "{'loss': 0.0663, 'learning_rate': 5.1525e-05, 'epoch': 12.12}\n",
+      "{'loss': 0.2063, 'learning_rate': 5.1500000000000005e-05, 'epoch': 12.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c2484317d78a4a768dfe8c6533178fb3",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.34791091084480286, 'eval_mean_iou': 0.29596109327877623, 'eval_mean_accuracy': 0.34596201806844895, 'eval_overall_accuracy': 0.5817500254252509, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7261836221477771, 'eval_accuracy_RV': 0.4376124176626948, 'eval_accuracy_RA': 0.5551475632096713, 'eval_accuracy_LA': 0.6686671148951351, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0011726078799249532, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.23285941108545036, 'eval_accuracy_VSD': 0.3269859357663358, 'eval_accuracy_AK': 0.5109915080374997, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6963262463180583, 'eval_iou_RV': 0.4270161151436825, 'eval_iou_RA': 0.5212123737742057, 'eval_iou_LA': 0.6155708118725586, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.001170664937684605, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.21763361803664324, 'eval_iou_VSD': 0.29906131936397357, 'eval_iou_AK': 0.477580876619732, 'eval_runtime': 4.56, 'eval_samples_per_second': 17.763, 'eval_steps_per_second': 8.991, 'epoch': 12.12}\n",
+      "{'loss': 0.2033, 'learning_rate': 5.1475000000000004e-05, 'epoch': 12.13}\n",
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+      "{'loss': 0.2219, 'learning_rate': 5.14e-05, 'epoch': 12.15}\n",
+      "{'loss': 0.1673, 'learning_rate': 5.137500000000001e-05, 'epoch': 12.16}\n",
+      "{'loss': 0.2591, 'learning_rate': 5.135e-05, 'epoch': 12.16}\n",
+      "{'loss': 0.5607, 'learning_rate': 5.1325e-05, 'epoch': 12.17}\n",
+      "{'loss': 0.1666, 'learning_rate': 5.130000000000001e-05, 'epoch': 12.18}\n",
+      "{'loss': 0.2558, 'learning_rate': 5.1275000000000006e-05, 'epoch': 12.18}\n",
+      "{'loss': 0.2379, 'learning_rate': 5.125e-05, 'epoch': 12.19}\n",
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+      "{'loss': 0.0226, 'learning_rate': 5.1200000000000004e-05, 'epoch': 12.2}\n",
+      "{'loss': 0.0918, 'learning_rate': 5.1175000000000004e-05, 'epoch': 12.21}\n",
+      "{'loss': 0.1382, 'learning_rate': 5.1149999999999996e-05, 'epoch': 12.21}\n",
+      "{'loss': 0.2411, 'learning_rate': 5.1125e-05, 'epoch': 12.22}\n",
+      "{'loss': 0.102, 'learning_rate': 5.11e-05, 'epoch': 12.22}\n",
+      "{'loss': 0.1866, 'learning_rate': 5.107500000000001e-05, 'epoch': 12.23}\n",
+      "{'loss': 0.297, 'learning_rate': 5.105e-05, 'epoch': 12.24}\n",
+      "{'loss': 0.2407, 'learning_rate': 5.1025e-05, 'epoch': 12.24}\n",
+      "{'loss': 0.2079, 'learning_rate': 5.1000000000000006e-05, 'epoch': 12.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "cc91b2b99808413da0f44d573059c003",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.39832377433776855, 'eval_mean_iou': 0.258530468069949, 'eval_mean_accuracy': 0.297334775785783, 'eval_overall_accuracy': 0.49071383285115516, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6142805790806661, 'eval_accuracy_RV': 0.37381596960042235, 'eval_accuracy_RA': 0.4643096365998725, 'eval_accuracy_LA': 0.5455906667855844, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.01930292971568769, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.2831805715935335, 'eval_accuracy_VSD': 0.23475874891294568, 'eval_accuracy_AK': 0.4381086555691173, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.5981131760350701, 'eval_iou_RV': 0.364798844979886, 'eval_iou_RA': 0.45331988622485564, 'eval_iou_LA': 0.517456273912704, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.018804920913884006, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2518372324379834, 'eval_iou_VSD': 0.22135510550312798, 'eval_iou_AK': 0.41814970876192836, 'eval_runtime': 4.5061, 'eval_samples_per_second': 17.976, 'eval_steps_per_second': 9.099, 'epoch': 12.25}\n",
+      "{'loss': 0.3536, 'learning_rate': 5.0975000000000006e-05, 'epoch': 12.26}\n",
+      "{'loss': 0.1707, 'learning_rate': 5.095e-05, 'epoch': 12.26}\n",
+      "{'loss': 0.171, 'learning_rate': 5.0925e-05, 'epoch': 12.27}\n",
+      "{'loss': 0.109, 'learning_rate': 5.0900000000000004e-05, 'epoch': 12.28}\n",
+      "{'loss': 0.1963, 'learning_rate': 5.0875e-05, 'epoch': 12.28}\n",
+      "{'loss': 0.168, 'learning_rate': 5.0849999999999996e-05, 'epoch': 12.29}\n",
+      "{'loss': 0.0761, 'learning_rate': 5.0825e-05, 'epoch': 12.29}\n",
+      "{'loss': 0.1412, 'learning_rate': 5.08e-05, 'epoch': 12.3}\n",
+      "{'loss': 0.1758, 'learning_rate': 5.077500000000001e-05, 'epoch': 12.31}\n",
+      "{'loss': 0.1564, 'learning_rate': 5.075e-05, 'epoch': 12.31}\n",
+      "{'loss': 0.0709, 'learning_rate': 5.0725e-05, 'epoch': 12.32}\n",
+      "{'loss': 0.2261, 'learning_rate': 5.0700000000000006e-05, 'epoch': 12.32}\n",
+      "{'loss': 0.1413, 'learning_rate': 5.0675000000000005e-05, 'epoch': 12.33}\n",
+      "{'loss': 0.1162, 'learning_rate': 5.065e-05, 'epoch': 12.34}\n",
+      "{'loss': 0.0121, 'learning_rate': 5.0625e-05, 'epoch': 12.34}\n",
+      "{'loss': 0.2899, 'learning_rate': 5.0600000000000003e-05, 'epoch': 12.35}\n",
+      "{'loss': 0.1497, 'learning_rate': 5.0575e-05, 'epoch': 12.36}\n",
+      "{'loss': 0.1063, 'learning_rate': 5.0549999999999995e-05, 'epoch': 12.36}\n",
+      "{'loss': 0.2179, 'learning_rate': 5.0525e-05, 'epoch': 12.37}\n",
+      "{'loss': 0.1139, 'learning_rate': 5.05e-05, 'epoch': 12.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f1be14b284d5475697eb7ce37924133d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3452411890029907, 'eval_mean_iou': 0.3338568029420432, 'eval_mean_accuracy': 0.3970191914835914, 'eval_overall_accuracy': 0.6347219126712959, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7720153272020548, 'eval_accuracy_RV': 0.5085483465011633, 'eval_accuracy_RA': 0.6268934655766546, 'eval_accuracy_LA': 0.6761966671011739, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.018545244624043875, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4057267609699769, 'eval_accuracy_VSD': 0.38536450055477256, 'eval_accuracy_AK': 0.5769016023060742, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7292650589508329, 'eval_iou_RV': 0.49422275252619413, 'eval_iou_RA': 0.5691757309759413, 'eval_iou_LA': 0.6202753303964758, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.018264515670528038, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.34643085479236796, 'eval_iou_VSD': 0.348987046139641, 'eval_iou_AK': 0.5458035429104936, 'eval_runtime': 4.588, 'eval_samples_per_second': 17.655, 'eval_steps_per_second': 8.936, 'epoch': 12.38}\n",
+      "{'loss': 0.0618, 'learning_rate': 5.047500000000001e-05, 'epoch': 12.38}\n",
+      "{'loss': 0.2096, 'learning_rate': 5.045e-05, 'epoch': 12.39}\n",
+      "{'loss': 0.1659, 'learning_rate': 5.0425e-05, 'epoch': 12.39}\n",
+      "{'loss': 0.21, 'learning_rate': 5.0400000000000005e-05, 'epoch': 12.4}\n",
+      "{'loss': 0.1525, 'learning_rate': 5.0375000000000005e-05, 'epoch': 12.41}\n",
+      "{'loss': 0.1585, 'learning_rate': 5.035e-05, 'epoch': 12.41}\n",
+      "{'loss': 0.1392, 'learning_rate': 5.0325e-05, 'epoch': 12.42}\n",
+      "{'loss': 0.1059, 'learning_rate': 5.03e-05, 'epoch': 12.43}\n",
+      "{'loss': 0.2623, 'learning_rate': 5.0275e-05, 'epoch': 12.43}\n",
+      "{'loss': 0.1707, 'learning_rate': 5.0249999999999995e-05, 'epoch': 12.44}\n",
+      "{'loss': 0.23, 'learning_rate': 5.0225e-05, 'epoch': 12.44}\n",
+      "{'loss': 0.2584, 'learning_rate': 5.02e-05, 'epoch': 12.45}\n",
+      "{'loss': 0.1913, 'learning_rate': 5.017500000000001e-05, 'epoch': 12.46}\n",
+      "{'loss': 0.1886, 'learning_rate': 5.015e-05, 'epoch': 12.46}\n",
+      "{'loss': 0.1741, 'learning_rate': 5.0125e-05, 'epoch': 12.47}\n",
+      "{'loss': 0.2032, 'learning_rate': 5.0100000000000005e-05, 'epoch': 12.47}\n",
+      "{'loss': 0.1909, 'learning_rate': 5.0075000000000004e-05, 'epoch': 12.48}\n",
+      "{'loss': 0.1645, 'learning_rate': 5.005e-05, 'epoch': 12.49}\n",
+      "{'loss': 0.2323, 'learning_rate': 5.0025e-05, 'epoch': 12.49}\n",
+      "{'loss': 0.168, 'learning_rate': 5e-05, 'epoch': 12.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "72b53bbf8232427fbbf9dc15d3a2f6e3",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.34912028908729553, 'eval_mean_iou': 0.3077906206995689, 'eval_mean_accuracy': 0.36095623829901224, 'eval_overall_accuracy': 0.5968039377762967, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7795402137694237, 'eval_accuracy_RV': 0.483966862495933, 'eval_accuracy_RA': 0.5374819429761204, 'eval_accuracy_LA': 0.588529696279475, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.01737263674411892, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.39154517898383373, 'eval_accuracy_VSD': 0.3317389870153237, 'eval_accuracy_AK': 0.479386864725894, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7344655435909146, 'eval_iou_RV': 0.4711446376252949, 'eval_iou_RA': 0.5102596270793629, 'eval_iou_LA': 0.5536687610730848, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.01681538004854284, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3307902779577309, 'eval_iou_VSD': 0.30741335111815093, 'eval_iou_AK': 0.4611392492021758, 'eval_runtime': 4.5921, 'eval_samples_per_second': 17.639, 'eval_steps_per_second': 8.928, 'epoch': 12.5}\n",
+      "{'loss': 0.0766, 'learning_rate': 4.9975e-05, 'epoch': 12.51}\n",
+      "{'loss': 0.0588, 'learning_rate': 4.995e-05, 'epoch': 12.51}\n",
+      "{'loss': 0.2504, 'learning_rate': 4.992500000000001e-05, 'epoch': 12.52}\n",
+      "{'loss': 0.0908, 'learning_rate': 4.99e-05, 'epoch': 12.53}\n",
+      "{'loss': 0.1601, 'learning_rate': 4.9875000000000006e-05, 'epoch': 12.53}\n",
+      "{'loss': 0.127, 'learning_rate': 4.9850000000000006e-05, 'epoch': 12.54}\n",
+      "{'loss': 0.4177, 'learning_rate': 4.9825000000000005e-05, 'epoch': 12.54}\n",
+      "{'loss': 0.2173, 'learning_rate': 4.9800000000000004e-05, 'epoch': 12.55}\n",
+      "{'loss': 0.1472, 'learning_rate': 4.9775000000000004e-05, 'epoch': 12.56}\n",
+      "{'loss': 0.092, 'learning_rate': 4.975e-05, 'epoch': 12.56}\n",
+      "{'loss': 0.2074, 'learning_rate': 4.9725e-05, 'epoch': 12.57}\n",
+      "{'loss': 0.1356, 'learning_rate': 4.97e-05, 'epoch': 12.57}\n",
+      "{'loss': 0.1499, 'learning_rate': 4.967500000000001e-05, 'epoch': 12.58}\n",
+      "{'loss': 0.0975, 'learning_rate': 4.965e-05, 'epoch': 12.59}\n",
+      "{'loss': 0.1936, 'learning_rate': 4.962500000000001e-05, 'epoch': 12.59}\n",
+      "{'loss': 0.2088, 'learning_rate': 4.96e-05, 'epoch': 12.6}\n",
+      "{'loss': 0.1739, 'learning_rate': 4.9575000000000006e-05, 'epoch': 12.61}\n",
+      "{'loss': 0.1471, 'learning_rate': 4.9550000000000005e-05, 'epoch': 12.61}\n",
+      "{'loss': 0.244, 'learning_rate': 4.9525000000000004e-05, 'epoch': 12.62}\n",
+      "{'loss': 0.2246, 'learning_rate': 4.9500000000000004e-05, 'epoch': 12.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "dc83763ee8ca4b2dbbbc0f6515681c85",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3425140678882599, 'eval_mean_iou': 0.3319827452362138, 'eval_mean_accuracy': 0.39778103719545005, 'eval_overall_accuracy': 0.6254468352595215, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7402743264890923, 'eval_accuracy_RV': 0.4888272957758584, 'eval_accuracy_RA': 0.6463163671285499, 'eval_accuracy_LA': 0.6802135717176984, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.014504257468610188, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4103005918013857, 'eval_accuracy_VSD': 0.39651242990373947, 'eval_accuracy_AK': 0.6008615316695666, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.708921022691969, 'eval_iou_RV': 0.47358521705902384, 'eval_iou_RA': 0.5823217395414109, 'eval_iou_LA': 0.6231032218126742, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.014283176407887723, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.34221456411491175, 'eval_iou_VSD': 0.35625517812758906, 'eval_iou_AK': 0.551126077842885, 'eval_runtime': 4.564, 'eval_samples_per_second': 17.748, 'eval_steps_per_second': 8.983, 'epoch': 12.62}\n",
+      "{'loss': 0.1872, 'learning_rate': 4.9475e-05, 'epoch': 12.63}\n",
+      "{'loss': 0.2027, 'learning_rate': 4.945e-05, 'epoch': 12.64}\n",
+      "{'loss': 0.2407, 'learning_rate': 4.9425e-05, 'epoch': 12.64}\n",
+      "{'loss': 0.2004, 'learning_rate': 4.94e-05, 'epoch': 12.65}\n",
+      "{'loss': 0.0107, 'learning_rate': 4.937500000000001e-05, 'epoch': 12.66}\n",
+      "{'loss': 0.2115, 'learning_rate': 4.935e-05, 'epoch': 12.66}\n",
+      "{'loss': 0.14, 'learning_rate': 4.9325000000000006e-05, 'epoch': 12.67}\n",
+      "{'loss': 0.1626, 'learning_rate': 4.93e-05, 'epoch': 12.68}\n",
+      "{'loss': 0.2034, 'learning_rate': 4.9275000000000005e-05, 'epoch': 12.68}\n",
+      "{'loss': 0.0937, 'learning_rate': 4.9250000000000004e-05, 'epoch': 12.69}\n",
+      "{'loss': 0.1094, 'learning_rate': 4.9225000000000004e-05, 'epoch': 12.69}\n",
+      "{'loss': 0.1362, 'learning_rate': 4.92e-05, 'epoch': 12.7}\n",
+      "{'loss': 0.1085, 'learning_rate': 4.9175e-05, 'epoch': 12.71}\n",
+      "{'loss': 0.2275, 'learning_rate': 4.915e-05, 'epoch': 12.71}\n",
+      "{'loss': 0.15, 'learning_rate': 4.9125e-05, 'epoch': 12.72}\n",
+      "{'loss': 0.0782, 'learning_rate': 4.91e-05, 'epoch': 12.72}\n",
+      "{'loss': 0.0708, 'learning_rate': 4.907500000000001e-05, 'epoch': 12.73}\n",
+      "{'loss': 0.1285, 'learning_rate': 4.905e-05, 'epoch': 12.74}\n",
+      "{'loss': 0.2726, 'learning_rate': 4.9025000000000006e-05, 'epoch': 12.74}\n",
+      "{'loss': 0.1949, 'learning_rate': 4.9e-05, 'epoch': 12.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e5730e62801e4128840d88e6b97e8c93",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.39219143986701965, 'eval_mean_iou': 0.2672240948735559, 'eval_mean_accuracy': 0.31036119892524944, 'eval_overall_accuracy': 0.5027626969375015, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6407966684664743, 'eval_accuracy_RV': 0.37812237180549674, 'eval_accuracy_RA': 0.45273498341578366, 'eval_accuracy_LA': 0.5270497876631974, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.013205368740077933, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3543771651270208, 'eval_accuracy_VSD': 0.2615452664407593, 'eval_accuracy_AK': 0.47578037759368424, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6208912384960459, 'eval_iou_RV': 0.37112128697957464, 'eval_iou_RA': 0.43535932825541196, 'eval_iou_LA': 0.49661905546882323, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.013000390722125528, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.30501525775117055, 'eval_iou_VSD': 0.2453772410446134, 'eval_iou_AK': 0.4520812448913496, 'eval_runtime': 4.5214, 'eval_samples_per_second': 17.915, 'eval_steps_per_second': 9.068, 'epoch': 12.75}\n",
+      "{'loss': 0.1907, 'learning_rate': 4.8975000000000005e-05, 'epoch': 12.76}\n",
+      "{'loss': 0.0981, 'learning_rate': 4.8950000000000004e-05, 'epoch': 12.76}\n",
+      "{'loss': 0.1032, 'learning_rate': 4.8925e-05, 'epoch': 12.77}\n",
+      "{'loss': 0.1681, 'learning_rate': 4.89e-05, 'epoch': 12.78}\n",
+      "{'loss': 0.2263, 'learning_rate': 4.8875e-05, 'epoch': 12.78}\n",
+      "{'loss': 0.418, 'learning_rate': 4.885e-05, 'epoch': 12.79}\n",
+      "{'loss': 0.2373, 'learning_rate': 4.8825e-05, 'epoch': 12.79}\n",
+      "{'loss': 0.162, 'learning_rate': 4.88e-05, 'epoch': 12.8}\n",
+      "{'loss': 0.2202, 'learning_rate': 4.8775000000000007e-05, 'epoch': 12.81}\n",
+      "{'loss': 0.4054, 'learning_rate': 4.875e-05, 'epoch': 12.81}\n",
+      "{'loss': 0.3333, 'learning_rate': 4.8725000000000005e-05, 'epoch': 12.82}\n",
+      "{'loss': 0.2562, 'learning_rate': 4.87e-05, 'epoch': 12.82}\n",
+      "{'loss': 0.1837, 'learning_rate': 4.8675000000000004e-05, 'epoch': 12.83}\n",
+      "{'loss': 0.1279, 'learning_rate': 4.8650000000000003e-05, 'epoch': 12.84}\n",
+      "{'loss': 0.1996, 'learning_rate': 4.8625e-05, 'epoch': 12.84}\n",
+      "{'loss': 0.2253, 'learning_rate': 4.86e-05, 'epoch': 12.85}\n",
+      "{'loss': 0.188, 'learning_rate': 4.8575e-05, 'epoch': 12.86}\n",
+      "{'loss': 0.1492, 'learning_rate': 4.855e-05, 'epoch': 12.86}\n",
+      "{'loss': 0.1235, 'learning_rate': 4.8525e-05, 'epoch': 12.87}\n",
+      "{'loss': 0.0716, 'learning_rate': 4.85e-05, 'epoch': 12.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "15d0546da51f4f34a162329b60e1441d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3551192581653595, 'eval_mean_iou': 0.30237402303309496, 'eval_mean_accuracy': 0.35838820729488363, 'eval_overall_accuracy': 0.5582638556797846, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.677256943926544, 'eval_accuracy_RV': 0.47076526885086895, 'eval_accuracy_RA': 0.527041149839, 'eval_accuracy_LA': 0.5695205784891499, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.03281498051666907, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4380232390300231, 'eval_accuracy_VSD': 0.3554817524814826, 'eval_accuracy_AK': 0.5129781598150985, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6572571481508823, 'eval_iou_RV': 0.4450946648712651, 'eval_iou_RA': 0.494244544425987, 'eval_iou_LA': 0.53005441801142, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.031905563740966814, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3634607898913076, 'eval_iou_VSD': 0.3259751687726004, 'eval_iou_AK': 0.4781219554996157, 'eval_runtime': 4.5645, 'eval_samples_per_second': 17.746, 'eval_steps_per_second': 8.982, 'epoch': 12.88}\n",
+      "{'loss': 0.2202, 'learning_rate': 4.8475000000000006e-05, 'epoch': 12.88}\n",
+      "{'loss': 0.1916, 'learning_rate': 4.845e-05, 'epoch': 12.89}\n",
+      "{'loss': 0.1189, 'learning_rate': 4.8425000000000005e-05, 'epoch': 12.89}\n",
+      "{'loss': 0.1483, 'learning_rate': 4.8400000000000004e-05, 'epoch': 12.9}\n",
+      "{'loss': 0.2445, 'learning_rate': 4.8375000000000004e-05, 'epoch': 12.91}\n",
+      "{'loss': 0.1007, 'learning_rate': 4.835e-05, 'epoch': 12.91}\n",
+      "{'loss': 0.2796, 'learning_rate': 4.8325e-05, 'epoch': 12.92}\n",
+      "{'loss': 0.1663, 'learning_rate': 4.83e-05, 'epoch': 12.93}\n",
+      "{'loss': 0.2031, 'learning_rate': 4.8275e-05, 'epoch': 12.93}\n",
+      "{'loss': 0.0939, 'learning_rate': 4.825e-05, 'epoch': 12.94}\n",
+      "{'loss': 0.0423, 'learning_rate': 4.822500000000001e-05, 'epoch': 12.94}\n",
+      "{'loss': 0.0877, 'learning_rate': 4.82e-05, 'epoch': 12.95}\n",
+      "{'loss': 0.1314, 'learning_rate': 4.8175000000000005e-05, 'epoch': 12.96}\n",
+      "{'loss': 0.0359, 'learning_rate': 4.815e-05, 'epoch': 12.96}\n",
+      "{'loss': 0.313, 'learning_rate': 4.8125000000000004e-05, 'epoch': 12.97}\n",
+      "{'loss': 0.1926, 'learning_rate': 4.8100000000000004e-05, 'epoch': 12.97}\n",
+      "{'loss': 0.2327, 'learning_rate': 4.8075e-05, 'epoch': 12.98}\n",
+      "{'loss': 0.194, 'learning_rate': 4.805e-05, 'epoch': 12.99}\n",
+      "{'loss': 0.1229, 'learning_rate': 4.8025e-05, 'epoch': 12.99}\n",
+      "{'loss': 0.1063, 'learning_rate': 4.8e-05, 'epoch': 13.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0a838e470f4448d5865699b40af4fe5a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.1715, 'learning_rate': 4.7975e-05, 'epoch': 13.01}\n",
+      "{'loss': 0.2337, 'learning_rate': 4.795e-05, 'epoch': 13.01}\n",
+      "{'loss': 0.2016, 'learning_rate': 4.7925000000000006e-05, 'epoch': 13.02}\n",
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+      "{'loss': 0.0758, 'learning_rate': 4.7875000000000005e-05, 'epoch': 13.03}\n",
+      "{'loss': 0.1278, 'learning_rate': 4.785e-05, 'epoch': 13.04}\n",
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+      "{'loss': 0.156, 'learning_rate': 4.78e-05, 'epoch': 13.05}\n",
+      "{'loss': 0.1172, 'learning_rate': 4.7775e-05, 'epoch': 13.06}\n",
+      "{'loss': 0.0663, 'learning_rate': 4.775e-05, 'epoch': 13.06}\n",
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+      "{'loss': 0.0128, 'learning_rate': 4.77e-05, 'epoch': 13.07}\n",
+      "{'loss': 0.2157, 'learning_rate': 4.7675e-05, 'epoch': 13.08}\n",
+      "{'loss': 0.1876, 'learning_rate': 4.765e-05, 'epoch': 13.09}\n",
+      "{'loss': 0.0909, 'learning_rate': 4.7625000000000006e-05, 'epoch': 13.09}\n",
+      "{'loss': 0.2447, 'learning_rate': 4.76e-05, 'epoch': 13.1}\n",
+      "{'loss': 0.1445, 'learning_rate': 4.7575000000000004e-05, 'epoch': 13.11}\n",
+      "{'loss': 0.2408, 'learning_rate': 4.755e-05, 'epoch': 13.11}\n",
+      "{'loss': 0.0347, 'learning_rate': 4.7525e-05, 'epoch': 13.12}\n",
+      "{'loss': 0.1873, 'learning_rate': 4.75e-05, 'epoch': 13.12}\n"
+     ]
+    },
+    {
+     "data": {
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+       "model_id": "4f598e0088c4427caa0a72fa49715b52",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.311, 'learning_rate': 4.74e-05, 'epoch': 13.15}\n",
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+      "{'loss': 0.3044, 'learning_rate': 4.7249999999999997e-05, 'epoch': 13.19}\n",
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+      "{'loss': 0.2817, 'learning_rate': 4.7175e-05, 'epoch': 13.21}\n",
+      "{'loss': 0.1517, 'learning_rate': 4.715e-05, 'epoch': 13.21}\n",
+      "{'loss': 0.1258, 'learning_rate': 4.7125e-05, 'epoch': 13.22}\n",
+      "{'loss': 0.17, 'learning_rate': 4.71e-05, 'epoch': 13.22}\n",
+      "{'loss': 0.154, 'learning_rate': 4.7075e-05, 'epoch': 13.23}\n",
+      "{'loss': 0.2024, 'learning_rate': 4.705e-05, 'epoch': 13.24}\n",
+      "{'loss': 0.1785, 'learning_rate': 4.7025000000000005e-05, 'epoch': 13.24}\n",
+      "{'loss': 0.0949, 'learning_rate': 4.7e-05, 'epoch': 13.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "504e7a5719b946d39fc292d6b831a5b8",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3521435260772705, 'eval_mean_iou': 0.33642998131406004, 'eval_mean_accuracy': 0.40090704300035956, 'eval_overall_accuracy': 0.6225916336859689, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7351195181686112, 'eval_accuracy_RV': 0.49490168634167603, 'eval_accuracy_RA': 0.6483258415178391, 'eval_accuracy_LA': 0.6695418464726021, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.031047048636166835, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4380593244803695, 'eval_accuracy_VSD': 0.42363630911326355, 'eval_accuracy_AK': 0.5684388552730673, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7052619001453152, 'eval_iou_RV': 0.4735118689264077, 'eval_iou_RA': 0.5954122660737446, 'eval_iou_LA': 0.6098198036351707, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.030408509435295782, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.37036359060018764, 'eval_iou_VSD': 0.38330778309885905, 'eval_iou_AK': 0.5326440725396796, 'eval_runtime': 4.6585, 'eval_samples_per_second': 17.388, 'eval_steps_per_second': 8.801, 'epoch': 13.25}\n",
+      "{'loss': 0.1816, 'learning_rate': 4.6975000000000003e-05, 'epoch': 13.26}\n",
+      "{'loss': 0.1429, 'learning_rate': 4.695e-05, 'epoch': 13.26}\n",
+      "{'loss': 0.0242, 'learning_rate': 4.6925e-05, 'epoch': 13.27}\n",
+      "{'loss': 0.1523, 'learning_rate': 4.69e-05, 'epoch': 13.28}\n",
+      "{'loss': 0.1875, 'learning_rate': 4.6875e-05, 'epoch': 13.28}\n",
+      "{'loss': 0.1519, 'learning_rate': 4.685000000000001e-05, 'epoch': 13.29}\n",
+      "{'loss': 0.0643, 'learning_rate': 4.6825e-05, 'epoch': 13.29}\n",
+      "{'loss': 0.2515, 'learning_rate': 4.6800000000000006e-05, 'epoch': 13.3}\n",
+      "{'loss': 0.1544, 'learning_rate': 4.6775000000000005e-05, 'epoch': 13.31}\n",
+      "{'loss': 0.0802, 'learning_rate': 4.6750000000000005e-05, 'epoch': 13.31}\n",
+      "{'loss': 0.3865, 'learning_rate': 4.6725000000000004e-05, 'epoch': 13.32}\n",
+      "{'loss': 0.0918, 'learning_rate': 4.6700000000000003e-05, 'epoch': 13.32}\n",
+      "{'loss': 0.1838, 'learning_rate': 4.6675e-05, 'epoch': 13.33}\n",
+      "{'loss': 0.1462, 'learning_rate': 4.665e-05, 'epoch': 13.34}\n",
+      "{'loss': 0.195, 'learning_rate': 4.6625e-05, 'epoch': 13.34}\n",
+      "{'loss': 0.0072, 'learning_rate': 4.660000000000001e-05, 'epoch': 13.35}\n",
+      "{'loss': 0.0605, 'learning_rate': 4.6575e-05, 'epoch': 13.36}\n",
+      "{'loss': 0.2393, 'learning_rate': 4.655000000000001e-05, 'epoch': 13.36}\n",
+      "{'loss': 0.2923, 'learning_rate': 4.6525e-05, 'epoch': 13.37}\n",
+      "{'loss': 0.1754, 'learning_rate': 4.6500000000000005e-05, 'epoch': 13.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3851158e06e4492fa3900d2f55d7fe86",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.37763381004333496, 'eval_mean_iou': 0.2897464081211321, 'eval_mean_accuracy': 0.3379642124270666, 'eval_overall_accuracy': 0.5583647452389865, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7048156290924494, 'eval_accuracy_RV': 0.4232521163680117, 'eval_accuracy_RA': 0.5595841437137347, 'eval_accuracy_LA': 0.6023607461631871, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.030036801847308413, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.29167869515011546, 'eval_accuracy_VSD': 0.3185443967973131, 'eval_accuracy_AK': 0.44936959513854624, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6745868933667387, 'eval_iou_RV': 0.41542044249493876, 'eval_iou_RA': 0.5321056387746332, 'eval_iou_LA': 0.5669064841105474, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.029194648524486683, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.25225084650553153, 'eval_iou_VSD': 0.29431730023273855, 'eval_iou_AK': 0.4224282353228381, 'eval_runtime': 4.4819, 'eval_samples_per_second': 18.073, 'eval_steps_per_second': 9.148, 'epoch': 13.38}\n",
+      "{'loss': 0.1339, 'learning_rate': 4.6475000000000005e-05, 'epoch': 13.38}\n",
+      "{'loss': 0.0963, 'learning_rate': 4.6450000000000004e-05, 'epoch': 13.39}\n",
+      "{'loss': 0.1714, 'learning_rate': 4.6425000000000004e-05, 'epoch': 13.39}\n",
+      "{'loss': 0.0931, 'learning_rate': 4.64e-05, 'epoch': 13.4}\n",
+      "{'loss': 0.0793, 'learning_rate': 4.6375e-05, 'epoch': 13.41}\n",
+      "{'loss': 0.1186, 'learning_rate': 4.635e-05, 'epoch': 13.41}\n",
+      "{'loss': 0.0961, 'learning_rate': 4.6325e-05, 'epoch': 13.42}\n",
+      "{'loss': 0.1677, 'learning_rate': 4.630000000000001e-05, 'epoch': 13.43}\n",
+      "{'loss': 0.1833, 'learning_rate': 4.6275e-05, 'epoch': 13.43}\n",
+      "{'loss': 0.1561, 'learning_rate': 4.6250000000000006e-05, 'epoch': 13.44}\n",
+      "{'loss': 0.0518, 'learning_rate': 4.6225e-05, 'epoch': 13.44}\n",
+      "{'loss': 0.1748, 'learning_rate': 4.6200000000000005e-05, 'epoch': 13.45}\n",
+      "{'loss': 0.1333, 'learning_rate': 4.6175000000000004e-05, 'epoch': 13.46}\n",
+      "{'loss': 0.0751, 'learning_rate': 4.6150000000000004e-05, 'epoch': 13.46}\n",
+      "{'loss': 0.2457, 'learning_rate': 4.6125e-05, 'epoch': 13.47}\n",
+      "{'loss': 0.1198, 'learning_rate': 4.61e-05, 'epoch': 13.47}\n",
+      "{'loss': 0.1633, 'learning_rate': 4.6075e-05, 'epoch': 13.48}\n",
+      "{'loss': 0.2255, 'learning_rate': 4.605e-05, 'epoch': 13.49}\n",
+      "{'loss': 0.2477, 'learning_rate': 4.6025e-05, 'epoch': 13.49}\n",
+      "{'loss': 0.1339, 'learning_rate': 4.600000000000001e-05, 'epoch': 13.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "05824f44a2784a53984e491c3f90f954",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3513140380382538, 'eval_mean_iou': 0.3435673273780436, 'eval_mean_accuracy': 0.4106585593339386, 'eval_overall_accuracy': 0.6499784155849214, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.8092616512688644, 'eval_accuracy_RV': 0.5046747331135626, 'eval_accuracy_RA': 0.595439945768402, 'eval_accuracy_LA': 0.6996909281759617, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.04118559676721027, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4561471564665127, 'eval_accuracy_VSD': 0.42914654991453505, 'eval_accuracy_AK': 0.5710390318643364, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7565544167886774, 'eval_iou_RV': 0.4922356575965416, 'eval_iou_RA': 0.5600293742599508, 'eval_iou_LA': 0.6409231165631835, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.03966158229387443, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.372938486502434, 'eval_iou_VSD': 0.3817523408114813, 'eval_iou_AK': 0.535145626342336, 'eval_runtime': 4.5475, 'eval_samples_per_second': 17.812, 'eval_steps_per_second': 9.016, 'epoch': 13.5}\n",
+      "{'loss': 0.0779, 'learning_rate': 4.5975e-05, 'epoch': 13.51}\n",
+      "{'loss': 0.1089, 'learning_rate': 4.5950000000000006e-05, 'epoch': 13.51}\n",
+      "{'loss': 0.2149, 'learning_rate': 4.5925e-05, 'epoch': 13.52}\n",
+      "{'loss': 0.3398, 'learning_rate': 4.5900000000000004e-05, 'epoch': 13.53}\n",
+      "{'loss': 0.1609, 'learning_rate': 4.5875000000000004e-05, 'epoch': 13.53}\n",
+      "{'loss': 0.3715, 'learning_rate': 4.585e-05, 'epoch': 13.54}\n",
+      "{'loss': 0.3454, 'learning_rate': 4.5825e-05, 'epoch': 13.54}\n",
+      "{'loss': 0.1036, 'learning_rate': 4.58e-05, 'epoch': 13.55}\n",
+      "{'loss': 0.1902, 'learning_rate': 4.5775e-05, 'epoch': 13.56}\n",
+      "{'loss': 0.184, 'learning_rate': 4.575e-05, 'epoch': 13.56}\n",
+      "{'loss': 0.1658, 'learning_rate': 4.5725e-05, 'epoch': 13.57}\n",
+      "{'loss': 0.1058, 'learning_rate': 4.5700000000000006e-05, 'epoch': 13.57}\n",
+      "{'loss': 0.1385, 'learning_rate': 4.5675e-05, 'epoch': 13.58}\n",
+      "{'loss': 0.0702, 'learning_rate': 4.5650000000000005e-05, 'epoch': 13.59}\n",
+      "{'loss': 0.1375, 'learning_rate': 4.5625e-05, 'epoch': 13.59}\n",
+      "{'loss': 0.0922, 'learning_rate': 4.5600000000000004e-05, 'epoch': 13.6}\n",
+      "{'loss': 0.1689, 'learning_rate': 4.5575e-05, 'epoch': 13.61}\n",
+      "{'loss': 0.1661, 'learning_rate': 4.555e-05, 'epoch': 13.61}\n",
+      "{'loss': 0.1603, 'learning_rate': 4.5525e-05, 'epoch': 13.62}\n",
+      "{'loss': 0.1873, 'learning_rate': 4.55e-05, 'epoch': 13.62}\n"
+     ]
+    },
+    {
+     "data": {
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+       "model_id": "19bfffbdc2b449f99743a60d5c042fd3",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.35521477460861206, 'eval_mean_iou': 0.30403473970438644, 'eval_mean_accuracy': 0.3572992999278645, 'eval_overall_accuracy': 0.5648887564131138, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6820739154169936, 'eval_accuracy_RV': 0.4740403445121764, 'eval_accuracy_RA': 0.5655742335348188, 'eval_accuracy_LA': 0.6145846911682984, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.05949631981526916, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4027406899538106, 'eval_accuracy_VSD': 0.34455123399406246, 'eval_accuracy_AK': 0.42993157088321604, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6549040359810471, 'eval_iou_RV': 0.4615011086341985, 'eval_iou_RA': 0.5368602081346402, 'eval_iou_LA': 0.574820050403533, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.057095372470266435, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3396325459317585, 'eval_iou_VSD': 0.31524542486350043, 'eval_iou_AK': 0.4043233903293067, 'eval_runtime': 4.5965, 'eval_samples_per_second': 17.622, 'eval_steps_per_second': 8.92, 'epoch': 13.62}\n",
+      "{'loss': 0.2105, 'learning_rate': 4.5475e-05, 'epoch': 13.63}\n",
+      "{'loss': 0.2001, 'learning_rate': 4.545000000000001e-05, 'epoch': 13.64}\n",
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+      "{'loss': 0.1654, 'learning_rate': 4.5400000000000006e-05, 'epoch': 13.65}\n",
+      "{'loss': 0.1819, 'learning_rate': 4.5375e-05, 'epoch': 13.66}\n",
+      "{'loss': 0.1969, 'learning_rate': 4.5350000000000005e-05, 'epoch': 13.66}\n",
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+      "{'loss': 0.1762, 'learning_rate': 4.53e-05, 'epoch': 13.68}\n",
+      "{'loss': 0.1938, 'learning_rate': 4.5275e-05, 'epoch': 13.68}\n",
+      "{'loss': 0.206, 'learning_rate': 4.525e-05, 'epoch': 13.69}\n",
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+      "{'loss': 0.1296, 'learning_rate': 4.52e-05, 'epoch': 13.7}\n",
+      "{'loss': 0.2214, 'learning_rate': 4.5175e-05, 'epoch': 13.71}\n",
+      "{'loss': 0.1777, 'learning_rate': 4.5150000000000006e-05, 'epoch': 13.71}\n",
+      "{'loss': 0.2058, 'learning_rate': 4.5125e-05, 'epoch': 13.72}\n",
+      "{'loss': 0.1107, 'learning_rate': 4.5100000000000005e-05, 'epoch': 13.72}\n",
+      "{'loss': 0.1022, 'learning_rate': 4.5075e-05, 'epoch': 13.73}\n",
+      "{'loss': 0.0738, 'learning_rate': 4.5050000000000004e-05, 'epoch': 13.74}\n",
+      "{'loss': 0.1575, 'learning_rate': 4.5025000000000003e-05, 'epoch': 13.74}\n",
+      "{'loss': 0.185, 'learning_rate': 4.5e-05, 'epoch': 13.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "727e708565734290987f2428c5dba0f3",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.34952178597450256, 'eval_mean_iou': 0.3441817169231985, 'eval_mean_accuracy': 0.41084059534167167, 'eval_overall_accuracy': 0.6517589945882083, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7800615116594725, 'eval_accuracy_RV': 0.5084516596376851, 'eval_accuracy_RA': 0.6541000540701944, 'eval_accuracy_LA': 0.7220223108007052, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.04488382161928128, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.39920431581986143, 'eval_accuracy_VSD': 0.3865340210513689, 'eval_accuracy_AK': 0.6131482587581478, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7337590091322471, 'eval_iou_RV': 0.49171522457351663, 'eval_iou_RA': 0.6016650335530613, 'eval_iou_LA': 0.6608348246522873, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.04318994549178905, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3380777752311101, 'eval_iou_VSD': 0.3502268775133138, 'eval_iou_AK': 0.5665301960078583, 'eval_runtime': 4.5969, 'eval_samples_per_second': 17.621, 'eval_steps_per_second': 8.919, 'epoch': 13.75}\n",
+      "{'loss': 0.1504, 'learning_rate': 4.4975e-05, 'epoch': 13.76}\n",
+      "{'loss': 0.056, 'learning_rate': 4.495e-05, 'epoch': 13.76}\n",
+      "{'loss': 0.0705, 'learning_rate': 4.4925e-05, 'epoch': 13.77}\n",
+      "{'loss': 0.1039, 'learning_rate': 4.49e-05, 'epoch': 13.78}\n",
+      "{'loss': 0.1901, 'learning_rate': 4.4875e-05, 'epoch': 13.78}\n",
+      "{'loss': 0.165, 'learning_rate': 4.4850000000000006e-05, 'epoch': 13.79}\n",
+      "{'loss': 0.1757, 'learning_rate': 4.4825e-05, 'epoch': 13.79}\n",
+      "{'loss': 0.0796, 'learning_rate': 4.4800000000000005e-05, 'epoch': 13.8}\n",
+      "{'loss': 0.1372, 'learning_rate': 4.4775e-05, 'epoch': 13.81}\n",
+      "{'loss': 0.133, 'learning_rate': 4.4750000000000004e-05, 'epoch': 13.81}\n",
+      "{'loss': 0.3217, 'learning_rate': 4.4725e-05, 'epoch': 13.82}\n",
+      "{'loss': 0.1602, 'learning_rate': 4.47e-05, 'epoch': 13.82}\n",
+      "{'loss': 0.0206, 'learning_rate': 4.4675e-05, 'epoch': 13.83}\n",
+      "{'loss': 0.1692, 'learning_rate': 4.465e-05, 'epoch': 13.84}\n",
+      "{'loss': 0.2036, 'learning_rate': 4.4625e-05, 'epoch': 13.84}\n",
+      "{'loss': 0.0938, 'learning_rate': 4.46e-05, 'epoch': 13.85}\n",
+      "{'loss': 0.0147, 'learning_rate': 4.4575e-05, 'epoch': 13.86}\n",
+      "{'loss': 0.1252, 'learning_rate': 4.4550000000000005e-05, 'epoch': 13.86}\n",
+      "{'loss': 0.0863, 'learning_rate': 4.4525e-05, 'epoch': 13.87}\n",
+      "{'loss': 0.1486, 'learning_rate': 4.4500000000000004e-05, 'epoch': 13.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f97095030e7a415cbacd99fc4b50dbeb",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3768700063228607, 'eval_mean_iou': 0.28693205551756523, 'eval_mean_accuracy': 0.3315957274532405, 'eval_overall_accuracy': 0.5356299728003913, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6510906237974351, 'eval_accuracy_RV': 0.4486792267506461, 'eval_accuracy_RA': 0.4593827927658922, 'eval_accuracy_LA': 0.6251277794167084, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.028034348390821185, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3055535508083141, 'eval_accuracy_VSD': 0.3352250577263322, 'eval_accuracy_AK': 0.4628638948762563, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6382217978962236, 'eval_iou_RV': 0.43903391334773983, 'eval_iou_RA': 0.4462322075651777, 'eval_iou_LA': 0.5886061639632307, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.02714220840465295, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.27049474903166554, 'eval_iou_VSD': 0.3094313770267184, 'eval_iou_AK': 0.43709019345780925, 'eval_runtime': 4.6534, 'eval_samples_per_second': 17.407, 'eval_steps_per_second': 8.811, 'epoch': 13.88}\n",
+      "{'loss': 0.0904, 'learning_rate': 4.4475e-05, 'epoch': 13.88}\n",
+      "{'loss': 0.1909, 'learning_rate': 4.445e-05, 'epoch': 13.89}\n",
+      "{'loss': 0.0679, 'learning_rate': 4.4425e-05, 'epoch': 13.89}\n",
+      "{'loss': 0.1701, 'learning_rate': 4.44e-05, 'epoch': 13.9}\n",
+      "{'loss': 0.3985, 'learning_rate': 4.4375e-05, 'epoch': 13.91}\n",
+      "{'loss': 0.3387, 'learning_rate': 4.435e-05, 'epoch': 13.91}\n",
+      "{'loss': 0.215, 'learning_rate': 4.4325e-05, 'epoch': 13.92}\n",
+      "{'loss': 0.1622, 'learning_rate': 4.43e-05, 'epoch': 13.93}\n",
+      "{'loss': 0.1047, 'learning_rate': 4.4275e-05, 'epoch': 13.93}\n",
+      "{'loss': 0.1865, 'learning_rate': 4.4250000000000005e-05, 'epoch': 13.94}\n",
+      "{'loss': 0.1524, 'learning_rate': 4.4225e-05, 'epoch': 13.94}\n",
+      "{'loss': 0.1106, 'learning_rate': 4.4200000000000004e-05, 'epoch': 13.95}\n",
+      "{'loss': 0.0239, 'learning_rate': 4.4174999999999996e-05, 'epoch': 13.96}\n",
+      "{'loss': 0.2571, 'learning_rate': 4.415e-05, 'epoch': 13.96}\n",
+      "{'loss': 0.1489, 'learning_rate': 4.4125e-05, 'epoch': 13.97}\n",
+      "{'loss': 0.1539, 'learning_rate': 4.41e-05, 'epoch': 13.97}\n",
+      "{'loss': 0.1853, 'learning_rate': 4.4075e-05, 'epoch': 13.98}\n",
+      "{'loss': 0.2369, 'learning_rate': 4.405e-05, 'epoch': 13.99}\n",
+      "{'loss': 0.2318, 'learning_rate': 4.4025e-05, 'epoch': 13.99}\n",
+      "{'loss': 0.1611, 'learning_rate': 4.4000000000000006e-05, 'epoch': 14.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "5db88eb4008446d3aaf78ec386c23c63",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3629535436630249, 'eval_mean_iou': 0.31902312578866504, 'eval_mean_accuracy': 0.3806276084501896, 'eval_overall_accuracy': 0.597738721466918, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7466231232530182, 'eval_accuracy_RV': 0.46676887849377213, 'eval_accuracy_RA': 0.580806695019893, 'eval_accuracy_LA': 0.6181385025967522, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0424484052532833, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4921694572748268, 'eval_accuracy_VSD': 0.37369178636758926, 'eval_accuracy_AK': 0.48562923624276105, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7109445126177409, 'eval_iou_RV': 0.45388488607398475, 'eval_iou_RA': 0.5330373228705114, 'eval_iou_LA': 0.5759772036425588, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.04059696342305038, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.38758169934640524, 'eval_iou_VSD': 0.3412707106668492, 'eval_iou_AK': 0.4659610850342149, 'eval_runtime': 4.5818, 'eval_samples_per_second': 17.679, 'eval_steps_per_second': 8.948, 'epoch': 14.0}\n",
+      "{'loss': 0.2389, 'learning_rate': 4.3975e-05, 'epoch': 14.01}\n",
+      "{'loss': 0.2119, 'learning_rate': 4.3950000000000004e-05, 'epoch': 14.01}\n",
+      "{'loss': 0.1629, 'learning_rate': 4.3925e-05, 'epoch': 14.02}\n",
+      "{'loss': 0.0674, 'learning_rate': 4.39e-05, 'epoch': 14.03}\n",
+      "{'loss': 0.0838, 'learning_rate': 4.3875e-05, 'epoch': 14.03}\n",
+      "{'loss': 0.0673, 'learning_rate': 4.385e-05, 'epoch': 14.04}\n",
+      "{'loss': 0.1219, 'learning_rate': 4.3825e-05, 'epoch': 14.04}\n",
+      "{'loss': 0.1958, 'learning_rate': 4.38e-05, 'epoch': 14.05}\n",
+      "{'loss': 0.1221, 'learning_rate': 4.3775e-05, 'epoch': 14.06}\n",
+      "{'loss': 0.0506, 'learning_rate': 4.375e-05, 'epoch': 14.06}\n",
+      "{'loss': 0.1876, 'learning_rate': 4.3725000000000006e-05, 'epoch': 14.07}\n",
+      "{'loss': 0.1376, 'learning_rate': 4.3700000000000005e-05, 'epoch': 14.07}\n",
+      "{'loss': 0.3647, 'learning_rate': 4.3675000000000005e-05, 'epoch': 14.08}\n",
+      "{'loss': 0.1216, 'learning_rate': 4.3650000000000004e-05, 'epoch': 14.09}\n",
+      "{'loss': 0.13, 'learning_rate': 4.3625e-05, 'epoch': 14.09}\n",
+      "{'loss': 0.1418, 'learning_rate': 4.36e-05, 'epoch': 14.1}\n",
+      "{'loss': 0.1124, 'learning_rate': 4.3575e-05, 'epoch': 14.11}\n",
+      "{'loss': 0.2331, 'learning_rate': 4.355e-05, 'epoch': 14.11}\n",
+      "{'loss': 0.1644, 'learning_rate': 4.352500000000001e-05, 'epoch': 14.12}\n",
+      "{'loss': 0.0573, 'learning_rate': 4.35e-05, 'epoch': 14.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2f02840f35b1493e97d6ab8da8a522bc",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.37233927845954895, 'eval_mean_iou': 0.320702018972036, 'eval_mean_accuracy': 0.3795258989012774, 'eval_overall_accuracy': 0.5851567385570142, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7035425883223306, 'eval_accuracy_RV': 0.47667084108362956, 'eval_accuracy_RA': 0.5875452938755417, 'eval_accuracy_LA': 0.6047276669022154, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.04937581180545533, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4646994081986143, 'eval_accuracy_VSD': 0.3924341020181725, 'eval_accuracy_AK': 0.5162632768068144, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6750211085192552, 'eval_iou_RV': 0.464150791136403, 'eval_iou_RA': 0.550068848798971, 'eval_iou_LA': 0.5668219656413076, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.047121410371186556, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.37731744299328296, 'eval_iou_VSD': 0.35704492902891366, 'eval_iou_AK': 0.4901757122030754, 'eval_runtime': 4.5297, 'eval_samples_per_second': 17.882, 'eval_steps_per_second': 9.051, 'epoch': 14.12}\n",
+      "{'loss': 0.0657, 'learning_rate': 4.3475000000000006e-05, 'epoch': 14.13}\n",
+      "{'loss': 0.1525, 'learning_rate': 4.345e-05, 'epoch': 14.14}\n",
+      "{'loss': 0.2278, 'learning_rate': 4.3425000000000005e-05, 'epoch': 14.14}\n",
+      "{'loss': 0.1539, 'learning_rate': 4.3400000000000005e-05, 'epoch': 14.15}\n",
+      "{'loss': 0.1195, 'learning_rate': 4.3375000000000004e-05, 'epoch': 14.16}\n",
+      "{'loss': 0.1408, 'learning_rate': 4.335e-05, 'epoch': 14.16}\n",
+      "{'loss': 0.2122, 'learning_rate': 4.3325e-05, 'epoch': 14.17}\n",
+      "{'loss': 0.1054, 'learning_rate': 4.33e-05, 'epoch': 14.18}\n",
+      "{'loss': 0.1228, 'learning_rate': 4.3275e-05, 'epoch': 14.18}\n",
+      "{'loss': 0.1925, 'learning_rate': 4.325e-05, 'epoch': 14.19}\n",
+      "{'loss': 0.066, 'learning_rate': 4.322500000000001e-05, 'epoch': 14.19}\n",
+      "{'loss': 0.0759, 'learning_rate': 4.32e-05, 'epoch': 14.2}\n",
+      "{'loss': 0.0173, 'learning_rate': 4.3175000000000006e-05, 'epoch': 14.21}\n",
+      "{'loss': 0.1063, 'learning_rate': 4.315e-05, 'epoch': 14.21}\n",
+      "{'loss': 0.143, 'learning_rate': 4.3125000000000005e-05, 'epoch': 14.22}\n",
+      "{'loss': 0.4395, 'learning_rate': 4.3100000000000004e-05, 'epoch': 14.22}\n",
+      "{'loss': 0.1522, 'learning_rate': 4.3075000000000003e-05, 'epoch': 14.23}\n",
+      "{'loss': 0.0829, 'learning_rate': 4.305e-05, 'epoch': 14.24}\n",
+      "{'loss': 0.0788, 'learning_rate': 4.3025e-05, 'epoch': 14.24}\n",
+      "{'loss': 0.0901, 'learning_rate': 4.3e-05, 'epoch': 14.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "d749da3f5cb34f2aa4e120341b874377",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.37828779220581055, 'eval_mean_iou': 0.30088219495553054, 'eval_mean_accuracy': 0.3538740972095752, 'eval_overall_accuracy': 0.5510417320330031, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6806800588268634, 'eval_accuracy_RV': 0.3843533030074219, 'eval_accuracy_RA': 0.5357085213012356, 'eval_accuracy_LA': 0.6217043201448967, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.04363905325443787, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.38326356812933027, 'eval_accuracy_VSD': 0.41665667076498636, 'eval_accuracy_AK': 0.4727354766665801, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6524677541689214, 'eval_iou_RV': 0.37562544245929375, 'eval_iou_RA': 0.5134708132379844, 'eval_iou_LA': 0.5807932959998718, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.04236724113773294, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.32902216508418397, 'eval_iou_VSD': 0.3723452720719272, 'eval_iou_AK': 0.44361216035091994, 'eval_runtime': 4.6146, 'eval_samples_per_second': 17.553, 'eval_steps_per_second': 8.885, 'epoch': 14.25}\n",
+      "{'loss': 0.1419, 'learning_rate': 4.2975e-05, 'epoch': 14.26}\n",
+      "{'loss': 0.2143, 'learning_rate': 4.295e-05, 'epoch': 14.26}\n",
+      "{'loss': 0.0621, 'learning_rate': 4.2925000000000007e-05, 'epoch': 14.27}\n",
+      "{'loss': 0.0776, 'learning_rate': 4.29e-05, 'epoch': 14.28}\n",
+      "{'loss': 0.2014, 'learning_rate': 4.2875000000000005e-05, 'epoch': 14.28}\n",
+      "{'loss': 0.1008, 'learning_rate': 4.285e-05, 'epoch': 14.29}\n",
+      "{'loss': 0.2119, 'learning_rate': 4.2825000000000004e-05, 'epoch': 14.29}\n",
+      "{'loss': 0.0468, 'learning_rate': 4.2800000000000004e-05, 'epoch': 14.3}\n",
+      "{'loss': 0.0346, 'learning_rate': 4.2775e-05, 'epoch': 14.31}\n",
+      "{'loss': 0.1593, 'learning_rate': 4.275e-05, 'epoch': 14.31}\n",
+      "{'loss': 0.2419, 'learning_rate': 4.2725e-05, 'epoch': 14.32}\n",
+      "{'loss': 0.1174, 'learning_rate': 4.27e-05, 'epoch': 14.32}\n",
+      "{'loss': 0.0069, 'learning_rate': 4.2675e-05, 'epoch': 14.33}\n",
+      "{'loss': 0.1552, 'learning_rate': 4.265e-05, 'epoch': 14.34}\n",
+      "{'loss': 0.1617, 'learning_rate': 4.2625000000000006e-05, 'epoch': 14.34}\n",
+      "{'loss': 0.0352, 'learning_rate': 4.26e-05, 'epoch': 14.35}\n",
+      "{'loss': 0.1758, 'learning_rate': 4.2575000000000005e-05, 'epoch': 14.36}\n",
+      "{'loss': 0.1572, 'learning_rate': 4.2550000000000004e-05, 'epoch': 14.36}\n",
+      "{'loss': 0.1702, 'learning_rate': 4.2525000000000004e-05, 'epoch': 14.37}\n",
+      "{'loss': 0.1414, 'learning_rate': 4.25e-05, 'epoch': 14.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "153a371ecf2542a3ae4adc7c55eb2182",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.36066362261772156, 'eval_mean_iou': 0.325860201413036, 'eval_mean_accuracy': 0.3873414364458378, 'eval_overall_accuracy': 0.6222256723626441, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7665838357382145, 'eval_accuracy_RV': 0.5181249501218561, 'eval_accuracy_RA': 0.5788113434425767, 'eval_accuracy_LA': 0.6607619426587723, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.03644104488382162, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4555517465357968, 'eval_accuracy_VSD': 0.3078237922451795, 'eval_accuracy_AK': 0.5493157088321604, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.724264954566977, 'eval_iou_RV': 0.500382396708424, 'eval_iou_RA': 0.5407633179146734, 'eval_iou_LA': 0.611253468812028, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.03527213675810648, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3776549599138447, 'eval_iou_VSD': 0.28563080861483664, 'eval_iou_AK': 0.5092401722545057, 'eval_runtime': 4.6799, 'eval_samples_per_second': 17.308, 'eval_steps_per_second': 8.761, 'epoch': 14.38}\n",
+      "{'loss': 0.1583, 'learning_rate': 4.2475e-05, 'epoch': 14.38}\n",
+      "{'loss': 0.1246, 'learning_rate': 4.245e-05, 'epoch': 14.39}\n",
+      "{'loss': 0.1081, 'learning_rate': 4.2425e-05, 'epoch': 14.39}\n",
+      "{'loss': 0.1513, 'learning_rate': 4.24e-05, 'epoch': 14.4}\n",
+      "{'loss': 0.1566, 'learning_rate': 4.237500000000001e-05, 'epoch': 14.41}\n",
+      "{'loss': 0.0826, 'learning_rate': 4.235e-05, 'epoch': 14.41}\n",
+      "{'loss': 0.1932, 'learning_rate': 4.2325000000000006e-05, 'epoch': 14.42}\n",
+      "{'loss': 0.1416, 'learning_rate': 4.23e-05, 'epoch': 14.43}\n",
+      "{'loss': 0.0647, 'learning_rate': 4.2275000000000004e-05, 'epoch': 14.43}\n",
+      "{'loss': 0.1626, 'learning_rate': 4.2250000000000004e-05, 'epoch': 14.44}\n",
+      "{'loss': 0.1623, 'learning_rate': 4.2225e-05, 'epoch': 14.44}\n",
+      "{'loss': 0.1329, 'learning_rate': 4.22e-05, 'epoch': 14.45}\n",
+      "{'loss': 0.2356, 'learning_rate': 4.2175e-05, 'epoch': 14.46}\n",
+      "{'loss': 0.0625, 'learning_rate': 4.215e-05, 'epoch': 14.46}\n",
+      "{'loss': 0.1504, 'learning_rate': 4.2125e-05, 'epoch': 14.47}\n",
+      "{'loss': 0.1601, 'learning_rate': 4.21e-05, 'epoch': 14.47}\n",
+      "{'loss': 0.1897, 'learning_rate': 4.2075000000000006e-05, 'epoch': 14.48}\n",
+      "{'loss': 0.1761, 'learning_rate': 4.205e-05, 'epoch': 14.49}\n",
+      "{'loss': 0.129, 'learning_rate': 4.2025000000000005e-05, 'epoch': 14.49}\n",
+      "{'loss': 0.2247, 'learning_rate': 4.2e-05, 'epoch': 14.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "fb328a215ac243e090978d3db2ff8781",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.35568779706954956, 'eval_mean_iou': 0.3244325500782414, 'eval_mean_accuracy': 0.3887769185843979, 'eval_overall_accuracy': 0.608702684690104, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7230856658741547, 'eval_accuracy_RV': 0.5043355617353297, 'eval_accuracy_RA': 0.6481180344273805, 'eval_accuracy_LA': 0.6203990834185196, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.041492278828113724, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.46386944284064663, 'eval_accuracy_VSD': 0.329242510570666, 'eval_accuracy_AK': 0.5572266081491677, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6936761169694069, 'eval_iou_RV': 0.4877505402645515, 'eval_iou_RA': 0.5695671522972151, 'eval_iou_LA': 0.5814465636277417, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.040122810690112344, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.384481366273853, 'eval_iou_VSD': 0.30246492696130084, 'eval_iou_AK': 0.5092485737764738, 'eval_runtime': 4.756, 'eval_samples_per_second': 17.031, 'eval_steps_per_second': 8.621, 'epoch': 14.5}\n",
+      "{'loss': 0.115, 'learning_rate': 4.1975000000000004e-05, 'epoch': 14.51}\n",
+      "{'loss': 0.2631, 'learning_rate': 4.195e-05, 'epoch': 14.51}\n",
+      "{'loss': 0.2001, 'learning_rate': 4.1925e-05, 'epoch': 14.52}\n",
+      "{'loss': 0.1306, 'learning_rate': 4.19e-05, 'epoch': 14.53}\n",
+      "{'loss': 0.1799, 'learning_rate': 4.1875e-05, 'epoch': 14.53}\n",
+      "{'loss': 0.115, 'learning_rate': 4.185e-05, 'epoch': 14.54}\n",
+      "{'loss': 0.0815, 'learning_rate': 4.1825e-05, 'epoch': 14.54}\n",
+      "{'loss': 0.1855, 'learning_rate': 4.18e-05, 'epoch': 14.55}\n",
+      "{'loss': 0.1442, 'learning_rate': 4.1775000000000006e-05, 'epoch': 14.56}\n",
+      "{'loss': 0.0718, 'learning_rate': 4.175e-05, 'epoch': 14.56}\n",
+      "{'loss': 0.0761, 'learning_rate': 4.1725000000000005e-05, 'epoch': 14.57}\n",
+      "{'loss': 0.1697, 'learning_rate': 4.17e-05, 'epoch': 14.57}\n",
+      "{'loss': 0.1375, 'learning_rate': 4.1675e-05, 'epoch': 14.58}\n",
+      "{'loss': 0.2512, 'learning_rate': 4.165e-05, 'epoch': 14.59}\n",
+      "{'loss': 0.049, 'learning_rate': 4.1625e-05, 'epoch': 14.59}\n",
+      "{'loss': 0.267, 'learning_rate': 4.16e-05, 'epoch': 14.6}\n",
+      "{'loss': 0.1504, 'learning_rate': 4.1575e-05, 'epoch': 14.61}\n",
+      "{'loss': 0.0859, 'learning_rate': 4.155e-05, 'epoch': 14.61}\n",
+      "{'loss': 0.2383, 'learning_rate': 4.1525e-05, 'epoch': 14.62}\n",
+      "{'loss': 0.138, 'learning_rate': 4.15e-05, 'epoch': 14.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "5cc3f95d05f94192b7f77ad85f4667be",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3722497820854187, 'eval_mean_iou': 0.3127835000576604, 'eval_mean_accuracy': 0.37136385453634946, 'eval_overall_accuracy': 0.5884622916481838, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7468490935830393, 'eval_accuracy_RV': 0.3869807301546376, 'eval_accuracy_RA': 0.5623300218701831, 'eval_accuracy_LA': 0.6803404935544289, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.05215399047481599, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.44964275404157045, 'eval_accuracy_VSD': 0.3631286172669206, 'eval_accuracy_AK': 0.47221284441789807, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7013583312030983, 'eval_iou_RV': 0.3793887398495698, 'eval_iou_RA': 0.5319449427823285, 'eval_iou_LA': 0.6308946115270283, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.05044406832894209, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3691043062909616, 'eval_iou_VSD': 0.3308063734027223, 'eval_iou_AK': 0.4466771272496139, 'eval_runtime': 4.6793, 'eval_samples_per_second': 17.31, 'eval_steps_per_second': 8.762, 'epoch': 14.62}\n",
+      "{'loss': 0.2935, 'learning_rate': 4.1475000000000005e-05, 'epoch': 14.63}\n",
+      "{'loss': 0.2827, 'learning_rate': 4.145e-05, 'epoch': 14.64}\n",
+      "{'loss': 0.0879, 'learning_rate': 4.1425000000000004e-05, 'epoch': 14.64}\n",
+      "{'loss': 0.1285, 'learning_rate': 4.14e-05, 'epoch': 14.65}\n",
+      "{'loss': 0.1565, 'learning_rate': 4.1375e-05, 'epoch': 14.66}\n",
+      "{'loss': 0.2474, 'learning_rate': 4.135e-05, 'epoch': 14.66}\n",
+      "{'loss': 0.0074, 'learning_rate': 4.1325e-05, 'epoch': 14.67}\n",
+      "{'loss': 0.2141, 'learning_rate': 4.13e-05, 'epoch': 14.68}\n",
+      "{'loss': 0.155, 'learning_rate': 4.1275e-05, 'epoch': 14.68}\n",
+      "{'loss': 0.4291, 'learning_rate': 4.125e-05, 'epoch': 14.69}\n",
+      "{'loss': 0.1817, 'learning_rate': 4.1225e-05, 'epoch': 14.69}\n",
+      "{'loss': 0.1393, 'learning_rate': 4.12e-05, 'epoch': 14.7}\n",
+      "{'loss': 0.132, 'learning_rate': 4.1175000000000005e-05, 'epoch': 14.71}\n",
+      "{'loss': 0.136, 'learning_rate': 4.115e-05, 'epoch': 14.71}\n",
+      "{'loss': 0.1423, 'learning_rate': 4.1125000000000004e-05, 'epoch': 14.72}\n",
+      "{'loss': 0.0901, 'learning_rate': 4.11e-05, 'epoch': 14.72}\n",
+      "{'loss': 0.1653, 'learning_rate': 4.1075e-05, 'epoch': 14.73}\n",
+      "{'loss': 0.137, 'learning_rate': 4.105e-05, 'epoch': 14.74}\n",
+      "{'loss': 0.1262, 'learning_rate': 4.1025e-05, 'epoch': 14.74}\n",
+      "{'loss': 0.1415, 'learning_rate': 4.1e-05, 'epoch': 14.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7d24216bdaed4b2b935e200ae38fe4bd",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.0647, 'learning_rate': 4.0975e-05, 'epoch': 14.76}\n",
+      "{'loss': 0.1438, 'learning_rate': 4.095e-05, 'epoch': 14.76}\n",
+      "{'loss': 0.0192, 'learning_rate': 4.0925000000000005e-05, 'epoch': 14.77}\n",
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+      "{'loss': 0.0827, 'learning_rate': 4.0875000000000004e-05, 'epoch': 14.78}\n",
+      "{'loss': 0.1087, 'learning_rate': 4.085e-05, 'epoch': 14.79}\n",
+      "{'loss': 0.0505, 'learning_rate': 4.0825e-05, 'epoch': 14.79}\n",
+      "{'loss': 0.1992, 'learning_rate': 4.08e-05, 'epoch': 14.8}\n",
+      "{'loss': 0.2151, 'learning_rate': 4.0775e-05, 'epoch': 14.81}\n",
+      "{'loss': 0.1513, 'learning_rate': 4.075e-05, 'epoch': 14.81}\n",
+      "{'loss': 0.2255, 'learning_rate': 4.0725e-05, 'epoch': 14.82}\n",
+      "{'loss': 0.0085, 'learning_rate': 4.07e-05, 'epoch': 14.82}\n",
+      "{'loss': 0.1262, 'learning_rate': 4.0675e-05, 'epoch': 14.83}\n",
+      "{'loss': 0.0406, 'learning_rate': 4.065e-05, 'epoch': 14.84}\n",
+      "{'loss': 0.2132, 'learning_rate': 4.0625000000000005e-05, 'epoch': 14.84}\n",
+      "{'loss': 0.2472, 'learning_rate': 4.0600000000000004e-05, 'epoch': 14.85}\n",
+      "{'loss': 0.1387, 'learning_rate': 4.0575000000000004e-05, 'epoch': 14.86}\n",
+      "{'loss': 0.1582, 'learning_rate': 4.055e-05, 'epoch': 14.86}\n",
+      "{'loss': 0.1757, 'learning_rate': 4.0525e-05, 'epoch': 14.87}\n",
+      "{'loss': 0.1217, 'learning_rate': 4.05e-05, 'epoch': 14.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "742ce8ce9073413ab99d8b098e5140d8",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.1243, 'learning_rate': 4.0475e-05, 'epoch': 14.88}\n",
+      "{'loss': 0.122, 'learning_rate': 4.045000000000001e-05, 'epoch': 14.89}\n",
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+      "{'loss': 0.1786, 'learning_rate': 4.0400000000000006e-05, 'epoch': 14.9}\n",
+      "{'loss': 0.2538, 'learning_rate': 4.0375e-05, 'epoch': 14.91}\n",
+      "{'loss': 0.0841, 'learning_rate': 4.0350000000000005e-05, 'epoch': 14.91}\n",
+      "{'loss': 0.1207, 'learning_rate': 4.0325000000000004e-05, 'epoch': 14.92}\n",
+      "{'loss': 0.1127, 'learning_rate': 4.0300000000000004e-05, 'epoch': 14.93}\n",
+      "{'loss': 0.1747, 'learning_rate': 4.0275e-05, 'epoch': 14.93}\n",
+      "{'loss': 0.2364, 'learning_rate': 4.025e-05, 'epoch': 14.94}\n",
+      "{'loss': 0.1673, 'learning_rate': 4.0225e-05, 'epoch': 14.94}\n",
+      "{'loss': 0.1032, 'learning_rate': 4.02e-05, 'epoch': 14.95}\n",
+      "{'loss': 0.184, 'learning_rate': 4.0175e-05, 'epoch': 14.96}\n",
+      "{'loss': 0.2191, 'learning_rate': 4.015000000000001e-05, 'epoch': 14.96}\n",
+      "{'loss': 0.1139, 'learning_rate': 4.0125e-05, 'epoch': 14.97}\n",
+      "{'loss': 0.1022, 'learning_rate': 4.0100000000000006e-05, 'epoch': 14.97}\n",
+      "{'loss': 0.2099, 'learning_rate': 4.0075e-05, 'epoch': 14.98}\n",
+      "{'loss': 0.1157, 'learning_rate': 4.0050000000000004e-05, 'epoch': 14.99}\n",
+      "{'loss': 0.1022, 'learning_rate': 4.0025000000000004e-05, 'epoch': 14.99}\n",
+      "{'loss': 0.1574, 'learning_rate': 4e-05, 'epoch': 15.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3b87ffa9dc6f460bb89a63c0991f74e8",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.357942670583725, 'eval_mean_iou': 0.33042097056855424, 'eval_mean_accuracy': 0.39321010189156774, 'eval_overall_accuracy': 0.6089369215755432, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7398552000023865, 'eval_accuracy_RV': 0.4310285026734685, 'eval_accuracy_RA': 0.611209074108447, 'eval_accuracy_LA': 0.6766168812903491, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.053597200173185165, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.47290884815242495, 'eval_accuracy_VSD': 0.3786022730680421, 'eval_accuracy_AK': 0.5682830394473732, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7047332191999772, 'eval_iou_RV': 0.42111126604921334, 'eval_iou_RA': 0.5711713512168267, 'eval_iou_LA': 0.6269002056337939, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.051555694379370784, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3897761915384043, 'eval_iou_VSD': 0.346914241749787, 'eval_iou_AK': 0.5224685064867236, 'eval_runtime': 4.5675, 'eval_samples_per_second': 17.734, 'eval_steps_per_second': 8.977, 'epoch': 15.0}\n",
+      "{'loss': 0.1691, 'learning_rate': 3.9975e-05, 'epoch': 15.01}\n",
+      "{'loss': 0.0708, 'learning_rate': 3.995e-05, 'epoch': 15.01}\n",
+      "{'loss': 0.0954, 'learning_rate': 3.9925e-05, 'epoch': 15.02}\n",
+      "{'loss': 0.1471, 'learning_rate': 3.99e-05, 'epoch': 15.03}\n",
+      "{'loss': 0.1264, 'learning_rate': 3.9875e-05, 'epoch': 15.03}\n",
+      "{'loss': 0.1809, 'learning_rate': 3.9850000000000006e-05, 'epoch': 15.04}\n",
+      "{'loss': 0.1516, 'learning_rate': 3.9825e-05, 'epoch': 15.04}\n",
+      "{'loss': 0.0728, 'learning_rate': 3.9800000000000005e-05, 'epoch': 15.05}\n",
+      "{'loss': 0.1618, 'learning_rate': 3.9775e-05, 'epoch': 15.06}\n",
+      "{'loss': 0.2057, 'learning_rate': 3.9750000000000004e-05, 'epoch': 15.06}\n",
+      "{'loss': 0.1628, 'learning_rate': 3.9725e-05, 'epoch': 15.07}\n",
+      "{'loss': 0.1307, 'learning_rate': 3.97e-05, 'epoch': 15.07}\n",
+      "{'loss': 0.214, 'learning_rate': 3.9675e-05, 'epoch': 15.08}\n",
+      "{'loss': 0.1859, 'learning_rate': 3.965e-05, 'epoch': 15.09}\n",
+      "{'loss': 0.0586, 'learning_rate': 3.9625e-05, 'epoch': 15.09}\n",
+      "{'loss': 0.2377, 'learning_rate': 3.960000000000001e-05, 'epoch': 15.1}\n",
+      "{'loss': 0.1259, 'learning_rate': 3.9575e-05, 'epoch': 15.11}\n",
+      "{'loss': 0.1603, 'learning_rate': 3.9550000000000006e-05, 'epoch': 15.11}\n",
+      "{'loss': 0.1014, 'learning_rate': 3.9525e-05, 'epoch': 15.12}\n",
+      "{'loss': 0.1813, 'learning_rate': 3.9500000000000005e-05, 'epoch': 15.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6123fa59a0614afab849b01dd49a8207",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.36944761872291565, 'eval_mean_iou': 0.31458901021269736, 'eval_mean_accuracy': 0.3707156221523364, 'eval_overall_accuracy': 0.6066164617138999, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.76753544676497, 'eval_accuracy_RV': 0.4745974450112648, 'eval_accuracy_RA': 0.5791603786527645, 'eval_accuracy_LA': 0.6244365699545139, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.01933900995814692, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3940350750577367, 'eval_accuracy_VSD': 0.30238852070651034, 'eval_accuracy_AK': 0.5456637754174566, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7259906773061252, 'eval_iou_RV': 0.46049608288995014, 'eval_iou_RA': 0.5427282558552835, 'eval_iou_LA': 0.585412171049458, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.01895701073405365, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.33411357934030966, 'eval_iou_VSD': 0.2797835813130788, 'eval_iou_AK': 0.5129977538514124, 'eval_runtime': 4.5943, 'eval_samples_per_second': 17.63, 'eval_steps_per_second': 8.924, 'epoch': 15.12}\n",
+      "{'loss': 0.0662, 'learning_rate': 3.9475000000000004e-05, 'epoch': 15.13}\n",
+      "{'loss': 0.0676, 'learning_rate': 3.9450000000000003e-05, 'epoch': 15.14}\n",
+      "{'loss': 0.1464, 'learning_rate': 3.9425e-05, 'epoch': 15.14}\n",
+      "{'loss': 0.1602, 'learning_rate': 3.94e-05, 'epoch': 15.15}\n",
+      "{'loss': 0.1406, 'learning_rate': 3.9375e-05, 'epoch': 15.16}\n",
+      "{'loss': 0.1184, 'learning_rate': 3.935e-05, 'epoch': 15.16}\n",
+      "{'loss': 0.1505, 'learning_rate': 3.9325e-05, 'epoch': 15.17}\n",
+      "{'loss': 0.3239, 'learning_rate': 3.9300000000000007e-05, 'epoch': 15.18}\n",
+      "{'loss': 0.1181, 'learning_rate': 3.9275e-05, 'epoch': 15.18}\n",
+      "{'loss': 0.0162, 'learning_rate': 3.9250000000000005e-05, 'epoch': 15.19}\n",
+      "{'loss': 0.1091, 'learning_rate': 3.9225e-05, 'epoch': 15.19}\n",
+      "{'loss': 0.1538, 'learning_rate': 3.9200000000000004e-05, 'epoch': 15.2}\n",
+      "{'loss': 0.1063, 'learning_rate': 3.9175000000000004e-05, 'epoch': 15.21}\n",
+      "{'loss': 0.0398, 'learning_rate': 3.915e-05, 'epoch': 15.21}\n",
+      "{'loss': 0.1982, 'learning_rate': 3.9125e-05, 'epoch': 15.22}\n",
+      "{'loss': 0.1044, 'learning_rate': 3.91e-05, 'epoch': 15.22}\n",
+      "{'loss': 0.0847, 'learning_rate': 3.9075e-05, 'epoch': 15.23}\n",
+      "{'loss': 0.1137, 'learning_rate': 3.905e-05, 'epoch': 15.24}\n",
+      "{'loss': 0.1943, 'learning_rate': 3.9025e-05, 'epoch': 15.24}\n",
+      "{'loss': 0.2485, 'learning_rate': 3.9000000000000006e-05, 'epoch': 15.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6af12cd765b54f829f781eafcf88c6ec",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3914329707622528, 'eval_mean_iou': 0.28182964760699386, 'eval_mean_accuracy': 0.3301161369671493, 'eval_overall_accuracy': 0.5360283918907515, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6825937217537087, 'eval_accuracy_RV': 0.35252183895344913, 'eval_accuracy_RA': 0.4914778917466287, 'eval_accuracy_LA': 0.6188983184571794, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.01493722037812094, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3233436778290993, 'eval_accuracy_VSD': 0.3213782349236813, 'eval_accuracy_AK': 0.4960104656296258, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6522760702618571, 'eval_iou_RV': 0.3465287384760212, 'eval_iou_RA': 0.46782123076686716, 'eval_iou_LA': 0.5777535116890852, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.014754887110857672, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.28079879037628386, 'eval_iou_VSD': 0.2938901990895629, 'eval_iou_AK': 0.46630269590639706, 'eval_runtime': 4.6896, 'eval_samples_per_second': 17.272, 'eval_steps_per_second': 8.743, 'epoch': 15.25}\n",
+      "{'loss': 0.1434, 'learning_rate': 3.8975e-05, 'epoch': 15.26}\n",
+      "{'loss': 0.1849, 'learning_rate': 3.8950000000000005e-05, 'epoch': 15.26}\n",
+      "{'loss': 0.1511, 'learning_rate': 3.8925e-05, 'epoch': 15.27}\n",
+      "{'loss': 0.1793, 'learning_rate': 3.8900000000000004e-05, 'epoch': 15.28}\n",
+      "{'loss': 0.1656, 'learning_rate': 3.8875e-05, 'epoch': 15.28}\n",
+      "{'loss': 0.1104, 'learning_rate': 3.885e-05, 'epoch': 15.29}\n",
+      "{'loss': 0.1475, 'learning_rate': 3.8825e-05, 'epoch': 15.29}\n",
+      "{'loss': 0.1161, 'learning_rate': 3.88e-05, 'epoch': 15.3}\n",
+      "{'loss': 0.1538, 'learning_rate': 3.8775e-05, 'epoch': 15.31}\n",
+      "{'loss': 0.0845, 'learning_rate': 3.875e-05, 'epoch': 15.31}\n",
+      "{'loss': 0.0502, 'learning_rate': 3.8725e-05, 'epoch': 15.32}\n",
+      "{'loss': 0.0911, 'learning_rate': 3.8700000000000006e-05, 'epoch': 15.32}\n",
+      "{'loss': 0.1365, 'learning_rate': 3.8675e-05, 'epoch': 15.33}\n",
+      "{'loss': 0.077, 'learning_rate': 3.8650000000000004e-05, 'epoch': 15.34}\n",
+      "{'loss': 0.1748, 'learning_rate': 3.8625e-05, 'epoch': 15.34}\n",
+      "{'loss': 0.212, 'learning_rate': 3.86e-05, 'epoch': 15.35}\n",
+      "{'loss': 0.1761, 'learning_rate': 3.8575e-05, 'epoch': 15.36}\n",
+      "{'loss': 0.0725, 'learning_rate': 3.855e-05, 'epoch': 15.36}\n",
+      "{'loss': 0.1026, 'learning_rate': 3.8525e-05, 'epoch': 15.37}\n",
+      "{'loss': 0.2723, 'learning_rate': 3.85e-05, 'epoch': 15.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "143d3d75c2a844209fd0e3afb4c8459a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.38223710656166077, 'eval_mean_iou': 0.28694094740392156, 'eval_mean_accuracy': 0.3367160025014605, 'eval_overall_accuracy': 0.5503520044834995, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7151021266567429, 'eval_accuracy_RV': 0.39947021737662447, 'eval_accuracy_RA': 0.567176163921461, 'eval_accuracy_LA': 0.5762542964756894, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.04107735603983259, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3764073325635104, 'eval_accuracy_VSD': 0.3356074009656041, 'eval_accuracy_AK': 0.3560651310151401, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.681076830848259, 'eval_iou_RV': 0.38877047919333374, 'eval_iou_RA': 0.5287010881626113, 'eval_iou_LA': 0.5470147394745368, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.039832761878105104, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3151716584205159, 'eval_iou_VSD': 0.3100224382946896, 'eval_iou_AK': 0.3457604251710866, 'eval_runtime': 4.566, 'eval_samples_per_second': 17.74, 'eval_steps_per_second': 8.979, 'epoch': 15.38}\n",
+      "{'loss': 0.0477, 'learning_rate': 3.8475e-05, 'epoch': 15.38}\n",
+      "{'loss': 0.1598, 'learning_rate': 3.845e-05, 'epoch': 15.39}\n",
+      "{'loss': 0.0729, 'learning_rate': 3.8425e-05, 'epoch': 15.39}\n",
+      "{'loss': 0.2513, 'learning_rate': 3.8400000000000005e-05, 'epoch': 15.4}\n",
+      "{'loss': 0.1587, 'learning_rate': 3.8375e-05, 'epoch': 15.41}\n",
+      "{'loss': 0.0374, 'learning_rate': 3.8350000000000004e-05, 'epoch': 15.41}\n",
+      "{'loss': 0.2367, 'learning_rate': 3.8324999999999996e-05, 'epoch': 15.42}\n",
+      "{'loss': 0.1883, 'learning_rate': 3.83e-05, 'epoch': 15.43}\n",
+      "{'loss': 0.0555, 'learning_rate': 3.8275e-05, 'epoch': 15.43}\n",
+      "{'loss': 0.149, 'learning_rate': 3.825e-05, 'epoch': 15.44}\n",
+      "{'loss': 0.1668, 'learning_rate': 3.8225e-05, 'epoch': 15.44}\n",
+      "{'loss': 0.0759, 'learning_rate': 3.82e-05, 'epoch': 15.45}\n",
+      "{'loss': 0.0823, 'learning_rate': 3.8175e-05, 'epoch': 15.46}\n",
+      "{'loss': 0.0403, 'learning_rate': 3.8150000000000006e-05, 'epoch': 15.46}\n",
+      "{'loss': 0.1008, 'learning_rate': 3.8125e-05, 'epoch': 15.47}\n",
+      "{'loss': 0.0516, 'learning_rate': 3.8100000000000005e-05, 'epoch': 15.47}\n",
+      "{'loss': 0.1249, 'learning_rate': 3.8075e-05, 'epoch': 15.48}\n",
+      "{'loss': 0.09, 'learning_rate': 3.805e-05, 'epoch': 15.49}\n",
+      "{'loss': 0.1069, 'learning_rate': 3.8025e-05, 'epoch': 15.49}\n",
+      "{'loss': 0.1334, 'learning_rate': 3.8e-05, 'epoch': 15.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "19ead39fd6524b36a550f8c90af6c8b1",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.375806599855423, 'eval_mean_iou': 0.32000875945310875, 'eval_mean_accuracy': 0.377518950590055, 'eval_overall_accuracy': 0.6069767429279935, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7672557805149439, 'eval_accuracy_RV': 0.45720301785791023, 'eval_accuracy_RA': 0.5658445845068718, 'eval_accuracy_LA': 0.6677014798400098, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.03829917737047193, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4784750288683603, 'eval_accuracy_VSD': 0.30993792545056525, 'eval_accuracy_AK': 0.49047251149141713, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7239219814389625, 'eval_iou_RV': 0.4447662613763944, 'eval_iou_RA': 0.5390846045023988, 'eval_iou_LA': 0.6239835867187061, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.037023473195912246, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.39727053465761836, 'eval_iou_VSD': 0.2894388630237687, 'eval_iou_AK': 0.4646070490704354, 'eval_runtime': 4.6072, 'eval_samples_per_second': 17.581, 'eval_steps_per_second': 8.899, 'epoch': 15.5}\n",
+      "{'loss': 0.1999, 'learning_rate': 3.7975e-05, 'epoch': 15.51}\n",
+      "{'loss': 0.1403, 'learning_rate': 3.795e-05, 'epoch': 15.51}\n",
+      "{'loss': 0.2294, 'learning_rate': 3.7925e-05, 'epoch': 15.52}\n",
+      "{'loss': 0.317, 'learning_rate': 3.79e-05, 'epoch': 15.53}\n",
+      "{'loss': 0.0824, 'learning_rate': 3.7875e-05, 'epoch': 15.53}\n",
+      "{'loss': 0.0079, 'learning_rate': 3.7850000000000005e-05, 'epoch': 15.54}\n",
+      "{'loss': 0.1371, 'learning_rate': 3.7825e-05, 'epoch': 15.54}\n",
+      "{'loss': 0.1001, 'learning_rate': 3.7800000000000004e-05, 'epoch': 15.55}\n",
+      "{'loss': 0.0578, 'learning_rate': 3.7775e-05, 'epoch': 15.56}\n",
+      "{'loss': 0.108, 'learning_rate': 3.775e-05, 'epoch': 15.56}\n",
+      "{'loss': 0.1373, 'learning_rate': 3.7725e-05, 'epoch': 15.57}\n",
+      "{'loss': 0.1277, 'learning_rate': 3.77e-05, 'epoch': 15.57}\n",
+      "{'loss': 0.1034, 'learning_rate': 3.7675e-05, 'epoch': 15.58}\n",
+      "{'loss': 0.1982, 'learning_rate': 3.765e-05, 'epoch': 15.59}\n",
+      "{'loss': 0.0506, 'learning_rate': 3.7625e-05, 'epoch': 15.59}\n",
+      "{'loss': 0.1916, 'learning_rate': 3.76e-05, 'epoch': 15.6}\n",
+      "{'loss': 0.2738, 'learning_rate': 3.7575e-05, 'epoch': 15.61}\n",
+      "{'loss': 0.092, 'learning_rate': 3.7550000000000005e-05, 'epoch': 15.61}\n",
+      "{'loss': 0.0809, 'learning_rate': 3.7525e-05, 'epoch': 15.62}\n",
+      "{'loss': 0.0622, 'learning_rate': 3.7500000000000003e-05, 'epoch': 15.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "11737cc15e2147c58af31956a7c830e9",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.36753568053245544, 'eval_mean_iou': 0.32817087109125703, 'eval_mean_accuracy': 0.3937573408533085, 'eval_overall_accuracy': 0.6072869850845741, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7390669140656463, 'eval_accuracy_RV': 0.46441769952792256, 'eval_accuracy_RA': 0.6027192465681567, 'eval_accuracy_LA': 0.647318518925075, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.04533482465002165, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.5459277569284064, 'eval_accuracy_VSD': 0.358450535280535, 'eval_accuracy_AK': 0.5343379125873218, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7012018747718094, 'eval_iou_RV': 0.4522248922523298, 'eval_iou_RA': 0.5577744958373086, 'eval_iou_LA': 0.6023429145985285, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.04386761163285969, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.4264562867330975, 'eval_iou_VSD': 0.3274728435817706, 'eval_iou_AK': 0.4985386625961227, 'eval_runtime': 4.7665, 'eval_samples_per_second': 16.994, 'eval_steps_per_second': 8.602, 'epoch': 15.62}\n",
+      "{'loss': 0.0848, 'learning_rate': 3.7475e-05, 'epoch': 15.63}\n",
+      "{'loss': 0.1276, 'learning_rate': 3.745e-05, 'epoch': 15.64}\n",
+      "{'loss': 0.2403, 'learning_rate': 3.7425e-05, 'epoch': 15.64}\n",
+      "{'loss': 0.2143, 'learning_rate': 3.74e-05, 'epoch': 15.65}\n",
+      "{'loss': 0.1958, 'learning_rate': 3.737500000000001e-05, 'epoch': 15.66}\n",
+      "{'loss': 0.1992, 'learning_rate': 3.735e-05, 'epoch': 15.66}\n",
+      "{'loss': 0.1928, 'learning_rate': 3.7325000000000006e-05, 'epoch': 15.67}\n",
+      "{'loss': 0.1421, 'learning_rate': 3.73e-05, 'epoch': 15.68}\n",
+      "{'loss': 0.2708, 'learning_rate': 3.7275000000000005e-05, 'epoch': 15.68}\n",
+      "{'loss': 0.1056, 'learning_rate': 3.7250000000000004e-05, 'epoch': 15.69}\n",
+      "{'loss': 0.1269, 'learning_rate': 3.7225000000000004e-05, 'epoch': 15.69}\n",
+      "{'loss': 0.1837, 'learning_rate': 3.72e-05, 'epoch': 15.7}\n",
+      "{'loss': 0.3659, 'learning_rate': 3.7175e-05, 'epoch': 15.71}\n",
+      "{'loss': 0.1656, 'learning_rate': 3.715e-05, 'epoch': 15.71}\n",
+      "{'loss': 0.0888, 'learning_rate': 3.7125e-05, 'epoch': 15.72}\n",
+      "{'loss': 0.1489, 'learning_rate': 3.71e-05, 'epoch': 15.72}\n",
+      "{'loss': 0.1087, 'learning_rate': 3.707500000000001e-05, 'epoch': 15.73}\n",
+      "{'loss': 0.0817, 'learning_rate': 3.705e-05, 'epoch': 15.74}\n",
+      "{'loss': 0.0687, 'learning_rate': 3.7025000000000005e-05, 'epoch': 15.74}\n",
+      "{'loss': 0.152, 'learning_rate': 3.7e-05, 'epoch': 15.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "571971d61fab4ddca37c69c56d4cd0bc",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3685884475708008, 'eval_mean_iou': 0.3397200629287481, 'eval_mean_accuracy': 0.40507835826223487, 'eval_overall_accuracy': 0.6422510326979545, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7858084666533421, 'eval_accuracy_RV': 0.5029359042830746, 'eval_accuracy_RA': 0.6311020635445836, 'eval_accuracy_LA': 0.7058569282171255, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.05424664453745129, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.5110150837182448, 'eval_accuracy_VSD': 0.31936156175967856, 'eval_accuracy_AK': 0.5404569299088477, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7367007255992941, 'eval_iou_RV': 0.4847406833262825, 'eval_iou_RA': 0.5928068815606694, 'eval_iou_LA': 0.6533449119459214, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.05087986463620981, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.4175974049909691, 'eval_iou_VSD': 0.2978638604342202, 'eval_iou_AK': 0.5029863597226628, 'eval_runtime': 4.5743, 'eval_samples_per_second': 17.708, 'eval_steps_per_second': 8.963, 'epoch': 15.75}\n",
+      "{'loss': 0.1225, 'learning_rate': 3.6975000000000004e-05, 'epoch': 15.76}\n",
+      "{'loss': 0.0071, 'learning_rate': 3.6950000000000004e-05, 'epoch': 15.76}\n",
+      "{'loss': 0.0746, 'learning_rate': 3.6925e-05, 'epoch': 15.77}\n",
+      "{'loss': 0.1582, 'learning_rate': 3.69e-05, 'epoch': 15.78}\n",
+      "{'loss': 0.0155, 'learning_rate': 3.6875e-05, 'epoch': 15.78}\n",
+      "{'loss': 0.107, 'learning_rate': 3.685e-05, 'epoch': 15.79}\n",
+      "{'loss': 0.0901, 'learning_rate': 3.6825e-05, 'epoch': 15.79}\n",
+      "{'loss': 0.0084, 'learning_rate': 3.68e-05, 'epoch': 15.8}\n",
+      "{'loss': 0.0848, 'learning_rate': 3.6775000000000006e-05, 'epoch': 15.81}\n",
+      "{'loss': 0.0734, 'learning_rate': 3.675e-05, 'epoch': 15.81}\n",
+      "{'loss': 0.4812, 'learning_rate': 3.6725000000000005e-05, 'epoch': 15.82}\n",
+      "{'loss': 0.5379, 'learning_rate': 3.6700000000000004e-05, 'epoch': 15.82}\n",
+      "{'loss': 0.1809, 'learning_rate': 3.6675000000000004e-05, 'epoch': 15.83}\n",
+      "{'loss': 0.1796, 'learning_rate': 3.665e-05, 'epoch': 15.84}\n",
+      "{'loss': 0.0888, 'learning_rate': 3.6625e-05, 'epoch': 15.84}\n",
+      "{'loss': 0.1467, 'learning_rate': 3.66e-05, 'epoch': 15.85}\n",
+      "{'loss': 0.1104, 'learning_rate': 3.6575e-05, 'epoch': 15.86}\n",
+      "{'loss': 0.1801, 'learning_rate': 3.655e-05, 'epoch': 15.86}\n",
+      "{'loss': 0.0398, 'learning_rate': 3.652500000000001e-05, 'epoch': 15.87}\n",
+      "{'loss': 0.191, 'learning_rate': 3.65e-05, 'epoch': 15.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "7755683841b249b7bfb85312ee71dd9e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.37473657727241516, 'eval_mean_iou': 0.31426850849893856, 'eval_mean_accuracy': 0.37028511224477106, 'eval_overall_accuracy': 0.5891555354557828, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7364992050020732, 'eval_accuracy_RV': 0.43524742628777696, 'eval_accuracy_RA': 0.5600380912414356, 'eval_accuracy_LA': 0.6661321084804369, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.045064222831577426, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4327096564665127, 'eval_accuracy_VSD': 0.3677017422856629, 'eval_accuracy_AK': 0.45945866985223466, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7049744975354161, 'eval_iou_RV': 0.4232941485519144, 'eval_iou_RA': 0.5351780302153946, 'eval_iou_LA': 0.6174684333196605, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.043185118594841296, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.35827127480784887, 'eval_iou_VSD': 0.33636457154613725, 'eval_iou_AK': 0.43821751891711147, 'eval_runtime': 4.5554, 'eval_samples_per_second': 17.781, 'eval_steps_per_second': 9.0, 'epoch': 15.88}\n",
+      "{'loss': 0.1131, 'learning_rate': 3.6475000000000006e-05, 'epoch': 15.88}\n",
+      "{'loss': 0.1747, 'learning_rate': 3.645e-05, 'epoch': 15.89}\n",
+      "{'loss': 0.2529, 'learning_rate': 3.6425000000000004e-05, 'epoch': 15.89}\n",
+      "{'loss': 0.2888, 'learning_rate': 3.6400000000000004e-05, 'epoch': 15.9}\n",
+      "{'loss': 0.1473, 'learning_rate': 3.6375e-05, 'epoch': 15.91}\n",
+      "{'loss': 0.1629, 'learning_rate': 3.635e-05, 'epoch': 15.91}\n",
+      "{'loss': 0.1445, 'learning_rate': 3.6325e-05, 'epoch': 15.92}\n",
+      "{'loss': 0.0072, 'learning_rate': 3.63e-05, 'epoch': 15.93}\n",
+      "{'loss': 0.1449, 'learning_rate': 3.6275e-05, 'epoch': 15.93}\n",
+      "{'loss': 0.1072, 'learning_rate': 3.625e-05, 'epoch': 15.94}\n",
+      "{'loss': 0.1276, 'learning_rate': 3.6225000000000006e-05, 'epoch': 15.94}\n",
+      "{'loss': 0.1593, 'learning_rate': 3.62e-05, 'epoch': 15.95}\n",
+      "{'loss': 0.1709, 'learning_rate': 3.6175000000000005e-05, 'epoch': 15.96}\n",
+      "{'loss': 0.1719, 'learning_rate': 3.615e-05, 'epoch': 15.96}\n",
+      "{'loss': 0.1519, 'learning_rate': 3.6125000000000004e-05, 'epoch': 15.97}\n",
+      "{'loss': 0.2281, 'learning_rate': 3.61e-05, 'epoch': 15.97}\n",
+      "{'loss': 0.1537, 'learning_rate': 3.6075e-05, 'epoch': 15.98}\n",
+      "{'loss': 0.2072, 'learning_rate': 3.605e-05, 'epoch': 15.99}\n",
+      "{'loss': 0.1328, 'learning_rate': 3.6025e-05, 'epoch': 15.99}\n",
+      "{'loss': 0.139, 'learning_rate': 3.6e-05, 'epoch': 16.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "536e347e1cb3447da9ec0f897c6252ea",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.387359619140625, 'eval_mean_iou': 0.3024376505873227, 'eval_mean_accuracy': 0.3564917128155886, 'eval_overall_accuracy': 0.5687666481296753, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7173402024336184, 'eval_accuracy_RV': 0.4048340362314837, 'eval_accuracy_RA': 0.543758524125798, 'eval_accuracy_LA': 0.6182911518328199, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.03891254149227883, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.40312860854503463, 'eval_accuracy_VSD': 0.3323837226737038, 'eval_accuracy_AK': 0.5062683408211494, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6895333049453819, 'eval_iou_RV': 0.39569214060920255, 'eval_iou_RA': 0.5139149751637476, 'eval_iou_LA': 0.5789405217894052, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.037631500898480434, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3329310087915363, 'eval_iou_VSD': 0.3062555260831123, 'eval_iou_AK': 0.47191517817968354, 'eval_runtime': 4.5237, 'eval_samples_per_second': 17.906, 'eval_steps_per_second': 9.063, 'epoch': 16.0}\n",
+      "{'loss': 0.0114, 'learning_rate': 3.5975e-05, 'epoch': 16.01}\n",
+      "{'loss': 0.1442, 'learning_rate': 3.595e-05, 'epoch': 16.01}\n",
+      "{'loss': 0.1998, 'learning_rate': 3.5925000000000006e-05, 'epoch': 16.02}\n",
+      "{'loss': 0.1891, 'learning_rate': 3.59e-05, 'epoch': 16.02}\n",
+      "{'loss': 0.2799, 'learning_rate': 3.5875000000000005e-05, 'epoch': 16.03}\n",
+      "{'loss': 0.1489, 'learning_rate': 3.585e-05, 'epoch': 16.04}\n",
+      "{'loss': 0.0533, 'learning_rate': 3.5825000000000003e-05, 'epoch': 16.04}\n",
+      "{'loss': 0.1486, 'learning_rate': 3.58e-05, 'epoch': 16.05}\n",
+      "{'loss': 0.0074, 'learning_rate': 3.5775e-05, 'epoch': 16.06}\n",
+      "{'loss': 0.175, 'learning_rate': 3.575e-05, 'epoch': 16.06}\n",
+      "{'loss': 0.1328, 'learning_rate': 3.5725e-05, 'epoch': 16.07}\n",
+      "{'loss': 0.2297, 'learning_rate': 3.57e-05, 'epoch': 16.07}\n",
+      "{'loss': 0.1966, 'learning_rate': 3.5675e-05, 'epoch': 16.08}\n",
+      "{'loss': 0.1942, 'learning_rate': 3.565e-05, 'epoch': 16.09}\n",
+      "{'loss': 0.1314, 'learning_rate': 3.5625000000000005e-05, 'epoch': 16.09}\n",
+      "{'loss': 0.1548, 'learning_rate': 3.56e-05, 'epoch': 16.1}\n",
+      "{'loss': 0.2106, 'learning_rate': 3.5575000000000004e-05, 'epoch': 16.11}\n",
+      "{'loss': 0.2891, 'learning_rate': 3.555e-05, 'epoch': 16.11}\n",
+      "{'loss': 0.0977, 'learning_rate': 3.5525e-05, 'epoch': 16.12}\n",
+      "{'loss': 0.1043, 'learning_rate': 3.55e-05, 'epoch': 16.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9ae6ef32f84048f3bc86fed641567561",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.38350510597229004, 'eval_mean_iou': 0.3246808596780914, 'eval_mean_accuracy': 0.38580313566729707, 'eval_overall_accuracy': 0.6041667117468986, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7256019163477229, 'eval_accuracy_RV': 0.4774013640521311, 'eval_accuracy_RA': 0.620346533454924, 'eval_accuracy_LA': 0.6631322937177121, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.06388006927406552, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4520334151270208, 'eval_accuracy_VSD': 0.3531427114882898, 'eval_accuracy_AK': 0.5024930532111045, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6909724910072901, 'eval_iou_RV': 0.46323048720739934, 'eval_iou_RA': 0.5772311019497854, 'eval_iou_LA': 0.6177145376926813, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.06064083023650095, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.36710576444040677, 'eval_iou_VSD': 0.32553109148456827, 'eval_iou_AK': 0.4690631524403732, 'eval_runtime': 4.6368, 'eval_samples_per_second': 17.469, 'eval_steps_per_second': 8.842, 'epoch': 16.12}\n",
+      "{'loss': 0.0456, 'learning_rate': 3.5475e-05, 'epoch': 16.13}\n",
+      "{'loss': 0.0874, 'learning_rate': 3.545e-05, 'epoch': 16.14}\n",
+      "{'loss': 0.0609, 'learning_rate': 3.5425e-05, 'epoch': 16.14}\n",
+      "{'loss': 0.1523, 'learning_rate': 3.54e-05, 'epoch': 16.15}\n",
+      "{'loss': 0.0569, 'learning_rate': 3.5375e-05, 'epoch': 16.16}\n",
+      "{'loss': 0.0829, 'learning_rate': 3.535e-05, 'epoch': 16.16}\n",
+      "{'loss': 0.0385, 'learning_rate': 3.5325000000000005e-05, 'epoch': 16.17}\n",
+      "{'loss': 0.0539, 'learning_rate': 3.53e-05, 'epoch': 16.18}\n",
+      "{'loss': 0.0835, 'learning_rate': 3.5275000000000004e-05, 'epoch': 16.18}\n",
+      "{'loss': 0.2187, 'learning_rate': 3.525e-05, 'epoch': 16.19}\n",
+      "{'loss': 0.0593, 'learning_rate': 3.5225e-05, 'epoch': 16.19}\n",
+      "{'loss': 0.0824, 'learning_rate': 3.52e-05, 'epoch': 16.2}\n",
+      "{'loss': 0.1109, 'learning_rate': 3.5175e-05, 'epoch': 16.21}\n",
+      "{'loss': 0.1683, 'learning_rate': 3.515e-05, 'epoch': 16.21}\n",
+      "{'loss': 0.1676, 'learning_rate': 3.5125e-05, 'epoch': 16.22}\n",
+      "{'loss': 0.1945, 'learning_rate': 3.51e-05, 'epoch': 16.23}\n",
+      "{'loss': 0.2147, 'learning_rate': 3.5075000000000006e-05, 'epoch': 16.23}\n",
+      "{'loss': 0.1363, 'learning_rate': 3.505e-05, 'epoch': 16.24}\n",
+      "{'loss': 0.1872, 'learning_rate': 3.5025000000000004e-05, 'epoch': 16.24}\n",
+      "{'loss': 0.1203, 'learning_rate': 3.5e-05, 'epoch': 16.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a3608d48dfe747179e6a42d7d443b6b9",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.38196438550949097, 'eval_mean_iou': 0.3052291652369293, 'eval_mean_accuracy': 0.3618511055015231, 'eval_overall_accuracy': 0.579454990814452, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7411558345091745, 'eval_accuracy_RV': 0.4010816651012603, 'eval_accuracy_RA': 0.5614160741810786, 'eval_accuracy_LA': 0.6567793412413642, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.055347091932457786, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4333952800230947, 'eval_accuracy_VSD': 0.3557291510480703, 'eval_accuracy_AK': 0.41360661697873113, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.696096189487575, 'eval_iou_RV': 0.39029387781922886, 'eval_iou_RA': 0.5263758235646849, 'eval_iou_LA': 0.6114254874785241, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.05296138376288215, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.35665976228126833, 'eval_iou_VSD': 0.32842143148831315, 'eval_iou_AK': 0.39528686172374533, 'eval_runtime': 4.6379, 'eval_samples_per_second': 17.465, 'eval_steps_per_second': 8.84, 'epoch': 16.25}\n",
+      "{'loss': 0.1565, 'learning_rate': 3.4975e-05, 'epoch': 16.26}\n",
+      "{'loss': 0.183, 'learning_rate': 3.495e-05, 'epoch': 16.26}\n",
+      "{'loss': 0.0624, 'learning_rate': 3.4925e-05, 'epoch': 16.27}\n",
+      "{'loss': 0.1649, 'learning_rate': 3.49e-05, 'epoch': 16.27}\n",
+      "{'loss': 0.0955, 'learning_rate': 3.4875e-05, 'epoch': 16.28}\n",
+      "{'loss': 0.1521, 'learning_rate': 3.485e-05, 'epoch': 16.29}\n",
+      "{'loss': 0.0978, 'learning_rate': 3.4825e-05, 'epoch': 16.29}\n",
+      "{'loss': 0.0775, 'learning_rate': 3.48e-05, 'epoch': 16.3}\n",
+      "{'loss': 0.0768, 'learning_rate': 3.4775000000000005e-05, 'epoch': 16.31}\n",
+      "{'loss': 0.1441, 'learning_rate': 3.475e-05, 'epoch': 16.31}\n",
+      "{'loss': 0.2104, 'learning_rate': 3.4725000000000004e-05, 'epoch': 16.32}\n",
+      "{'loss': 0.1012, 'learning_rate': 3.4699999999999996e-05, 'epoch': 16.32}\n",
+      "{'loss': 0.0522, 'learning_rate': 3.4675e-05, 'epoch': 16.33}\n",
+      "{'loss': 0.196, 'learning_rate': 3.465e-05, 'epoch': 16.34}\n",
+      "{'loss': 0.1376, 'learning_rate': 3.4625e-05, 'epoch': 16.34}\n",
+      "{'loss': 0.2112, 'learning_rate': 3.46e-05, 'epoch': 16.35}\n",
+      "{'loss': 0.0553, 'learning_rate': 3.4575e-05, 'epoch': 16.36}\n",
+      "{'loss': 0.2299, 'learning_rate': 3.455e-05, 'epoch': 16.36}\n",
+      "{'loss': 0.1449, 'learning_rate': 3.4525e-05, 'epoch': 16.37}\n",
+      "{'loss': 0.1466, 'learning_rate': 3.45e-05, 'epoch': 16.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "fc83219313cd40a481f8ad997c552d03",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3763272166252136, 'eval_mean_iou': 0.30246121780637447, 'eval_mean_accuracy': 0.3564991947924606, 'eval_overall_accuracy': 0.5699840848748969, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.719388850937143, 'eval_accuracy_RV': 0.41247229844625743, 'eval_accuracy_RA': 0.5148834262748864, 'eval_accuracy_LA': 0.6390651692176812, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.033031461971424446, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.40955181870669743, 'eval_accuracy_VSD': 0.3368293999460221, 'eval_accuracy_AK': 0.49976952242449424, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6844949650130319, 'eval_iou_RV': 0.4029662992777667, 'eval_iou_RA': 0.49343384931882955, 'eval_iou_LA': 0.5957145415243723, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.03191174163863569, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.342861890052791, 'eval_iou_VSD': 0.31162174534256265, 'eval_iou_AK': 0.46406836370212956, 'eval_runtime': 4.456, 'eval_samples_per_second': 18.178, 'eval_steps_per_second': 9.201, 'epoch': 16.38}\n",
+      "{'loss': 0.2741, 'learning_rate': 3.4475000000000005e-05, 'epoch': 16.38}\n",
+      "{'loss': 0.1274, 'learning_rate': 3.445e-05, 'epoch': 16.39}\n",
+      "{'loss': 0.0779, 'learning_rate': 3.4425e-05, 'epoch': 16.39}\n",
+      "{'loss': 0.1606, 'learning_rate': 3.4399999999999996e-05, 'epoch': 16.4}\n",
+      "{'loss': 0.1603, 'learning_rate': 3.4375e-05, 'epoch': 16.41}\n",
+      "{'loss': 0.1554, 'learning_rate': 3.435e-05, 'epoch': 16.41}\n",
+      "{'loss': 0.0909, 'learning_rate': 3.4325e-05, 'epoch': 16.42}\n",
+      "{'loss': 0.0987, 'learning_rate': 3.430000000000001e-05, 'epoch': 16.43}\n",
+      "{'loss': 0.1189, 'learning_rate': 3.4275e-05, 'epoch': 16.43}\n",
+      "{'loss': 0.1129, 'learning_rate': 3.4250000000000006e-05, 'epoch': 16.44}\n",
+      "{'loss': 0.0072, 'learning_rate': 3.4225e-05, 'epoch': 16.44}\n",
+      "{'loss': 0.0748, 'learning_rate': 3.4200000000000005e-05, 'epoch': 16.45}\n",
+      "{'loss': 0.1379, 'learning_rate': 3.4175000000000004e-05, 'epoch': 16.46}\n",
+      "{'loss': 0.1607, 'learning_rate': 3.415e-05, 'epoch': 16.46}\n",
+      "{'loss': 0.2121, 'learning_rate': 3.4125e-05, 'epoch': 16.47}\n",
+      "{'loss': 0.2124, 'learning_rate': 3.41e-05, 'epoch': 16.48}\n",
+      "{'loss': 0.1451, 'learning_rate': 3.4075e-05, 'epoch': 16.48}\n",
+      "{'loss': 0.1852, 'learning_rate': 3.405e-05, 'epoch': 16.49}\n",
+      "{'loss': 0.1066, 'learning_rate': 3.4025e-05, 'epoch': 16.49}\n",
+      "{'loss': 0.246, 'learning_rate': 3.4000000000000007e-05, 'epoch': 16.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "3d7cb397a8f140f99e0a08f2affe3e53",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.1631, 'learning_rate': 3.3975e-05, 'epoch': 16.51}\n",
+      "{'loss': 0.0543, 'learning_rate': 3.3950000000000005e-05, 'epoch': 16.51}\n",
+      "{'loss': 0.0571, 'learning_rate': 3.3925e-05, 'epoch': 16.52}\n",
+      "{'loss': 0.1585, 'learning_rate': 3.3900000000000004e-05, 'epoch': 16.52}\n",
+      "{'loss': 0.1759, 'learning_rate': 3.3875000000000003e-05, 'epoch': 16.53}\n",
+      "{'loss': 0.2408, 'learning_rate': 3.385e-05, 'epoch': 16.54}\n",
+      "{'loss': 0.064, 'learning_rate': 3.3825e-05, 'epoch': 16.54}\n",
+      "{'loss': 0.0161, 'learning_rate': 3.38e-05, 'epoch': 16.55}\n",
+      "{'loss': 0.0597, 'learning_rate': 3.3775e-05, 'epoch': 16.56}\n",
+      "{'loss': 0.1064, 'learning_rate': 3.375000000000001e-05, 'epoch': 16.56}\n",
+      "{'loss': 0.1477, 'learning_rate': 3.3725e-05, 'epoch': 16.57}\n",
+      "{'loss': 0.1535, 'learning_rate': 3.3700000000000006e-05, 'epoch': 16.57}\n",
+      "{'loss': 0.194, 'learning_rate': 3.3675e-05, 'epoch': 16.58}\n",
+      "{'loss': 0.0694, 'learning_rate': 3.3650000000000005e-05, 'epoch': 16.59}\n",
+      "{'loss': 0.1528, 'learning_rate': 3.3625000000000004e-05, 'epoch': 16.59}\n",
+      "{'loss': 0.0723, 'learning_rate': 3.3600000000000004e-05, 'epoch': 16.6}\n",
+      "{'loss': 0.1622, 'learning_rate': 3.3575e-05, 'epoch': 16.61}\n",
+      "{'loss': 0.1838, 'learning_rate': 3.355e-05, 'epoch': 16.61}\n",
+      "{'loss': 0.148, 'learning_rate': 3.3525e-05, 'epoch': 16.62}\n",
+      "{'loss': 0.0531, 'learning_rate': 3.35e-05, 'epoch': 16.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "454535d1a288457c8e8174a773ba4163",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.39099058508872986, 'eval_mean_iou': 0.2883476253322745, 'eval_mean_accuracy': 0.33834330747606745, 'eval_overall_accuracy': 0.5554419233174435, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7369735189621175, 'eval_accuracy_RV': 0.3946972626874651, 'eval_accuracy_RA': 0.49625543728260957, 'eval_accuracy_LA': 0.5544957772761888, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.03171453312166258, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.35233833718244806, 'eval_accuracy_VSD': 0.30680421027378774, 'eval_accuracy_AK': 0.5101539979743943, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7012306711958508, 'eval_iou_RV': 0.3870989105599523, 'eval_iou_RA': 0.4734799631949551, 'eval_iou_LA': 0.5219843384193106, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.030617576369779513, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.2985499048303381, 'eval_iou_VSD': 0.28454815360760943, 'eval_iou_AK': 0.4743143604772238, 'eval_runtime': 4.5586, 'eval_samples_per_second': 17.769, 'eval_steps_per_second': 8.994, 'epoch': 16.62}\n",
+      "{'loss': 0.3629, 'learning_rate': 3.3475e-05, 'epoch': 16.63}\n",
+      "{'loss': 0.0696, 'learning_rate': 3.345000000000001e-05, 'epoch': 16.64}\n",
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+      "{'loss': 0.0738, 'learning_rate': 3.3350000000000004e-05, 'epoch': 16.66}\n",
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+      "{'loss': 0.1983, 'learning_rate': 3.33e-05, 'epoch': 16.68}\n",
+      "{'loss': 0.1512, 'learning_rate': 3.3275e-05, 'epoch': 16.68}\n",
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+      "{'loss': 0.0745, 'learning_rate': 3.3225e-05, 'epoch': 16.69}\n",
+      "{'loss': 0.0783, 'learning_rate': 3.32e-05, 'epoch': 16.7}\n",
+      "{'loss': 0.3218, 'learning_rate': 3.3175e-05, 'epoch': 16.71}\n",
+      "{'loss': 0.1583, 'learning_rate': 3.3150000000000006e-05, 'epoch': 16.71}\n",
+      "{'loss': 0.1138, 'learning_rate': 3.3125e-05, 'epoch': 16.72}\n",
+      "{'loss': 0.0643, 'learning_rate': 3.3100000000000005e-05, 'epoch': 16.73}\n",
+      "{'loss': 0.1045, 'learning_rate': 3.3075e-05, 'epoch': 16.73}\n",
+      "{'loss': 0.1559, 'learning_rate': 3.3050000000000004e-05, 'epoch': 16.74}\n",
+      "{'loss': 0.0918, 'learning_rate': 3.3025e-05, 'epoch': 16.74}\n",
+      "{'loss': 0.1899, 'learning_rate': 3.3e-05, 'epoch': 16.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "111a1c62286c4b0e8bb308dac4f1c98e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.39111748337745667, 'eval_mean_iou': 0.2832092551322585, 'eval_mean_accuracy': 0.33173422949339987, 'eval_overall_accuracy': 0.5320312178803347, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6564400798279344, 'eval_accuracy_RV': 0.4213260526590422, 'eval_accuracy_RA': 0.5033531590712839, 'eval_accuracy_LA': 0.5899464184029802, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.030559965362967238, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3381026270207852, 'eval_accuracy_VSD': 0.3431118241520976, 'eval_accuracy_AK': 0.4345021684369076, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6345511405498228, 'eval_iou_RV': 0.4115851510249487, 'eval_iou_RA': 0.48215086346840647, 'eval_iou_LA': 0.548319937254702, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.029387783425567717, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.29185064050149906, 'eval_iou_VSD': 0.31634571519416066, 'eval_iou_AK': 0.4011105750357356, 'eval_runtime': 4.5847, 'eval_samples_per_second': 17.667, 'eval_steps_per_second': 8.943, 'epoch': 16.75}\n",
+      "{'loss': 0.1227, 'learning_rate': 3.2975e-05, 'epoch': 16.76}\n",
+      "{'loss': 0.1538, 'learning_rate': 3.295e-05, 'epoch': 16.76}\n",
+      "{'loss': 0.1802, 'learning_rate': 3.2925e-05, 'epoch': 16.77}\n",
+      "{'loss': 0.157, 'learning_rate': 3.29e-05, 'epoch': 16.77}\n",
+      "{'loss': 0.1873, 'learning_rate': 3.2875e-05, 'epoch': 16.78}\n",
+      "{'loss': 0.1924, 'learning_rate': 3.2850000000000006e-05, 'epoch': 16.79}\n",
+      "{'loss': 0.1603, 'learning_rate': 3.2825e-05, 'epoch': 16.79}\n",
+      "{'loss': 0.0601, 'learning_rate': 3.2800000000000004e-05, 'epoch': 16.8}\n",
+      "{'loss': 0.0474, 'learning_rate': 3.2775e-05, 'epoch': 16.81}\n",
+      "{'loss': 0.1149, 'learning_rate': 3.275e-05, 'epoch': 16.81}\n",
+      "{'loss': 0.1497, 'learning_rate': 3.2725e-05, 'epoch': 16.82}\n",
+      "{'loss': 0.1275, 'learning_rate': 3.27e-05, 'epoch': 16.82}\n",
+      "{'loss': 0.0629, 'learning_rate': 3.2675e-05, 'epoch': 16.83}\n",
+      "{'loss': 0.2673, 'learning_rate': 3.265e-05, 'epoch': 16.84}\n",
+      "{'loss': 0.023, 'learning_rate': 3.2625e-05, 'epoch': 16.84}\n",
+      "{'loss': 0.1002, 'learning_rate': 3.26e-05, 'epoch': 16.85}\n",
+      "{'loss': 0.1781, 'learning_rate': 3.2575e-05, 'epoch': 16.86}\n",
+      "{'loss': 0.1033, 'learning_rate': 3.2550000000000005e-05, 'epoch': 16.86}\n",
+      "{'loss': 0.228, 'learning_rate': 3.2525e-05, 'epoch': 16.87}\n",
+      "{'loss': 0.0908, 'learning_rate': 3.2500000000000004e-05, 'epoch': 16.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "63161a6a02de44a99e868657007bf551",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3878847062587738, 'eval_mean_iou': 0.2958596171227957, 'eval_mean_accuracy': 0.3476296982948238, 'eval_overall_accuracy': 0.5574764843477829, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6966627985716886, 'eval_accuracy_RV': 0.4246747945020473, 'eval_accuracy_RA': 0.544761243775875, 'eval_accuracy_LA': 0.5973850671313606, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.04914129022947034, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.35999747401847576, 'eval_accuracy_VSD': 0.33388310792575043, 'eval_accuracy_AK': 0.46979120679357, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6673844349075415, 'eval_iou_RV': 0.41360203996221406, 'eval_iou_RA': 0.5113689306046385, 'eval_iou_LA': 0.5576588693020799, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0463383516203113, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.30753165483704403, 'eval_iou_VSD': 0.3095852130935582, 'eval_iou_AK': 0.44098629402336537, 'eval_runtime': 4.8035, 'eval_samples_per_second': 16.863, 'eval_steps_per_second': 8.535, 'epoch': 16.88}\n",
+      "{'loss': 0.1177, 'learning_rate': 3.2474999999999997e-05, 'epoch': 16.88}\n",
+      "{'loss': 0.1558, 'learning_rate': 3.245e-05, 'epoch': 16.89}\n",
+      "{'loss': 0.1084, 'learning_rate': 3.2425e-05, 'epoch': 16.89}\n",
+      "{'loss': 0.0531, 'learning_rate': 3.24e-05, 'epoch': 16.9}\n",
+      "{'loss': 0.0419, 'learning_rate': 3.2375e-05, 'epoch': 16.91}\n",
+      "{'loss': 0.0941, 'learning_rate': 3.235e-05, 'epoch': 16.91}\n",
+      "{'loss': 0.2467, 'learning_rate': 3.2325e-05, 'epoch': 16.92}\n",
+      "{'loss': 0.0596, 'learning_rate': 3.2300000000000006e-05, 'epoch': 16.93}\n",
+      "{'loss': 0.1347, 'learning_rate': 3.2275e-05, 'epoch': 16.93}\n",
+      "{'loss': 0.2695, 'learning_rate': 3.2250000000000005e-05, 'epoch': 16.94}\n",
+      "{'loss': 0.0624, 'learning_rate': 3.2225e-05, 'epoch': 16.94}\n",
+      "{'loss': 0.0396, 'learning_rate': 3.2200000000000003e-05, 'epoch': 16.95}\n",
+      "{'loss': 0.1883, 'learning_rate': 3.2175e-05, 'epoch': 16.96}\n",
+      "{'loss': 0.0824, 'learning_rate': 3.215e-05, 'epoch': 16.96}\n",
+      "{'loss': 0.1349, 'learning_rate': 3.2125e-05, 'epoch': 16.97}\n",
+      "{'loss': 0.148, 'learning_rate': 3.21e-05, 'epoch': 16.98}\n",
+      "{'loss': 0.142, 'learning_rate': 3.2075e-05, 'epoch': 16.98}\n",
+      "{'loss': 0.1955, 'learning_rate': 3.205e-05, 'epoch': 16.99}\n",
+      "{'loss': 0.1673, 'learning_rate': 3.2025e-05, 'epoch': 16.99}\n",
+      "{'loss': 0.1216, 'learning_rate': 3.2000000000000005e-05, 'epoch': 17.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8e3be064fc834c74b4e7fa05fb5c0e75",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.37109020352363586, 'eval_mean_iou': 0.32204075661768083, 'eval_mean_accuracy': 0.3849453258434156, 'eval_overall_accuracy': 0.604464241278057, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7361330286587058, 'eval_accuracy_RV': 0.4686381578543497, 'eval_accuracy_RA': 0.6466815426952781, 'eval_accuracy_LA': 0.6103756886367223, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.06203997690864482, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4311670034642032, 'eval_accuracy_VSD': 0.3482022370827961, 'eval_accuracy_AK': 0.5462156231334563, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.694136956939091, 'eval_iou_RV': 0.45527588592421186, 'eval_iou_RA': 0.5710780907584585, 'eval_iou_LA': 0.5705319252973533, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.058479432720594485, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3598864483483054, 'eval_iou_VSD': 0.3216593372346688, 'eval_iou_AK': 0.5114002455718054, 'eval_runtime': 4.5729, 'eval_samples_per_second': 17.713, 'eval_steps_per_second': 8.966, 'epoch': 17.0}\n",
+      "{'loss': 0.0581, 'learning_rate': 3.1975e-05, 'epoch': 17.01}\n",
+      "{'loss': 0.1236, 'learning_rate': 3.1950000000000004e-05, 'epoch': 17.01}\n",
+      "{'loss': 0.1824, 'learning_rate': 3.1925e-05, 'epoch': 17.02}\n",
+      "{'loss': 0.2742, 'learning_rate': 3.19e-05, 'epoch': 17.02}\n",
+      "{'loss': 0.133, 'learning_rate': 3.1875e-05, 'epoch': 17.03}\n",
+      "{'loss': 0.1292, 'learning_rate': 3.185e-05, 'epoch': 17.04}\n",
+      "{'loss': 0.1144, 'learning_rate': 3.1825e-05, 'epoch': 17.04}\n",
+      "{'loss': 0.0408, 'learning_rate': 3.18e-05, 'epoch': 17.05}\n",
+      "{'loss': 0.1647, 'learning_rate': 3.1775e-05, 'epoch': 17.06}\n",
+      "{'loss': 0.1254, 'learning_rate': 3.175e-05, 'epoch': 17.06}\n",
+      "{'loss': 0.0688, 'learning_rate': 3.1725e-05, 'epoch': 17.07}\n",
+      "{'loss': 0.1428, 'learning_rate': 3.1700000000000005e-05, 'epoch': 17.07}\n",
+      "{'loss': 0.1191, 'learning_rate': 3.1675e-05, 'epoch': 17.08}\n",
+      "{'loss': 0.0982, 'learning_rate': 3.1650000000000004e-05, 'epoch': 17.09}\n",
+      "{'loss': 0.0056, 'learning_rate': 3.1624999999999996e-05, 'epoch': 17.09}\n",
+      "{'loss': 0.1225, 'learning_rate': 3.16e-05, 'epoch': 17.1}\n",
+      "{'loss': 0.0493, 'learning_rate': 3.1575e-05, 'epoch': 17.11}\n",
+      "{'loss': 0.2079, 'learning_rate': 3.155e-05, 'epoch': 17.11}\n",
+      "{'loss': 0.0063, 'learning_rate': 3.1525e-05, 'epoch': 17.12}\n",
+      "{'loss': 0.0945, 'learning_rate': 3.15e-05, 'epoch': 17.12}\n"
+     ]
+    },
+    {
+     "data": {
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+       "model_id": "5130361839ae492ca11a0e73d9b941b6",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.38992244005203247, 'eval_mean_iou': 0.2986706152013228, 'eval_mean_accuracy': 0.3503259379883595, 'eval_overall_accuracy': 0.5664012883569662, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.723995513407573, 'eval_accuracy_RV': 0.4230387913835123, 'eval_accuracy_RA': 0.5430059800020982, 'eval_accuracy_LA': 0.5946545324816992, 'eval_accuracy_VS': 0.0009176416609314062, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.05565377399336124, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3808819284064665, 'eval_accuracy_VSD': 0.31022280864845414, 'eval_accuracy_AK': 0.4708884098994988, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6854781253596699, 'eval_iou_RV': 0.4141604913786368, 'eval_iou_RA': 0.5103669289845454, 'eval_iou_LA': 0.5613828569393012, 'eval_iou_VS': 0.0009059509654039975, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.05141580973650439, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.32548780769853447, 'eval_iou_VSD': 0.2884447821328742, 'eval_iou_AK': 0.44773401401908103, 'eval_runtime': 4.5864, 'eval_samples_per_second': 17.661, 'eval_steps_per_second': 8.94, 'epoch': 17.12}\n",
+      "{'loss': 0.1191, 'learning_rate': 3.1475e-05, 'epoch': 17.13}\n",
+      "{'loss': 0.1958, 'learning_rate': 3.145e-05, 'epoch': 17.14}\n",
+      "{'loss': 0.1134, 'learning_rate': 3.1425e-05, 'epoch': 17.14}\n",
+      "{'loss': 0.0702, 'learning_rate': 3.1400000000000004e-05, 'epoch': 17.15}\n",
+      "{'loss': 0.1537, 'learning_rate': 3.1375e-05, 'epoch': 17.16}\n",
+      "{'loss': 0.1186, 'learning_rate': 3.135e-05, 'epoch': 17.16}\n",
+      "{'loss': 0.1347, 'learning_rate': 3.1324999999999996e-05, 'epoch': 17.17}\n",
+      "{'loss': 0.1665, 'learning_rate': 3.13e-05, 'epoch': 17.18}\n",
+      "{'loss': 0.1535, 'learning_rate': 3.1275e-05, 'epoch': 17.18}\n",
+      "{'loss': 0.2332, 'learning_rate': 3.125e-05, 'epoch': 17.19}\n",
+      "{'loss': 0.24, 'learning_rate': 3.122500000000001e-05, 'epoch': 17.19}\n",
+      "{'loss': 0.192, 'learning_rate': 3.12e-05, 'epoch': 17.2}\n",
+      "{'loss': 0.2068, 'learning_rate': 3.1175000000000006e-05, 'epoch': 17.21}\n",
+      "{'loss': 0.034, 'learning_rate': 3.115e-05, 'epoch': 17.21}\n",
+      "{'loss': 0.1504, 'learning_rate': 3.1125000000000004e-05, 'epoch': 17.22}\n",
+      "{'loss': 0.1113, 'learning_rate': 3.1100000000000004e-05, 'epoch': 17.23}\n",
+      "{'loss': 0.1298, 'learning_rate': 3.1075e-05, 'epoch': 17.23}\n",
+      "{'loss': 0.1222, 'learning_rate': 3.105e-05, 'epoch': 17.24}\n",
+      "{'loss': 0.189, 'learning_rate': 3.1025e-05, 'epoch': 17.24}\n",
+      "{'loss': 0.1514, 'learning_rate': 3.1e-05, 'epoch': 17.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6550d4de2bba4bc580c21bee2dc0622b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3747710585594177, 'eval_mean_iou': 0.31143651018294727, 'eval_mean_accuracy': 0.3681988474179092, 'eval_overall_accuracy': 0.5871610056714538, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7283799344313154, 'eval_accuracy_RV': 0.4772033861888187, 'eval_accuracy_RA': 0.5549639666540234, 'eval_accuracy_LA': 0.6202104158233797, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.054066243325155146, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.41644413972286376, 'eval_accuracy_VSD': 0.33523255465259244, 'eval_accuracy_AK': 0.4954878333809437, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6904263696862846, 'eval_iou_RV': 0.46434806242878496, 'eval_iou_RA': 0.5183829002938023, 'eval_iou_LA': 0.5790367881837135, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.05046389061947499, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.34835827428252325, 'eval_iou_VSD': 0.31070038910505837, 'eval_iou_AK': 0.46408493741277773, 'eval_runtime': 4.5997, 'eval_samples_per_second': 17.61, 'eval_steps_per_second': 8.914, 'epoch': 17.25}\n",
+      "{'loss': 0.0928, 'learning_rate': 3.0975e-05, 'epoch': 17.26}\n",
+      "{'loss': 0.0957, 'learning_rate': 3.095e-05, 'epoch': 17.26}\n",
+      "{'loss': 0.0674, 'learning_rate': 3.0925000000000006e-05, 'epoch': 17.27}\n",
+      "{'loss': 0.1043, 'learning_rate': 3.09e-05, 'epoch': 17.27}\n",
+      "{'loss': 0.1403, 'learning_rate': 3.0875000000000005e-05, 'epoch': 17.28}\n",
+      "{'loss': 0.1696, 'learning_rate': 3.0850000000000004e-05, 'epoch': 17.29}\n",
+      "{'loss': 0.0934, 'learning_rate': 3.0825000000000004e-05, 'epoch': 17.29}\n",
+      "{'loss': 0.1417, 'learning_rate': 3.08e-05, 'epoch': 17.3}\n",
+      "{'loss': 0.1691, 'learning_rate': 3.0775e-05, 'epoch': 17.31}\n",
+      "{'loss': 0.0644, 'learning_rate': 3.075e-05, 'epoch': 17.31}\n",
+      "{'loss': 0.168, 'learning_rate': 3.0725e-05, 'epoch': 17.32}\n",
+      "{'loss': 0.1477, 'learning_rate': 3.07e-05, 'epoch': 17.32}\n",
+      "{'loss': 0.1425, 'learning_rate': 3.067500000000001e-05, 'epoch': 17.33}\n",
+      "{'loss': 0.2279, 'learning_rate': 3.065e-05, 'epoch': 17.34}\n",
+      "{'loss': 0.0461, 'learning_rate': 3.0625000000000006e-05, 'epoch': 17.34}\n",
+      "{'loss': 0.1678, 'learning_rate': 3.06e-05, 'epoch': 17.35}\n",
+      "{'loss': 0.175, 'learning_rate': 3.0575000000000005e-05, 'epoch': 17.36}\n",
+      "{'loss': 0.0867, 'learning_rate': 3.0550000000000004e-05, 'epoch': 17.36}\n",
+      "{'loss': 0.104, 'learning_rate': 3.0525e-05, 'epoch': 17.37}\n",
+      "{'loss': 0.1432, 'learning_rate': 3.05e-05, 'epoch': 17.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c807808a8547409597197b8aa4177bd5",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3754992187023163, 'eval_mean_iou': 0.3174284948308326, 'eval_mean_accuracy': 0.3774822602141247, 'eval_overall_accuracy': 0.5971030901958069, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7449548208495291, 'eval_accuracy_RV': 0.44106551992977155, 'eval_accuracy_RA': 0.5981656484791749, 'eval_accuracy_LA': 0.6127254577761923, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.05895511617838072, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3973549364896074, 'eval_accuracy_VSD': 0.3645530332563649, 'eval_accuracy_AK': 0.5570480691822266, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7041504709619297, 'eval_iou_RV': 0.43123741443315056, 'eval_iou_RA': 0.548515587853851, 'eval_iou_LA': 0.5750858022266724, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.05533449601246211, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.33215441115476557, 'eval_iou_VSD': 0.33179808400884303, 'eval_iou_AK': 0.5134371764874843, 'eval_runtime': 4.6062, 'eval_samples_per_second': 17.585, 'eval_steps_per_second': 8.901, 'epoch': 17.38}\n",
+      "{'loss': 0.0507, 'learning_rate': 3.0475000000000002e-05, 'epoch': 17.38}\n",
+      "{'loss': 0.0839, 'learning_rate': 3.045e-05, 'epoch': 17.39}\n",
+      "{'loss': 0.0362, 'learning_rate': 3.0425000000000004e-05, 'epoch': 17.39}\n",
+      "{'loss': 0.1221, 'learning_rate': 3.04e-05, 'epoch': 17.4}\n",
+      "{'loss': 0.0442, 'learning_rate': 3.0375000000000003e-05, 'epoch': 17.41}\n",
+      "{'loss': 0.2261, 'learning_rate': 3.035e-05, 'epoch': 17.41}\n",
+      "{'loss': 0.0592, 'learning_rate': 3.0325000000000002e-05, 'epoch': 17.42}\n",
+      "{'loss': 0.2581, 'learning_rate': 3.03e-05, 'epoch': 17.43}\n",
+      "{'loss': 0.0657, 'learning_rate': 3.0275000000000004e-05, 'epoch': 17.43}\n",
+      "{'loss': 0.0708, 'learning_rate': 3.025e-05, 'epoch': 17.44}\n",
+      "{'loss': 0.0749, 'learning_rate': 3.0225000000000003e-05, 'epoch': 17.44}\n",
+      "{'loss': 0.118, 'learning_rate': 3.02e-05, 'epoch': 17.45}\n",
+      "{'loss': 0.0969, 'learning_rate': 3.0175e-05, 'epoch': 17.46}\n",
+      "{'loss': 0.1457, 'learning_rate': 3.015e-05, 'epoch': 17.46}\n",
+      "{'loss': 0.1978, 'learning_rate': 3.0125000000000004e-05, 'epoch': 17.47}\n",
+      "{'loss': 0.1509, 'learning_rate': 3.01e-05, 'epoch': 17.48}\n",
+      "{'loss': 0.1518, 'learning_rate': 3.0075000000000003e-05, 'epoch': 17.48}\n",
+      "{'loss': 0.1035, 'learning_rate': 3.0050000000000002e-05, 'epoch': 17.49}\n",
+      "{'loss': 0.0743, 'learning_rate': 3.0025000000000005e-05, 'epoch': 17.49}\n",
+      "{'loss': 0.2577, 'learning_rate': 3e-05, 'epoch': 17.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "31f9074dc15e4cd0a31c307b9d99be6b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.39499714970588684, 'eval_mean_iou': 0.29052478547990435, 'eval_mean_accuracy': 0.34267391591564456, 'eval_overall_accuracy': 0.553286186623505, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6933910763347165, 'eval_accuracy_RV': 0.4298176148118136, 'eval_accuracy_RA': 0.5617126532325099, 'eval_accuracy_LA': 0.5683885729183104, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.05498628950786549, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.35842775692840645, 'eval_accuracy_VSD': 0.2918178546795814, 'eval_accuracy_AK': 0.4681973407432415, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.662939686668435, 'eval_iou_RV': 0.41946470561804483, 'eval_iou_RA': 0.5147607241047145, 'eval_iou_LA': 0.5391267991039255, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.051995905834186285, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.29967566752149644, 'eval_iou_VSD': 0.271911870516161, 'eval_iou_AK': 0.435897280911984, 'eval_runtime': 4.6269, 'eval_samples_per_second': 17.506, 'eval_steps_per_second': 8.861, 'epoch': 17.5}\n",
+      "{'loss': 0.1935, 'learning_rate': 2.9975000000000004e-05, 'epoch': 17.51}\n",
+      "{'loss': 0.1712, 'learning_rate': 2.995e-05, 'epoch': 17.51}\n",
+      "{'loss': 0.1078, 'learning_rate': 2.9925000000000002e-05, 'epoch': 17.52}\n",
+      "{'loss': 0.1423, 'learning_rate': 2.9900000000000002e-05, 'epoch': 17.52}\n",
+      "{'loss': 0.08, 'learning_rate': 2.9875000000000004e-05, 'epoch': 17.53}\n",
+      "{'loss': 0.0809, 'learning_rate': 2.985e-05, 'epoch': 17.54}\n",
+      "{'loss': 0.1136, 'learning_rate': 2.9825000000000003e-05, 'epoch': 17.54}\n",
+      "{'loss': 0.0494, 'learning_rate': 2.98e-05, 'epoch': 17.55}\n",
+      "{'loss': 0.0053, 'learning_rate': 2.9775000000000002e-05, 'epoch': 17.56}\n",
+      "{'loss': 0.1587, 'learning_rate': 2.975e-05, 'epoch': 17.56}\n",
+      "{'loss': 0.1021, 'learning_rate': 2.9725000000000004e-05, 'epoch': 17.57}\n",
+      "{'loss': 0.1687, 'learning_rate': 2.97e-05, 'epoch': 17.57}\n",
+      "{'loss': 0.1173, 'learning_rate': 2.9675000000000003e-05, 'epoch': 17.58}\n",
+      "{'loss': 0.0842, 'learning_rate': 2.965e-05, 'epoch': 17.59}\n",
+      "{'loss': 0.1238, 'learning_rate': 2.9625000000000002e-05, 'epoch': 17.59}\n",
+      "{'loss': 0.1137, 'learning_rate': 2.96e-05, 'epoch': 17.6}\n",
+      "{'loss': 0.0994, 'learning_rate': 2.9575000000000004e-05, 'epoch': 17.61}\n",
+      "{'loss': 0.184, 'learning_rate': 2.955e-05, 'epoch': 17.61}\n",
+      "{'loss': 0.0988, 'learning_rate': 2.9525000000000003e-05, 'epoch': 17.62}\n",
+      "{'loss': 0.019, 'learning_rate': 2.95e-05, 'epoch': 17.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9e7059d1f6774276b6fe2955910d534d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3993169069290161, 'eval_mean_iou': 0.3013647300292599, 'eval_mean_accuracy': 0.35443440679667193, 'eval_overall_accuracy': 0.5652255057461066, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7006474833020604, 'eval_accuracy_RV': 0.39817952448479715, 'eval_accuracy_RA': 0.5458708932880327, 'eval_accuracy_LA': 0.6469480443746184, 'eval_accuracy_VS': 0.0010323468685478321, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.03550295857988166, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3685948325635104, 'eval_accuracy_VSD': 0.3488469727411761, 'eval_accuracy_AK': 0.49872101176409483, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.672435351907932, 'eval_iou_RV': 0.38982645931935994, 'eval_iou_RA': 0.5174545920504293, 'eval_iou_LA': 0.600902961867863, 'eval_iou_VS': 0.0010241820768136557, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.03397086239038873, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3152526156600105, 'eval_iou_VSD': 0.3220697960935229, 'eval_iou_AK': 0.4620752089555381, 'eval_runtime': 4.5444, 'eval_samples_per_second': 17.824, 'eval_steps_per_second': 9.022, 'epoch': 17.62}\n",
+      "{'loss': 0.1623, 'learning_rate': 2.9475e-05, 'epoch': 17.63}\n",
+      "{'loss': 0.0634, 'learning_rate': 2.945e-05, 'epoch': 17.64}\n",
+      "{'loss': 0.0704, 'learning_rate': 2.9425000000000004e-05, 'epoch': 17.64}\n",
+      "{'loss': 0.136, 'learning_rate': 2.94e-05, 'epoch': 17.65}\n",
+      "{'loss': 0.0932, 'learning_rate': 2.9375000000000003e-05, 'epoch': 17.66}\n",
+      "{'loss': 0.1469, 'learning_rate': 2.935e-05, 'epoch': 17.66}\n",
+      "{'loss': 0.2079, 'learning_rate': 2.9325e-05, 'epoch': 17.67}\n",
+      "{'loss': 0.0789, 'learning_rate': 2.93e-05, 'epoch': 17.68}\n",
+      "{'loss': 0.115, 'learning_rate': 2.9275000000000003e-05, 'epoch': 17.68}\n",
+      "{'loss': 0.1882, 'learning_rate': 2.925e-05, 'epoch': 17.69}\n",
+      "{'loss': 0.1395, 'learning_rate': 2.9225000000000002e-05, 'epoch': 17.69}\n",
+      "{'loss': 0.1154, 'learning_rate': 2.9199999999999998e-05, 'epoch': 17.7}\n",
+      "{'loss': 0.1624, 'learning_rate': 2.9175e-05, 'epoch': 17.71}\n",
+      "{'loss': 0.0667, 'learning_rate': 2.915e-05, 'epoch': 17.71}\n",
+      "{'loss': 0.1739, 'learning_rate': 2.9125000000000003e-05, 'epoch': 17.72}\n",
+      "{'loss': 0.0826, 'learning_rate': 2.91e-05, 'epoch': 17.73}\n",
+      "{'loss': 0.1471, 'learning_rate': 2.9075000000000002e-05, 'epoch': 17.73}\n",
+      "{'loss': 0.0719, 'learning_rate': 2.9049999999999998e-05, 'epoch': 17.74}\n",
+      "{'loss': 0.0455, 'learning_rate': 2.9025e-05, 'epoch': 17.74}\n",
+      "{'loss': 0.1216, 'learning_rate': 2.9e-05, 'epoch': 17.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "175195b099084c01b9220d07fcbf6d26",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.4006803631782532, 'eval_mean_iou': 0.2962972797211025, 'eval_mean_accuracy': 0.35018430515782584, 'eval_overall_accuracy': 0.5593449698034574, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7087197699428138, 'eval_accuracy_RV': 0.4196885148283885, 'eval_accuracy_RA': 0.5463954548755982, 'eval_accuracy_LA': 0.5853789474406383, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.046218790590272764, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4082888279445728, 'eval_accuracy_VSD': 0.33343329235013647, 'eval_accuracy_AK': 0.4537194536058379, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.680046313888227, 'eval_iou_RV': 0.40888450295676615, 'eval_iou_RA': 0.5096434855427695, 'eval_iou_LA': 0.5526978466780349, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.043747758823830744, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3326057719866834, 'eval_iou_VSD': 0.30659148249762175, 'eval_iou_AK': 0.42505291455819383, 'eval_runtime': 4.5681, 'eval_samples_per_second': 17.732, 'eval_steps_per_second': 8.975, 'epoch': 17.75}\n",
+      "{'loss': 0.104, 'learning_rate': 2.8975000000000003e-05, 'epoch': 17.76}\n",
+      "{'loss': 0.0058, 'learning_rate': 2.895e-05, 'epoch': 17.76}\n",
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+      "{'loss': 0.0583, 'learning_rate': 2.8899999999999998e-05, 'epoch': 17.77}\n",
+      "{'loss': 0.0807, 'learning_rate': 2.8875e-05, 'epoch': 17.78}\n",
+      "{'loss': 0.0859, 'learning_rate': 2.885e-05, 'epoch': 17.79}\n",
+      "{'loss': 0.1484, 'learning_rate': 2.8825000000000003e-05, 'epoch': 17.79}\n",
+      "{'loss': 0.0704, 'learning_rate': 2.88e-05, 'epoch': 17.8}\n",
+      "{'loss': 0.115, 'learning_rate': 2.8775e-05, 'epoch': 17.81}\n",
+      "{'loss': 0.1681, 'learning_rate': 2.8749999999999997e-05, 'epoch': 17.81}\n",
+      "{'loss': 0.1471, 'learning_rate': 2.8725e-05, 'epoch': 17.82}\n",
+      "{'loss': 0.1032, 'learning_rate': 2.87e-05, 'epoch': 17.82}\n",
+      "{'loss': 0.1273, 'learning_rate': 2.8675000000000002e-05, 'epoch': 17.83}\n",
+      "{'loss': 0.044, 'learning_rate': 2.865e-05, 'epoch': 17.84}\n",
+      "{'loss': 0.1334, 'learning_rate': 2.8625e-05, 'epoch': 17.84}\n",
+      "{'loss': 0.1461, 'learning_rate': 2.86e-05, 'epoch': 17.85}\n",
+      "{'loss': 0.2014, 'learning_rate': 2.8575000000000003e-05, 'epoch': 17.86}\n",
+      "{'loss': 0.0573, 'learning_rate': 2.855e-05, 'epoch': 17.86}\n",
+      "{'loss': 0.1568, 'learning_rate': 2.8525000000000002e-05, 'epoch': 17.87}\n",
+      "{'loss': 0.0888, 'learning_rate': 2.8499999999999998e-05, 'epoch': 17.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "a9701d7ad44e44c7bf14d530a96ccfd3",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.381398469209671, 'eval_mean_iou': 0.3271937002997902, 'eval_mean_accuracy': 0.3921720025824893, 'eval_overall_accuracy': 0.6061487993871973, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.734158212045188, 'eval_accuracy_RV': 0.45190826104839255, 'eval_accuracy_RA': 0.6105291615891795, 'eval_accuracy_LA': 0.6515995581747954, 'eval_accuracy_VS': 0.002351456756136729, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.056231057872708906, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.466648022517321, 'eval_accuracy_VSD': 0.3859192730980298, 'eval_accuracy_AK': 0.5623750227231412, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6989834282545455, 'eval_iou_RV': 0.4405936668157966, 'eval_iou_RA': 0.5604646554071199, 'eval_iou_LA': 0.6025806349281879, 'eval_iou_VS': 0.0023313999772546345, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.052780411812516935, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3750861087544505, 'eval_iou_VSD': 0.3509715688279812, 'eval_iou_AK': 0.5153388285198395, 'eval_runtime': 4.5311, 'eval_samples_per_second': 17.877, 'eval_steps_per_second': 9.049, 'epoch': 17.88}\n",
+      "{'loss': 0.1094, 'learning_rate': 2.8475e-05, 'epoch': 17.88}\n",
+      "{'loss': 0.2214, 'learning_rate': 2.845e-05, 'epoch': 17.89}\n",
+      "{'loss': 0.0201, 'learning_rate': 2.8425000000000003e-05, 'epoch': 17.89}\n",
+      "{'loss': 0.0773, 'learning_rate': 2.84e-05, 'epoch': 17.9}\n",
+      "{'loss': 0.0516, 'learning_rate': 2.8375000000000002e-05, 'epoch': 17.91}\n",
+      "{'loss': 0.1564, 'learning_rate': 2.8349999999999998e-05, 'epoch': 17.91}\n",
+      "{'loss': 0.1862, 'learning_rate': 2.8325e-05, 'epoch': 17.92}\n",
+      "{'loss': 0.1186, 'learning_rate': 2.83e-05, 'epoch': 17.93}\n",
+      "{'loss': 0.1699, 'learning_rate': 2.8275000000000003e-05, 'epoch': 17.93}\n",
+      "{'loss': 0.1115, 'learning_rate': 2.825e-05, 'epoch': 17.94}\n",
+      "{'loss': 0.3214, 'learning_rate': 2.8225e-05, 'epoch': 17.94}\n",
+      "{'loss': 0.0743, 'learning_rate': 2.8199999999999998e-05, 'epoch': 17.95}\n",
+      "{'loss': 0.1423, 'learning_rate': 2.8175e-05, 'epoch': 17.96}\n",
+      "{'loss': 0.1331, 'learning_rate': 2.815e-05, 'epoch': 17.96}\n",
+      "{'loss': 0.1351, 'learning_rate': 2.8125000000000003e-05, 'epoch': 17.97}\n",
+      "{'loss': 0.1318, 'learning_rate': 2.8100000000000005e-05, 'epoch': 17.98}\n",
+      "{'loss': 0.1623, 'learning_rate': 2.8075e-05, 'epoch': 17.98}\n",
+      "{'loss': 0.0944, 'learning_rate': 2.8050000000000004e-05, 'epoch': 17.99}\n",
+      "{'loss': 0.124, 'learning_rate': 2.8025e-05, 'epoch': 17.99}\n",
+      "{'loss': 0.0926, 'learning_rate': 2.8000000000000003e-05, 'epoch': 18.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8ed8879de3a14d00b13a5b442b61e6d3",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3799093961715698, 'eval_mean_iou': 0.3352434198236371, 'eval_mean_accuracy': 0.4004830235227968, 'eval_overall_accuracy': 0.6139202707410542, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7131467002365603, 'eval_accuracy_RV': 0.5106969434673444, 'eval_accuracy_RA': 0.6253601317053094, 'eval_accuracy_LA': 0.6705898092056065, 'eval_accuracy_VS': 0.003785271851342051, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.05689854235820465, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.45547957563510394, 'eval_accuracy_VSD': 0.4144675682969982, 'eval_accuracy_AK': 0.5544056924714987, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6833440048479166, 'eval_iou_RV': 0.4927982655415592, 'eval_iou_RA': 0.5801015118224592, 'eval_iou_LA': 0.6186840435413505, 'eval_iou_VS': 0.0037546933667083854, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.05351931039163782, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3734752601951371, 'eval_iou_VSD': 0.3741185864901809, 'eval_iou_AK': 0.5078819418630585, 'eval_runtime': 4.5787, 'eval_samples_per_second': 17.69, 'eval_steps_per_second': 8.954, 'epoch': 18.0}\n",
+      "{'loss': 0.1383, 'learning_rate': 2.7975000000000002e-05, 'epoch': 18.01}\n",
+      "{'loss': 0.1976, 'learning_rate': 2.7950000000000005e-05, 'epoch': 18.01}\n",
+      "{'loss': 0.1589, 'learning_rate': 2.7925e-05, 'epoch': 18.02}\n",
+      "{'loss': 0.2887, 'learning_rate': 2.7900000000000004e-05, 'epoch': 18.02}\n",
+      "{'loss': 0.1166, 'learning_rate': 2.7875e-05, 'epoch': 18.03}\n",
+      "{'loss': 0.176, 'learning_rate': 2.7850000000000003e-05, 'epoch': 18.04}\n",
+      "{'loss': 0.1324, 'learning_rate': 2.7825000000000002e-05, 'epoch': 18.04}\n",
+      "{'loss': 0.1289, 'learning_rate': 2.7800000000000005e-05, 'epoch': 18.05}\n",
+      "{'loss': 0.0723, 'learning_rate': 2.7775e-05, 'epoch': 18.06}\n",
+      "{'loss': 0.0985, 'learning_rate': 2.7750000000000004e-05, 'epoch': 18.06}\n",
+      "{'loss': 0.1308, 'learning_rate': 2.7725e-05, 'epoch': 18.07}\n",
+      "{'loss': 0.0745, 'learning_rate': 2.7700000000000002e-05, 'epoch': 18.07}\n",
+      "{'loss': 0.097, 'learning_rate': 2.7675000000000002e-05, 'epoch': 18.08}\n",
+      "{'loss': 0.0416, 'learning_rate': 2.7650000000000005e-05, 'epoch': 18.09}\n",
+      "{'loss': 0.113, 'learning_rate': 2.7625e-05, 'epoch': 18.09}\n",
+      "{'loss': 0.1033, 'learning_rate': 2.7600000000000003e-05, 'epoch': 18.1}\n",
+      "{'loss': 0.139, 'learning_rate': 2.7575e-05, 'epoch': 18.11}\n",
+      "{'loss': 0.1375, 'learning_rate': 2.7550000000000002e-05, 'epoch': 18.11}\n",
+      "{'loss': 0.1836, 'learning_rate': 2.7525e-05, 'epoch': 18.12}\n",
+      "{'loss': 0.2018, 'learning_rate': 2.7500000000000004e-05, 'epoch': 18.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "432352a90b8f4cb8826f874402ab025a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.406538724899292, 'eval_mean_iou': 0.283844836776348, 'eval_mean_accuracy': 0.33200585732360527, 'eval_overall_accuracy': 0.5520792986525699, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7388334859689578, 'eval_accuracy_RV': 0.3802402745293038, 'eval_accuracy_RA': 0.49555938440680153, 'eval_accuracy_LA': 0.600163626259785, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.045406985134940105, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3682339780600462, 'eval_accuracy_VSD': 0.2821693105826611, 'eval_accuracy_AK': 0.409451528293557, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7009848699800394, 'eval_iou_RV': 0.3726773473964781, 'eval_iou_RA': 0.4791018924159024, 'eval_iou_LA': 0.5666956559762515, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.04329130905901171, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.31064636178908195, 'eval_iou_VSD': 0.26376907066219085, 'eval_iou_AK': 0.38512669726087206, 'eval_runtime': 4.6221, 'eval_samples_per_second': 17.525, 'eval_steps_per_second': 8.87, 'epoch': 18.12}\n",
+      "{'loss': 0.1261, 'learning_rate': 2.7475e-05, 'epoch': 18.13}\n",
+      "{'loss': 0.0925, 'learning_rate': 2.7450000000000003e-05, 'epoch': 18.14}\n",
+      "{'loss': 0.1569, 'learning_rate': 2.7425e-05, 'epoch': 18.14}\n",
+      "{'loss': 0.0399, 'learning_rate': 2.7400000000000002e-05, 'epoch': 18.15}\n",
+      "{'loss': 0.0475, 'learning_rate': 2.7375e-05, 'epoch': 18.16}\n",
+      "{'loss': 0.1806, 'learning_rate': 2.7350000000000004e-05, 'epoch': 18.16}\n",
+      "{'loss': 0.073, 'learning_rate': 2.7325e-05, 'epoch': 18.17}\n",
+      "{'loss': 0.134, 'learning_rate': 2.7300000000000003e-05, 'epoch': 18.18}\n",
+      "{'loss': 0.0594, 'learning_rate': 2.7275e-05, 'epoch': 18.18}\n",
+      "{'loss': 0.1518, 'learning_rate': 2.725e-05, 'epoch': 18.19}\n",
+      "{'loss': 0.1351, 'learning_rate': 2.7225e-05, 'epoch': 18.19}\n",
+      "{'loss': 0.0776, 'learning_rate': 2.7200000000000004e-05, 'epoch': 18.2}\n",
+      "{'loss': 0.1106, 'learning_rate': 2.7175e-05, 'epoch': 18.21}\n",
+      "{'loss': 0.0731, 'learning_rate': 2.7150000000000003e-05, 'epoch': 18.21}\n",
+      "{'loss': 0.0049, 'learning_rate': 2.7125000000000002e-05, 'epoch': 18.22}\n",
+      "{'loss': 0.0673, 'learning_rate': 2.7100000000000005e-05, 'epoch': 18.23}\n",
+      "{'loss': 0.1053, 'learning_rate': 2.7075e-05, 'epoch': 18.23}\n",
+      "{'loss': 0.1294, 'learning_rate': 2.7050000000000004e-05, 'epoch': 18.24}\n",
+      "{'loss': 0.1196, 'learning_rate': 2.7025e-05, 'epoch': 18.24}\n",
+      "{'loss': 0.0521, 'learning_rate': 2.7000000000000002e-05, 'epoch': 18.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "52a639cdfba64106b2b7d6def66b3708",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
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+      "{'loss': 0.0729, 'learning_rate': 2.6975000000000002e-05, 'epoch': 18.26}\n",
+      "{'loss': 0.0646, 'learning_rate': 2.6950000000000005e-05, 'epoch': 18.26}\n",
+      "{'loss': 0.077, 'learning_rate': 2.6925e-05, 'epoch': 18.27}\n",
+      "{'loss': 0.1384, 'learning_rate': 2.6900000000000003e-05, 'epoch': 18.27}\n",
+      "{'loss': 0.1038, 'learning_rate': 2.6875e-05, 'epoch': 18.28}\n",
+      "{'loss': 0.109, 'learning_rate': 2.6850000000000002e-05, 'epoch': 18.29}\n",
+      "{'loss': 0.1641, 'learning_rate': 2.6825e-05, 'epoch': 18.29}\n",
+      "{'loss': 0.0426, 'learning_rate': 2.6800000000000004e-05, 'epoch': 18.3}\n",
+      "{'loss': 0.2535, 'learning_rate': 2.6775e-05, 'epoch': 18.31}\n",
+      "{'loss': 0.1391, 'learning_rate': 2.6750000000000003e-05, 'epoch': 18.31}\n",
+      "{'loss': 0.1376, 'learning_rate': 2.6725e-05, 'epoch': 18.32}\n",
+      "{'loss': 0.1378, 'learning_rate': 2.6700000000000002e-05, 'epoch': 18.32}\n",
+      "{'loss': 0.1613, 'learning_rate': 2.6675e-05, 'epoch': 18.33}\n",
+      "{'loss': 0.0472, 'learning_rate': 2.6650000000000004e-05, 'epoch': 18.34}\n",
+      "{'loss': 0.1171, 'learning_rate': 2.6625e-05, 'epoch': 18.34}\n",
+      "{'loss': 0.2208, 'learning_rate': 2.6600000000000003e-05, 'epoch': 18.35}\n",
+      "{'loss': 0.118, 'learning_rate': 2.6575e-05, 'epoch': 18.36}\n",
+      "{'loss': 0.1052, 'learning_rate': 2.655e-05, 'epoch': 18.36}\n",
+      "{'loss': 0.1113, 'learning_rate': 2.6525e-05, 'epoch': 18.37}\n",
+      "{'loss': 0.0515, 'learning_rate': 2.6500000000000004e-05, 'epoch': 18.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "86968d5f2b904adda61071da8a8582ea",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3915819823741913, 'eval_mean_iou': 0.3096925891548107, 'eval_mean_accuracy': 0.3631792001219528, 'eval_overall_accuracy': 0.5900251331309411, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7416115040525504, 'eval_accuracy_RV': 0.45097055194386637, 'eval_accuracy_RA': 0.5675494096664595, 'eval_accuracy_LA': 0.6246406739892563, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.031389810939529514, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.35033559468822173, 'eval_accuracy_VSD': 0.3406528323387411, 'eval_accuracy_AK': 0.5246416236009037, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.702275935759388, 'eval_iou_RV': 0.43961365666249264, 'eval_iou_RA': 0.5381075078762977, 'eval_iou_LA': 0.5873696841453344, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.03011109957429135, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.30180614275055956, 'eval_iou_VSD': 0.3154259454656522, 'eval_iou_AK': 0.4919085084689017, 'eval_runtime': 4.6424, 'eval_samples_per_second': 17.448, 'eval_steps_per_second': 8.832, 'epoch': 18.38}\n",
+      "{'loss': 0.1607, 'learning_rate': 2.6475e-05, 'epoch': 18.38}\n",
+      "{'loss': 0.1195, 'learning_rate': 2.6450000000000003e-05, 'epoch': 18.39}\n",
+      "{'loss': 0.1241, 'learning_rate': 2.6425e-05, 'epoch': 18.39}\n",
+      "{'loss': 0.0553, 'learning_rate': 2.64e-05, 'epoch': 18.4}\n",
+      "{'loss': 0.1531, 'learning_rate': 2.6375e-05, 'epoch': 18.41}\n",
+      "{'loss': 0.135, 'learning_rate': 2.6350000000000004e-05, 'epoch': 18.41}\n",
+      "{'loss': 0.2925, 'learning_rate': 2.6325e-05, 'epoch': 18.42}\n",
+      "{'loss': 0.1012, 'learning_rate': 2.6300000000000002e-05, 'epoch': 18.43}\n",
+      "{'loss': 0.1247, 'learning_rate': 2.6275e-05, 'epoch': 18.43}\n",
+      "{'loss': 0.1232, 'learning_rate': 2.625e-05, 'epoch': 18.44}\n",
+      "{'loss': 0.1469, 'learning_rate': 2.6225e-05, 'epoch': 18.44}\n",
+      "{'loss': 0.0993, 'learning_rate': 2.6200000000000003e-05, 'epoch': 18.45}\n",
+      "{'loss': 0.1276, 'learning_rate': 2.6175e-05, 'epoch': 18.46}\n",
+      "{'loss': 0.1335, 'learning_rate': 2.6150000000000002e-05, 'epoch': 18.46}\n",
+      "{'loss': 0.0375, 'learning_rate': 2.6124999999999998e-05, 'epoch': 18.47}\n",
+      "{'loss': 0.2096, 'learning_rate': 2.61e-05, 'epoch': 18.48}\n",
+      "{'loss': 0.0069, 'learning_rate': 2.6075e-05, 'epoch': 18.48}\n",
+      "{'loss': 0.0658, 'learning_rate': 2.6050000000000003e-05, 'epoch': 18.49}\n",
+      "{'loss': 0.0998, 'learning_rate': 2.6025e-05, 'epoch': 18.49}\n",
+      "{'loss': 0.1245, 'learning_rate': 2.6000000000000002e-05, 'epoch': 18.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "24471ce75e1d4bef9965b705c9a5c29b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.38596272468566895, 'eval_mean_iou': 0.32965886782459014, 'eval_mean_accuracy': 0.39152766187797305, 'eval_overall_accuracy': 0.6129695286483071, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7483988174965173, 'eval_accuracy_RV': 0.4767951527652443, 'eval_accuracy_RA': 0.5930874888026276, 'eval_accuracy_LA': 0.6622284044209963, 'eval_accuracy_VS': 0.004817618719889883, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.060326165391831436, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4254113741339492, 'eval_accuracy_VSD': 0.3978693735568417, 'eval_accuracy_AK': 0.5463422234918327, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.707384881730799, 'eval_iou_RV': 0.4619145111577971, 'eval_iou_RA': 0.5594761613843164, 'eval_iou_LA': 0.6147285328306429, 'eval_iou_VS': 0.004761364924611722, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.05671160858136182, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3545883839143381, 'eval_iou_VSD': 0.36142551655565996, 'eval_iou_AK': 0.5052565849909638, 'eval_runtime': 4.5657, 'eval_samples_per_second': 17.741, 'eval_steps_per_second': 8.98, 'epoch': 18.5}\n",
+      "{'loss': 0.1746, 'learning_rate': 2.5974999999999998e-05, 'epoch': 18.51}\n",
+      "{'loss': 0.1249, 'learning_rate': 2.595e-05, 'epoch': 18.51}\n",
+      "{'loss': 0.0444, 'learning_rate': 2.5925e-05, 'epoch': 18.52}\n",
+      "{'loss': 0.1, 'learning_rate': 2.5900000000000003e-05, 'epoch': 18.52}\n",
+      "{'loss': 0.1425, 'learning_rate': 2.5875e-05, 'epoch': 18.53}\n",
+      "{'loss': 0.1118, 'learning_rate': 2.585e-05, 'epoch': 18.54}\n",
+      "{'loss': 0.1143, 'learning_rate': 2.5824999999999998e-05, 'epoch': 18.54}\n",
+      "{'loss': 0.0408, 'learning_rate': 2.58e-05, 'epoch': 18.55}\n",
+      "{'loss': 0.3069, 'learning_rate': 2.5775e-05, 'epoch': 18.56}\n",
+      "{'loss': 0.1686, 'learning_rate': 2.5750000000000002e-05, 'epoch': 18.56}\n",
+      "{'loss': 0.0836, 'learning_rate': 2.5725e-05, 'epoch': 18.57}\n",
+      "{'loss': 0.0911, 'learning_rate': 2.57e-05, 'epoch': 18.57}\n",
+      "{'loss': 0.063, 'learning_rate': 2.5675e-05, 'epoch': 18.58}\n",
+      "{'loss': 0.1679, 'learning_rate': 2.5650000000000003e-05, 'epoch': 18.59}\n",
+      "{'loss': 0.1408, 'learning_rate': 2.5625e-05, 'epoch': 18.59}\n",
+      "{'loss': 0.0739, 'learning_rate': 2.5600000000000002e-05, 'epoch': 18.6}\n",
+      "{'loss': 0.13, 'learning_rate': 2.5574999999999998e-05, 'epoch': 18.61}\n",
+      "{'loss': 0.2671, 'learning_rate': 2.555e-05, 'epoch': 18.61}\n",
+      "{'loss': 0.1227, 'learning_rate': 2.5525e-05, 'epoch': 18.62}\n",
+      "{'loss': 0.2029, 'learning_rate': 2.5500000000000003e-05, 'epoch': 18.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2a4e3f9c91e34955910f594bfb760c1a",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.39912641048431396, 'eval_mean_iou': 0.29942136360468374, 'eval_mean_accuracy': 0.3515280905550978, 'eval_overall_accuracy': 0.5643899887263356, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7116156207397508, 'eval_accuracy_RV': 0.42415145766957035, 'eval_accuracy_RA': 0.5090708803757475, 'eval_accuracy_LA': 0.6092265314663246, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.05154062635300909, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3790145063510393, 'eval_accuracy_VSD': 0.29905988544696677, 'eval_accuracy_AK': 0.5316013971485704, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6796955526033671, 'eval_iou_RV': 0.41385816584156193, 'eval_iou_RA': 0.4891544356409923, 'eval_iou_LA': 0.5751609539354371, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.04875842648690161, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3206756529836506, 'eval_iou_VSD': 0.2786560022353393, 'eval_iou_AK': 0.48767580992427106, 'eval_runtime': 4.587, 'eval_samples_per_second': 17.659, 'eval_steps_per_second': 8.938, 'epoch': 18.62}\n",
+      "{'loss': 0.1636, 'learning_rate': 2.5475e-05, 'epoch': 18.63}\n",
+      "{'loss': 0.0529, 'learning_rate': 2.5450000000000002e-05, 'epoch': 18.64}\n",
+      "{'loss': 0.0565, 'learning_rate': 2.5424999999999998e-05, 'epoch': 18.64}\n",
+      "{'loss': 0.1428, 'learning_rate': 2.54e-05, 'epoch': 18.65}\n",
+      "{'loss': 0.0762, 'learning_rate': 2.5375e-05, 'epoch': 18.66}\n",
+      "{'loss': 0.1431, 'learning_rate': 2.5350000000000003e-05, 'epoch': 18.66}\n",
+      "{'loss': 0.004, 'learning_rate': 2.5325e-05, 'epoch': 18.67}\n",
+      "{'loss': 0.1264, 'learning_rate': 2.5300000000000002e-05, 'epoch': 18.68}\n",
+      "{'loss': 0.0771, 'learning_rate': 2.5274999999999998e-05, 'epoch': 18.68}\n",
+      "{'loss': 0.1238, 'learning_rate': 2.525e-05, 'epoch': 18.69}\n",
+      "{'loss': 0.0117, 'learning_rate': 2.5225e-05, 'epoch': 18.69}\n",
+      "{'loss': 0.1357, 'learning_rate': 2.5200000000000003e-05, 'epoch': 18.7}\n",
+      "{'loss': 0.1114, 'learning_rate': 2.5175e-05, 'epoch': 18.71}\n",
+      "{'loss': 0.19, 'learning_rate': 2.515e-05, 'epoch': 18.71}\n",
+      "{'loss': 0.1433, 'learning_rate': 2.5124999999999997e-05, 'epoch': 18.72}\n",
+      "{'loss': 0.1217, 'learning_rate': 2.51e-05, 'epoch': 18.73}\n",
+      "{'loss': 0.0432, 'learning_rate': 2.5075e-05, 'epoch': 18.73}\n",
+      "{'loss': 0.2202, 'learning_rate': 2.5050000000000002e-05, 'epoch': 18.74}\n",
+      "{'loss': 0.1194, 'learning_rate': 2.5025e-05, 'epoch': 18.74}\n",
+      "{'loss': 0.1229, 'learning_rate': 2.5e-05, 'epoch': 18.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "0e13f4968bf643beb3dbe50080d2478d",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.39152607321739197, 'eval_mean_iou': 0.32266518288367735, 'eval_mean_accuracy': 0.3838076732416479, 'eval_overall_accuracy': 0.6094619259573418, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.755010873423801, 'eval_accuracy_RV': 0.4812765121518506, 'eval_accuracy_RA': 0.5982725783412556, 'eval_accuracy_LA': 0.6504298190849278, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.05695266272189349, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.47529048787528866, 'eval_accuracy_VSD': 0.32744324826821003, 'eval_accuracy_AK': 0.4934005505492508, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7127031528734613, 'eval_iou_RV': 0.46749394005348854, 'eval_iou_RA': 0.5584000572457273, 'eval_iou_LA': 0.6074795997808599, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.05333220711208717, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3841666605901955, 'eval_iou_VSD': 0.30323458555787747, 'eval_iou_AK': 0.46250680850675374, 'eval_runtime': 4.6155, 'eval_samples_per_second': 17.549, 'eval_steps_per_second': 8.883, 'epoch': 18.75}\n",
+      "{'loss': 0.1274, 'learning_rate': 2.4975e-05, 'epoch': 18.76}\n",
+      "{'loss': 0.1358, 'learning_rate': 2.495e-05, 'epoch': 18.76}\n",
+      "{'loss': 0.0047, 'learning_rate': 2.4925000000000003e-05, 'epoch': 18.77}\n",
+      "{'loss': 0.1585, 'learning_rate': 2.4900000000000002e-05, 'epoch': 18.77}\n",
+      "{'loss': 0.0899, 'learning_rate': 2.4875e-05, 'epoch': 18.78}\n",
+      "{'loss': 0.0678, 'learning_rate': 2.485e-05, 'epoch': 18.79}\n",
+      "{'loss': 0.1451, 'learning_rate': 2.4825e-05, 'epoch': 18.79}\n",
+      "{'loss': 0.0664, 'learning_rate': 2.48e-05, 'epoch': 18.8}\n",
+      "{'loss': 0.1211, 'learning_rate': 2.4775000000000003e-05, 'epoch': 18.81}\n",
+      "{'loss': 0.1206, 'learning_rate': 2.4750000000000002e-05, 'epoch': 18.81}\n",
+      "{'loss': 0.0993, 'learning_rate': 2.4725e-05, 'epoch': 18.82}\n",
+      "{'loss': 0.043, 'learning_rate': 2.47e-05, 'epoch': 18.82}\n",
+      "{'loss': 0.1239, 'learning_rate': 2.4675e-05, 'epoch': 18.83}\n",
+      "{'loss': 0.1563, 'learning_rate': 2.465e-05, 'epoch': 18.84}\n",
+      "{'loss': 0.3513, 'learning_rate': 2.4625000000000002e-05, 'epoch': 18.84}\n",
+      "{'loss': 0.1161, 'learning_rate': 2.46e-05, 'epoch': 18.85}\n",
+      "{'loss': 0.1443, 'learning_rate': 2.4575e-05, 'epoch': 18.86}\n",
+      "{'loss': 0.1618, 'learning_rate': 2.455e-05, 'epoch': 18.86}\n",
+      "{'loss': 0.2001, 'learning_rate': 2.4525e-05, 'epoch': 18.87}\n",
+      "{'loss': 0.1025, 'learning_rate': 2.45e-05, 'epoch': 18.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "6ff1ef1e84704cccbc311cda34330f48",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3834681212902069, 'eval_mean_iou': 0.30846422335695955, 'eval_mean_accuracy': 0.3645563377030695, 'eval_overall_accuracy': 0.5820713573189019, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7277967370779277, 'eval_accuracy_RV': 0.4335208751542386, 'eval_accuracy_RA': 0.5872285393784349, 'eval_accuracy_LA': 0.6332988014462229, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.050855101746283736, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.42080145785219397, 'eval_accuracy_VSD': 0.3443413200587759, 'eval_accuracy_AK': 0.44772054431661773, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6903576820066751, 'eval_iou_RV': 0.42354184784238463, 'eval_iou_RA': 0.5503013733853647, 'eval_iou_LA': 0.5938399136667969, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.047994415690547534, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.34695258922063044, 'eval_iou_VSD': 0.3185007974481659, 'eval_iou_AK': 0.4216178376659901, 'eval_runtime': 4.4869, 'eval_samples_per_second': 18.053, 'eval_steps_per_second': 9.138, 'epoch': 18.88}\n",
+      "{'loss': 0.1871, 'learning_rate': 2.4475000000000002e-05, 'epoch': 18.88}\n",
+      "{'loss': 0.1092, 'learning_rate': 2.445e-05, 'epoch': 18.89}\n",
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+      "{'loss': 0.2938, 'learning_rate': 2.44e-05, 'epoch': 18.9}\n",
+      "{'loss': 0.1177, 'learning_rate': 2.4375e-05, 'epoch': 18.91}\n",
+      "{'loss': 0.1073, 'learning_rate': 2.435e-05, 'epoch': 18.91}\n",
+      "{'loss': 0.076, 'learning_rate': 2.4325000000000002e-05, 'epoch': 18.92}\n",
+      "{'loss': 0.1509, 'learning_rate': 2.43e-05, 'epoch': 18.93}\n",
+      "{'loss': 0.2515, 'learning_rate': 2.4275e-05, 'epoch': 18.93}\n",
+      "{'loss': 0.1698, 'learning_rate': 2.425e-05, 'epoch': 18.94}\n",
+      "{'loss': 0.1222, 'learning_rate': 2.4225e-05, 'epoch': 18.94}\n",
+      "{'loss': 0.0972, 'learning_rate': 2.4200000000000002e-05, 'epoch': 18.95}\n",
+      "{'loss': 0.1375, 'learning_rate': 2.4175e-05, 'epoch': 18.96}\n",
+      "{'loss': 0.0549, 'learning_rate': 2.415e-05, 'epoch': 18.96}\n",
+      "{'loss': 0.0463, 'learning_rate': 2.4125e-05, 'epoch': 18.97}\n",
+      "{'loss': 0.0623, 'learning_rate': 2.41e-05, 'epoch': 18.98}\n",
+      "{'loss': 0.1745, 'learning_rate': 2.4075e-05, 'epoch': 18.98}\n",
+      "{'loss': 0.0038, 'learning_rate': 2.4050000000000002e-05, 'epoch': 18.99}\n",
+      "{'loss': 0.1943, 'learning_rate': 2.4025e-05, 'epoch': 18.99}\n",
+      "{'loss': 0.0738, 'learning_rate': 2.4e-05, 'epoch': 19.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "1ee5ccaad34b403fa5c1eba9af9ef964",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.41162410378456116, 'eval_mean_iou': 0.2848832963029761, 'eval_mean_accuracy': 0.3351992162264082, 'eval_overall_accuracy': 0.5213104174285226, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6625054814585005, 'eval_accuracy_RV': 0.365790959931736, 'eval_accuracy_RA': 0.47703227264290265, 'eval_accuracy_LA': 0.5709733189717273, 'eval_accuracy_VS': 0.00028676301904106445, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.0743252994660124, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4179958140877598, 'eval_accuracy_VSD': 0.3456682760068372, 'eval_accuracy_AK': 0.4374139766795648, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6380481827675715, 'eval_iou_RV': 0.35813402772873504, 'eval_iou_RA': 0.46069762638681594, 'eval_iou_LA': 0.5420149596376342, 'eval_iou_VS': 0.00028396183552930487, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.06907536256182413, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3378665130489948, 'eval_iou_VSD': 0.31786782853282225, 'eval_iou_AK': 0.40972779683281035, 'eval_runtime': 4.4392, 'eval_samples_per_second': 18.247, 'eval_steps_per_second': 9.236, 'epoch': 19.0}\n",
+      "{'loss': 0.1413, 'learning_rate': 2.3975e-05, 'epoch': 19.01}\n",
+      "{'loss': 0.1054, 'learning_rate': 2.395e-05, 'epoch': 19.01}\n",
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+      "{'loss': 0.1695, 'learning_rate': 2.39e-05, 'epoch': 19.02}\n",
+      "{'loss': 0.2665, 'learning_rate': 2.3875e-05, 'epoch': 19.03}\n",
+      "{'loss': 0.0503, 'learning_rate': 2.385e-05, 'epoch': 19.04}\n",
+      "{'loss': 0.1866, 'learning_rate': 2.3825e-05, 'epoch': 19.04}\n",
+      "{'loss': 0.0535, 'learning_rate': 2.38e-05, 'epoch': 19.05}\n",
+      "{'loss': 0.0883, 'learning_rate': 2.3775e-05, 'epoch': 19.06}\n",
+      "{'loss': 0.1194, 'learning_rate': 2.375e-05, 'epoch': 19.06}\n",
+      "{'loss': 0.1433, 'learning_rate': 2.3725e-05, 'epoch': 19.07}\n",
+      "{'loss': 0.0576, 'learning_rate': 2.37e-05, 'epoch': 19.07}\n",
+      "{'loss': 0.1359, 'learning_rate': 2.3675e-05, 'epoch': 19.08}\n",
+      "{'loss': 0.3147, 'learning_rate': 2.365e-05, 'epoch': 19.09}\n",
+      "{'loss': 0.1034, 'learning_rate': 2.3624999999999998e-05, 'epoch': 19.09}\n",
+      "{'loss': 0.1606, 'learning_rate': 2.36e-05, 'epoch': 19.1}\n",
+      "{'loss': 0.0637, 'learning_rate': 2.3575e-05, 'epoch': 19.11}\n",
+      "{'loss': 0.1446, 'learning_rate': 2.355e-05, 'epoch': 19.11}\n",
+      "{'loss': 0.0845, 'learning_rate': 2.3525e-05, 'epoch': 19.12}\n",
+      "{'loss': 0.2782, 'learning_rate': 2.35e-05, 'epoch': 19.12}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "797195c902004f0782cbae679035e0a6",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3842342495918274, 'eval_mean_iou': 0.3338145140397865, 'eval_mean_accuracy': 0.4005078205487543, 'eval_overall_accuracy': 0.6216990450924939, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7716849481386906, 'eval_accuracy_RV': 0.4700945996549967, 'eval_accuracy_RA': 0.6389866277146062, 'eval_accuracy_LA': 0.6424440343306417, 'eval_accuracy_VS': 0.02575131910988759, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.07138475970558522, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.47787961893764436, 'eval_accuracy_VSD': 0.40407682850031484, 'eval_accuracy_AK': 0.5027754693951749, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7244277508042468, 'eval_iou_RV': 0.45765358187123584, 'eval_iou_RA': 0.577110901358251, 'eval_iou_LA': 0.5993011289455495, 'eval_iou_VS': 0.025287226852894796, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.06667565336074276, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.38101403304346576, 'eval_iou_VSD': 0.3685225322548664, 'eval_iou_AK': 0.4719668459463989, 'eval_runtime': 4.5168, 'eval_samples_per_second': 17.933, 'eval_steps_per_second': 9.077, 'epoch': 19.12}\n",
+      "{'loss': 0.1187, 'learning_rate': 2.3475e-05, 'epoch': 19.13}\n",
+      "{'loss': 0.1988, 'learning_rate': 2.345e-05, 'epoch': 19.14}\n",
+      "{'loss': 0.0811, 'learning_rate': 2.3425000000000004e-05, 'epoch': 19.14}\n",
+      "{'loss': 0.1207, 'learning_rate': 2.3400000000000003e-05, 'epoch': 19.15}\n",
+      "{'loss': 0.1243, 'learning_rate': 2.3375000000000002e-05, 'epoch': 19.16}\n",
+      "{'loss': 0.0767, 'learning_rate': 2.3350000000000002e-05, 'epoch': 19.16}\n",
+      "{'loss': 0.0039, 'learning_rate': 2.3325e-05, 'epoch': 19.17}\n",
+      "{'loss': 0.0834, 'learning_rate': 2.3300000000000004e-05, 'epoch': 19.18}\n",
+      "{'loss': 0.1297, 'learning_rate': 2.3275000000000003e-05, 'epoch': 19.18}\n",
+      "{'loss': 0.067, 'learning_rate': 2.3250000000000003e-05, 'epoch': 19.19}\n",
+      "{'loss': 0.1573, 'learning_rate': 2.3225000000000002e-05, 'epoch': 19.19}\n",
+      "{'loss': 0.1365, 'learning_rate': 2.32e-05, 'epoch': 19.2}\n",
+      "{'loss': 0.0986, 'learning_rate': 2.3175e-05, 'epoch': 19.21}\n",
+      "{'loss': 0.1443, 'learning_rate': 2.3150000000000004e-05, 'epoch': 19.21}\n",
+      "{'loss': 0.1016, 'learning_rate': 2.3125000000000003e-05, 'epoch': 19.22}\n",
+      "{'loss': 0.1164, 'learning_rate': 2.3100000000000002e-05, 'epoch': 19.23}\n",
+      "{'loss': 0.0955, 'learning_rate': 2.3075000000000002e-05, 'epoch': 19.23}\n",
+      "{'loss': 0.1257, 'learning_rate': 2.305e-05, 'epoch': 19.24}\n",
+      "{'loss': 0.1059, 'learning_rate': 2.3025e-05, 'epoch': 19.24}\n",
+      "{'loss': 0.1912, 'learning_rate': 2.3000000000000003e-05, 'epoch': 19.25}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "b8eb83e5dada4c8598635d357ff02b5b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3942511975765228, 'eval_mean_iou': 0.3115995174712182, 'eval_mean_accuracy': 0.3675817321694435, 'eval_overall_accuracy': 0.5802369525186145, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7226106061374437, 'eval_accuracy_RV': 0.43487449124293265, 'eval_accuracy_RA': 0.5554723878850484, 'eval_accuracy_LA': 0.6261877482694036, 'eval_accuracy_VS': 0.00476026611608167, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.062346658969548274, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4142609699769053, 'eval_accuracy_VSD': 0.34606561309862954, 'eval_accuracy_AK': 0.5092385799984418, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6845564894734648, 'eval_iou_RV': 0.42478787515365934, 'eval_iou_RA': 0.5283255296284924, 'eval_iou_LA': 0.5869585838010427, 'eval_iou_VS': 0.004695632496039828, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.05865480898151763, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.34377690436084596, 'eval_iou_VSD': 0.3207496039356291, 'eval_iou_AK': 0.47508926435270854, 'eval_runtime': 4.6548, 'eval_samples_per_second': 17.401, 'eval_steps_per_second': 8.808, 'epoch': 19.25}\n",
+      "{'loss': 0.1733, 'learning_rate': 2.2975000000000003e-05, 'epoch': 19.26}\n",
+      "{'loss': 0.0534, 'learning_rate': 2.2950000000000002e-05, 'epoch': 19.26}\n",
+      "{'loss': 0.1115, 'learning_rate': 2.2925e-05, 'epoch': 19.27}\n",
+      "{'loss': 0.0612, 'learning_rate': 2.29e-05, 'epoch': 19.27}\n",
+      "{'loss': 0.1591, 'learning_rate': 2.2875e-05, 'epoch': 19.28}\n",
+      "{'loss': 0.1495, 'learning_rate': 2.2850000000000003e-05, 'epoch': 19.29}\n",
+      "{'loss': 0.0997, 'learning_rate': 2.2825000000000003e-05, 'epoch': 19.29}\n",
+      "{'loss': 0.1208, 'learning_rate': 2.2800000000000002e-05, 'epoch': 19.3}\n",
+      "{'loss': 0.1093, 'learning_rate': 2.2775e-05, 'epoch': 19.31}\n",
+      "{'loss': 0.1439, 'learning_rate': 2.275e-05, 'epoch': 19.31}\n",
+      "{'loss': 0.0734, 'learning_rate': 2.2725000000000003e-05, 'epoch': 19.32}\n",
+      "{'loss': 0.0566, 'learning_rate': 2.2700000000000003e-05, 'epoch': 19.32}\n",
+      "{'loss': 0.1402, 'learning_rate': 2.2675000000000002e-05, 'epoch': 19.33}\n",
+      "{'loss': 0.0982, 'learning_rate': 2.265e-05, 'epoch': 19.34}\n",
+      "{'loss': 0.1885, 'learning_rate': 2.2625e-05, 'epoch': 19.34}\n",
+      "{'loss': 0.1568, 'learning_rate': 2.26e-05, 'epoch': 19.35}\n",
+      "{'loss': 0.0788, 'learning_rate': 2.2575000000000003e-05, 'epoch': 19.36}\n",
+      "{'loss': 0.1652, 'learning_rate': 2.2550000000000003e-05, 'epoch': 19.36}\n",
+      "{'loss': 0.1284, 'learning_rate': 2.2525000000000002e-05, 'epoch': 19.37}\n",
+      "{'loss': 0.1143, 'learning_rate': 2.25e-05, 'epoch': 19.38}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8c832820a40e4ad4902a24124e054077",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.3765915632247925, 'eval_mean_iou': 0.33260067256604703, 'eval_mean_accuracy': 0.39524872159310653, 'eval_overall_accuracy': 0.6140133163398891, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7472600165264109, 'eval_accuracy_RV': 0.4982335463513754, 'eval_accuracy_RA': 0.6023480183677258, 'eval_accuracy_LA': 0.6387701617052807, 'eval_accuracy_VS': 0.0020646937370956643, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.07759056140857266, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4534046622401848, 'eval_accuracy_VSD': 0.39785437970432125, 'eval_accuracy_AK': 0.534961175890098, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7057299278555788, 'eval_iou_RV': 0.483002670594449, 'eval_iou_RA': 0.5603362524257997, 'eval_iou_LA': 0.5956757344661685, 'eval_iou_VS': 0.0020407006405532566, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.07214143142286855, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.370464010614381, 'eval_iou_VSD': 0.36613955927198466, 'eval_iou_AK': 0.5030771109347335, 'eval_runtime': 4.4535, 'eval_samples_per_second': 18.188, 'eval_steps_per_second': 9.206, 'epoch': 19.38}\n",
+      "{'loss': 0.1759, 'learning_rate': 2.2475e-05, 'epoch': 19.38}\n",
+      "{'loss': 0.1356, 'learning_rate': 2.245e-05, 'epoch': 19.39}\n",
+      "{'loss': 0.2093, 'learning_rate': 2.2425000000000003e-05, 'epoch': 19.39}\n",
+      "{'loss': 0.1066, 'learning_rate': 2.2400000000000002e-05, 'epoch': 19.4}\n",
+      "{'loss': 0.143, 'learning_rate': 2.2375000000000002e-05, 'epoch': 19.41}\n",
+      "{'loss': 0.1833, 'learning_rate': 2.235e-05, 'epoch': 19.41}\n",
+      "{'loss': 0.0744, 'learning_rate': 2.2325e-05, 'epoch': 19.42}\n",
+      "{'loss': 0.1477, 'learning_rate': 2.23e-05, 'epoch': 19.43}\n",
+      "{'loss': 0.1237, 'learning_rate': 2.2275000000000003e-05, 'epoch': 19.43}\n",
+      "{'loss': 0.1556, 'learning_rate': 2.2250000000000002e-05, 'epoch': 19.44}\n",
+      "{'loss': 0.1124, 'learning_rate': 2.2225e-05, 'epoch': 19.44}\n",
+      "{'loss': 0.0818, 'learning_rate': 2.22e-05, 'epoch': 19.45}\n",
+      "{'loss': 0.0156, 'learning_rate': 2.2175e-05, 'epoch': 19.46}\n",
+      "{'loss': 0.1382, 'learning_rate': 2.215e-05, 'epoch': 19.46}\n",
+      "{'loss': 0.0722, 'learning_rate': 2.2125000000000002e-05, 'epoch': 19.47}\n",
+      "{'loss': 0.0516, 'learning_rate': 2.2100000000000002e-05, 'epoch': 19.48}\n",
+      "{'loss': 0.1153, 'learning_rate': 2.2075e-05, 'epoch': 19.48}\n",
+      "{'loss': 0.0939, 'learning_rate': 2.205e-05, 'epoch': 19.49}\n",
+      "{'loss': 0.1022, 'learning_rate': 2.2025e-05, 'epoch': 19.49}\n",
+      "{'loss': 0.0821, 'learning_rate': 2.2000000000000003e-05, 'epoch': 19.5}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9ec691846d6146919b8412e9b21520ba",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.41279664635658264, 'eval_mean_iou': 0.2827200278472803, 'eval_mean_accuracy': 0.32969202740727716, 'eval_overall_accuracy': 0.5399452329277555, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6993908496186099, 'eval_accuracy_RV': 0.39445017403635424, 'eval_accuracy_RA': 0.4965701742351489, 'eval_accuracy_LA': 0.5987760618555287, 'eval_accuracy_VS': 0.0, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.05834175205657382, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.3545395496535797, 'eval_accuracy_VSD': 0.28857168560890034, 'eval_accuracy_AK': 0.40628002700807647, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6663043138458565, 'eval_iou_RV': 0.38616722058284403, 'eval_iou_RA': 0.4789682933521709, 'eval_iou_LA': 0.5646721628340685, 'eval_iou_VS': 0.0, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.054682876515446135, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.29932366561052887, 'eval_iou_VSD': 0.2716289835436249, 'eval_iou_AK': 0.38817279003554306, 'eval_runtime': 4.7753, 'eval_samples_per_second': 16.962, 'eval_steps_per_second': 8.586, 'epoch': 19.5}\n",
+      "{'loss': 0.0649, 'learning_rate': 2.1975000000000002e-05, 'epoch': 19.51}\n",
+      "{'loss': 0.1713, 'learning_rate': 2.195e-05, 'epoch': 19.51}\n",
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+      "{'loss': 0.0437, 'learning_rate': 2.19e-05, 'epoch': 19.52}\n",
+      "{'loss': 0.0995, 'learning_rate': 2.1875e-05, 'epoch': 19.53}\n",
+      "{'loss': 0.1176, 'learning_rate': 2.1850000000000003e-05, 'epoch': 19.54}\n",
+      "{'loss': 0.1558, 'learning_rate': 2.1825000000000002e-05, 'epoch': 19.54}\n",
+      "{'loss': 0.1276, 'learning_rate': 2.18e-05, 'epoch': 19.55}\n",
+      "{'loss': 0.1294, 'learning_rate': 2.1775e-05, 'epoch': 19.56}\n",
+      "{'loss': 0.0735, 'learning_rate': 2.175e-05, 'epoch': 19.56}\n",
+      "{'loss': 0.101, 'learning_rate': 2.1725e-05, 'epoch': 19.57}\n",
+      "{'loss': 0.0443, 'learning_rate': 2.1700000000000002e-05, 'epoch': 19.57}\n",
+      "{'loss': 0.1198, 'learning_rate': 2.1675e-05, 'epoch': 19.58}\n",
+      "{'loss': 0.0934, 'learning_rate': 2.165e-05, 'epoch': 19.59}\n",
+      "{'loss': 0.0674, 'learning_rate': 2.1625e-05, 'epoch': 19.59}\n",
+      "{'loss': 0.1518, 'learning_rate': 2.16e-05, 'epoch': 19.6}\n",
+      "{'loss': 0.1219, 'learning_rate': 2.1575e-05, 'epoch': 19.61}\n",
+      "{'loss': 0.0511, 'learning_rate': 2.1550000000000002e-05, 'epoch': 19.61}\n",
+      "{'loss': 0.0048, 'learning_rate': 2.1525e-05, 'epoch': 19.62}\n",
+      "{'loss': 0.0794, 'learning_rate': 2.15e-05, 'epoch': 19.62}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "9448900c7f17416d81d7b057bada87cd",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.40002796053886414, 'eval_mean_iou': 0.31443526622630746, 'eval_mean_accuracy': 0.37453880414908997, 'eval_overall_accuracy': 0.5885299119961743, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.7409604410224896, 'eval_accuracy_RV': 0.4409642289299373, 'eval_accuracy_RA': 0.5722079200729544, 'eval_accuracy_LA': 0.6132845999217887, 'eval_accuracy_VS': 0.0004588208304657031, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.08294847741376822, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.44310226616628173, 'eval_accuracy_VSD': 0.3561714696974241, 'eval_accuracy_AK': 0.49528981743579087, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7007596943730705, 'eval_iou_RV': 0.4297339579070797, 'eval_iou_RA': 0.5342193792404567, 'eval_iou_LA': 0.5745774232580712, 'eval_iou_VS': 0.00045636052481460356, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.0765618755827894, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3532351904724234, 'eval_iou_VSD': 0.32851601125732105, 'eval_iou_AK': 0.4607280358733562, 'eval_runtime': 4.5764, 'eval_samples_per_second': 17.7, 'eval_steps_per_second': 8.959, 'epoch': 19.62}\n",
+      "{'loss': 0.0035, 'learning_rate': 2.1475e-05, 'epoch': 19.63}\n",
+      "{'loss': 0.2045, 'learning_rate': 2.145e-05, 'epoch': 19.64}\n",
+      "{'loss': 0.1156, 'learning_rate': 2.1425e-05, 'epoch': 19.64}\n",
+      "{'loss': 0.0825, 'learning_rate': 2.1400000000000002e-05, 'epoch': 19.65}\n",
+      "{'loss': 0.2205, 'learning_rate': 2.1375e-05, 'epoch': 19.66}\n",
+      "{'loss': 0.0716, 'learning_rate': 2.135e-05, 'epoch': 19.66}\n",
+      "{'loss': 0.0624, 'learning_rate': 2.1325e-05, 'epoch': 19.67}\n",
+      "{'loss': 0.1193, 'learning_rate': 2.13e-05, 'epoch': 19.68}\n",
+      "{'loss': 0.1261, 'learning_rate': 2.1275000000000002e-05, 'epoch': 19.68}\n",
+      "{'loss': 0.1924, 'learning_rate': 2.125e-05, 'epoch': 19.69}\n",
+      "{'loss': 0.1521, 'learning_rate': 2.1225e-05, 'epoch': 19.69}\n",
+      "{'loss': 0.1031, 'learning_rate': 2.12e-05, 'epoch': 19.7}\n",
+      "{'loss': 0.0547, 'learning_rate': 2.1175e-05, 'epoch': 19.71}\n",
+      "{'loss': 0.1208, 'learning_rate': 2.115e-05, 'epoch': 19.71}\n",
+      "{'loss': 0.1217, 'learning_rate': 2.1125000000000002e-05, 'epoch': 19.72}\n",
+      "{'loss': 0.1301, 'learning_rate': 2.11e-05, 'epoch': 19.73}\n",
+      "{'loss': 0.1691, 'learning_rate': 2.1075e-05, 'epoch': 19.73}\n",
+      "{'loss': 0.05, 'learning_rate': 2.105e-05, 'epoch': 19.74}\n",
+      "{'loss': 0.1001, 'learning_rate': 2.1025e-05, 'epoch': 19.74}\n",
+      "{'loss': 0.2129, 'learning_rate': 2.1e-05, 'epoch': 19.75}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "59838973c3ff4427b19b754d2455a2e3",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.39379698038101196, 'eval_mean_iou': 0.337447111509286, 'eval_mean_accuracy': 0.40409919708691094, 'eval_overall_accuracy': 0.6219873782563254, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.758653246664141, 'eval_accuracy_RV': 0.5047269133255984, 'eval_accuracy_RA': 0.5944533664748655, 'eval_accuracy_LA': 0.6348424454064586, 'eval_accuracy_VS': 0.01049552649690296, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.08385048347524895, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4796026991916859, 'eval_accuracy_VSD': 0.3979818274507452, 'eval_accuracy_AK': 0.5763854623834628, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.7163945971070015, 'eval_iou_RV': 0.48868462267711577, 'eval_iou_RA': 0.5501024060282331, 'eval_iou_LA': 0.5909458844566493, 'eval_iou_VS': 0.010408964222740458, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.07802192268309469, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3865050745921424, 'eval_iou_VSD': 0.36147105085761366, 'eval_iou_AK': 0.5293837039775556, 'eval_runtime': 4.4821, 'eval_samples_per_second': 18.072, 'eval_steps_per_second': 9.148, 'epoch': 19.75}\n",
+      "{'loss': 0.0633, 'learning_rate': 2.0975e-05, 'epoch': 19.76}\n",
+      "{'loss': 0.0545, 'learning_rate': 2.095e-05, 'epoch': 19.76}\n",
+      "{'loss': 0.2476, 'learning_rate': 2.0925e-05, 'epoch': 19.77}\n",
+      "{'loss': 0.128, 'learning_rate': 2.09e-05, 'epoch': 19.77}\n",
+      "{'loss': 0.232, 'learning_rate': 2.0875e-05, 'epoch': 19.78}\n",
+      "{'loss': 0.0931, 'learning_rate': 2.085e-05, 'epoch': 19.79}\n",
+      "{'loss': 0.0767, 'learning_rate': 2.0825e-05, 'epoch': 19.79}\n",
+      "{'loss': 0.0646, 'learning_rate': 2.08e-05, 'epoch': 19.8}\n",
+      "{'loss': 0.1461, 'learning_rate': 2.0775e-05, 'epoch': 19.81}\n",
+      "{'loss': 0.1628, 'learning_rate': 2.075e-05, 'epoch': 19.81}\n",
+      "{'loss': 0.1881, 'learning_rate': 2.0725e-05, 'epoch': 19.82}\n",
+      "{'loss': 0.089, 'learning_rate': 2.07e-05, 'epoch': 19.82}\n",
+      "{'loss': 0.0055, 'learning_rate': 2.0675e-05, 'epoch': 19.83}\n",
+      "{'loss': 0.1203, 'learning_rate': 2.065e-05, 'epoch': 19.84}\n",
+      "{'loss': 0.0487, 'learning_rate': 2.0625e-05, 'epoch': 19.84}\n",
+      "{'loss': 0.0968, 'learning_rate': 2.06e-05, 'epoch': 19.85}\n",
+      "{'loss': 0.1213, 'learning_rate': 2.0575e-05, 'epoch': 19.86}\n",
+      "{'loss': 0.0946, 'learning_rate': 2.055e-05, 'epoch': 19.86}\n",
+      "{'loss': 0.0469, 'learning_rate': 2.0525e-05, 'epoch': 19.87}\n",
+      "{'loss': 0.0585, 'learning_rate': 2.05e-05, 'epoch': 19.88}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "f22f9478002241cf8a687570d2efbea8",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'eval_loss': 0.403333455324173, 'eval_mean_iou': 0.3147717573626251, 'eval_mean_accuracy': 0.3733777878494031, 'eval_overall_accuracy': 0.5793443639251394, 'eval_accuracy_unlabeled': nan, 'eval_accuracy_LV': 0.6963711998949946, 'eval_accuracy_RV': 0.42839186725354056, 'eval_accuracy_RA': 0.5617913374706447, 'eval_accuracy_LA': 0.6673653084886697, 'eval_accuracy_VS': 0.011642578573067218, 'eval_accuracy_AS': 0.0, 'eval_accuracy_MK': 0.06480011545677587, 'eval_accuracy_TK': nan, 'eval_accuracy_ASD': 0.4160291570438799, 'eval_accuracy_VSD': 0.3538924041143131, 'eval_accuracy_AK': 0.5334939101981457, 'eval_iou_unlabeled': 0.0, 'eval_iou_LV': 0.6661575230077763, 'eval_iou_RV': 0.418041993650033, 'eval_iou_RA': 0.5356132315913187, 'eval_iou_LA': 0.6171995082682318, 'eval_iou_VS': 0.011433399042523234, 'eval_iou_AS': 0.0, 'eval_iou_MK': 0.06101268832911522, 'eval_iou_TK': nan, 'eval_iou_ASD': 0.3431632994753879, 'eval_iou_VSD': 0.32636200221238937, 'eval_iou_AK': 0.4835056854121004, 'eval_runtime': 4.65, 'eval_samples_per_second': 17.419, 'eval_steps_per_second': 8.817, 'epoch': 19.88}\n",
+      "{'loss': 0.1032, 'learning_rate': 2.0475e-05, 'epoch': 19.88}\n",
+      "{'loss': 0.0533, 'learning_rate': 2.045e-05, 'epoch': 19.89}\n",
+      "{'loss': 0.1082, 'learning_rate': 2.0425e-05, 'epoch': 19.89}\n",
+      "{'loss': 0.0655, 'learning_rate': 2.04e-05, 'epoch': 19.9}\n",
+      "{'loss': 0.1144, 'learning_rate': 2.0375e-05, 'epoch': 19.91}\n",
+      "{'loss': 0.2155, 'learning_rate': 2.035e-05, 'epoch': 19.91}\n",
+      "{'loss': 0.0048, 'learning_rate': 2.0325e-05, 'epoch': 19.92}\n",
+      "{'loss': 0.0532, 'learning_rate': 2.0300000000000002e-05, 'epoch': 19.93}\n",
+      "{'loss': 0.1288, 'learning_rate': 2.0275e-05, 'epoch': 19.93}\n",
+      "{'loss': 0.1084, 'learning_rate': 2.025e-05, 'epoch': 19.94}\n",
+      "{'loss': 0.1087, 'learning_rate': 2.0225000000000004e-05, 'epoch': 19.94}\n",
+      "{'loss': 0.0988, 'learning_rate': 2.0200000000000003e-05, 'epoch': 19.95}\n",
+      "{'loss': 0.0746, 'learning_rate': 2.0175000000000003e-05, 'epoch': 19.96}\n",
+      "{'loss': 0.1284, 'learning_rate': 2.0150000000000002e-05, 'epoch': 19.96}\n",
+      "{'loss': 0.0836, 'learning_rate': 2.0125e-05, 'epoch': 19.97}\n",
+      "{'loss': 0.1444, 'learning_rate': 2.01e-05, 'epoch': 19.98}\n",
+      "{'loss': 0.1048, 'learning_rate': 2.0075000000000003e-05, 'epoch': 19.98}\n",
+      "{'loss': 0.1909, 'learning_rate': 2.0050000000000003e-05, 'epoch': 19.99}\n",
+      "{'loss': 0.1754, 'learning_rate': 2.0025000000000002e-05, 'epoch': 19.99}\n",
+      "{'loss': 0.0479, 'learning_rate': 2e-05, 'epoch': 20.0}\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "067a47fe7b5d4b479294fc50d3f18c40",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/41 [00:00<?, ?it/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:259: RuntimeWarning: invalid value encountered in divide\n",
+      "  iou = total_area_intersect / total_area_union\n",
+      "C:\\Users\\rogbeast\\.cache\\huggingface\\modules\\evaluate_modules\\metrics\\evaluate-metric--mean_iou\\08bc20f4f895f3caf75fb9e3fada1404bded3c3265243d05327cbb3b9326ffe9\\mean_iou.py:260: RuntimeWarning: invalid value encountered in divide\n",
+      "  acc = total_area_intersect / total_area_label\n"
+     ]
+    },
+    {
+     "name": "stdout",
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+    "outputId": "f80a6791-acb6-4888-ef6b-d6808cabdcd1"
+   },
+   "outputs": [],
+   "source": [
+    "kwargs = {\n",
+    "    \"tags\": [\"vision\", \"image-segmentation\"],\n",
+    "    \"finetuned_from\": pretrained_model_name,\n",
+    "    \"dataset\": hf_dataset_identifier,\n",
+    "}\n",
+    "\n",
+    "processor.push_to_hub(hub_model_id)\n",
+    "trainer.push_to_hub(**kwargs)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
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+     "height": 168,
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+     ]
+    },
+    "id": "iTyvFlq2xxb0",
+    "outputId": "587e4e75-4cc6-4ab1-b062-28c1bbd4f369"
+   },
+   "outputs": [],
+   "source": [
+    "from transformers import SegformerImageProcessor, SegformerForSemanticSegmentation\n",
+    "\n",
+    "processor = SegformerImageProcessor.from_pretrained(\"nvidia/segformer-b0-finetuned-ade-512-512\")\n",
+    "model = SegformerForSemanticSegmentation.from_pretrained(f\"unreal-hug/{hub_model_id}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "id": "GkRFoCsiyxO9"
+   },
    "outputs": [],
    "source": []
   }
  ],
  "metadata": {
+  "colab": {
+   "include_colab_link": true,
+   "provenance": []
+  },
   "kernelspec": {
    "display_name": "Python 3 (ipykernel)",
    "language": "python",
@@ -24,7 +9573,8837 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
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