Mistral_Unsloth_slimorca_A100.ipynb

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      "source": [
        "<a href=\"https://colab.research.google.com/github/Troys-Code/AI_For_Free/blob/main/Mistral_Unsloth_slimorca_A100.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "GTSV6PLnHW6B"
      },
      "outputs": [],
      "source": [
        "%%capture\n",
        "import torch\n",
        "major_version, minor_version = torch.cuda.get_device_capability()\n",
        "if major_version >= 8:\n",
        "    # A100, RTX 3060+ support\n",
        "    !pip install \"unsloth[colab_ampere] @ git+https://github.com/unslothai/unsloth.git\"\n",
        "else:\n",
        "    # Tesla T4, V100 support\n",
        "    !pip install \"unsloth[colab] @ git+https://github.com/unslothai/unsloth.git\"\n",
        "pass"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "model_name = \"mistralai/Mistral-7B-v0.1\"\n",
        "max_seq_length = 2048\n",
        "learning_rate = 2e-4\n",
        "weight_decay = 0.01\n",
        "max_steps = 120*2\n",
        "warmup_steps = 10\n",
        "batch_size = 4\n",
        "gradient_accumulation_steps = 4\n",
        "lr_scheduler_type = \"linear\"\n",
        "optimizer = \"adamw_8bit\"\n",
        "use_gradient_checkpointing = True\n",
        "random_state = 3407"
      ],
      "metadata": {
        "id": "bQXaQb8_Wmue"
      },
      "execution_count": null,
      "outputs": []
    },
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      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/unsloth/__init__.py:65: UserWarning: CUDA is not linked properly.\n",
            "We shall run `ldconfig /usr/lib64-nvidia` to try to fix it.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "==((====))==  Unsloth: Fast Mistral patching release 2023.12\n",
            "   \\\\   /|    GPU: NVIDIA A100-SXM4-40GB. Max memory: 39.564 GB\n",
            "O^O/ \\_/ \\    CUDA compute capability = 8.0\n",
            "\\        /    Pytorch version: 2.1.0+cu118. CUDA Toolkit = 11.8\n",
            " \"-____-\"     bfloat16 support = TRUE\n",
            "\n"
          ]
        },
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              "model_id": "1cbd4e315c9241d687be8f74fabbf4f6"
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          "metadata": {}
        }
      ],
      "source": [
        "from unsloth import FastMistralModel\n",
        "import torch\n",
        "max_seq_length = 2048\n",
        "dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+\n",
        "load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False.\n",
        "HAS_BFLOAT16 = torch.cuda.is_bf16_supported()\n",
        "\n",
        "model, tokenizer = FastMistralModel.from_pretrained(\n",
        "    model_name = model_name,\n",
        "    max_seq_length = max_seq_length,\n",
        "    dtype = dtype,\n",
        "    load_in_4bit = load_in_4bit,\n",
        "    # token = \"hf_...\", # use one if using gated models like meta-llama/Llama-2-7b-hf\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "wl3agZgoIG65"
      },
      "outputs": [],
      "source": [
        "model = FastMistralModel.get_peft_model(\n",
        "    model,\n",
        "    r = 16,\n",
        "    target_modules = [\"q_proj\", \"k_proj\", \"v_proj\", \"o_proj\",\n",
        "                      \"gate_proj\", \"up_proj\", \"down_proj\",],\n",
        "    lora_alpha = 16,\n",
        "    lora_dropout = 0, # Currently only supports dropout = 0\n",
        "    bias = \"none\",    # Currently only supports bias = \"none\"\n",
        "    use_gradient_checkpointing = True,\n",
        "    random_state = 3407,\n",
        "    max_seq_length = max_seq_length,\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#@title Slim Orca data prep\n",
        "from datasets import load_dataset\n",
        "dataset = load_dataset(\"Open-Orca/SlimOrca\", split = \"train\")\n",
        "def formatting_prompts_func(examples):\n",
        "    convos = examples[\"conversations\"]\n",
        "    texts = []\n",
        "    mapper = {\"system\" : \"SYSTEM:\", \"human\" : \"USER:\", \"gpt\" : \"ASSISTANT:\"}\n",
        "    end_mapper = {\"system\" : \"\\n\\n\", \"human\" : \"\\n\", \"gpt\" : \"</s>\\n\"}\n",
        "    for convo in convos:\n",
        "        text = \"\".join(f\"{mapper[(turn := x['from'])]} {x['value']}{end_mapper[turn]}\" for x in convo)\n",
        "        texts.append(text)\n",
        "    return { \"text\" : texts, }\n",
        "pass\n",
        "dataset = dataset.map(formatting_prompts_func, batched = True,)"
      ],
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            "231322144d1b420b86cd3ba6c26b1520",
            "05998f609ded4f4eb65740fd3fe730bd",
            "697858e95dab4f08be3d223571a4f5fe",
            "f8e5806ee44e4a4aa0c2b33a81455fae",
            "84447168cccb47429180f05650f309a0",
            "f9481fe2c1ef478fba9156cef17cb021"
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        "id": "yxCHPF3jXtJx",
        "outputId": "3a652170-644d-48b0-83a9-f5af75c81192",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading readme:   0%|          | 0.00/2.15k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading data files:   0%|          | 0/1 [00:00<?, ?it/s]"
            ],
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              "version_major": 2,
              "version_minor": 0,
              "model_id": "bd6cf0ac315d4a228ac0190f847e84c6"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading data:   0%|          | 0.00/986M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "54d11acfa3d14ad0ad41dae155e990ea"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Extracting data files:   0%|          | 0/1 [00:00<?, ?it/s]"
            ],
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              "version_major": 2,
              "version_minor": 0,
              "model_id": "be2de5fc01ec4dee8ab8ae6fea13b7b8"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Generating train split: 0 examples [00:00, ? examples/s]"
            ],
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              "version_major": 2,
              "version_minor": 0,
              "model_id": "8bb6e5f81b034c3a84bebfd4a1256d53"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Map:   0%|          | 0/517982 [00:00<?, ? examples/s]"
            ],
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              "version_major": 2,
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              "model_id": "9dfa9abad4094d8ebc09027fdf191abe"
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          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175,
          "referenced_widgets": [
            "6ce114405a1d449d9f98e0887b62e3c6",
            "b1dfe875758844b99fcabce58570ed1f",
            "989667acf0b34dc9ba06be986ae771c8",
            "d0db1fa44e7343f591dc89177ead70e2",
            "0b70c31479144eb1a1706c71825329a1",
            "ccc47e48e67c4d698693ed3e6f67d208",
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            "e2ce17b40df042ac96355fd2c69f6eab",
            "22e0a61cb0aa4c7a808f3fed4ab965f8",
            "517f6ef510044be5bdc06dbbe8cb591b",
            "3a97b016177b40a3987a740258422c15"
          ]
        },
        "id": "-nX3SL7cI2fZ",
        "outputId": "2be0895e-1379-48cc-b4e1-2df3d99697ac"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/trl/trainer/ppo_config.py:141: UserWarning: The `optimize_cuda_cache` arguement will be deprecated soon, please use `optimize_device_cache` instead.\n",
            "  warnings.warn(\n",
            "PyTorch: setting up devices\n",
            "The default value for the training argument `--report_to` will change in v5 (from all installed integrations to none). In v5, you will need to use `--report_to all` to get the same behavior as now. You should start updating your code and make this info disappear :-).\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Map:   0%|          | 0/517982 [00:00<?, ? examples/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "6ce114405a1d449d9f98e0887b62e3c6"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "max_steps is given, it will override any value given in num_train_epochs\n",
            "Using auto half precision backend\n"
          ]
        }
      ],
      "source": [
        "from trl import SFTTrainer\n",
        "from transformers import TrainingArguments\n",
        "from transformers.utils import logging\n",
        "logging.set_verbosity_info()\n",
        "\n",
        "trainer = SFTTrainer(\n",
        "    model = model,\n",
        "    train_dataset = dataset,\n",
        "    dataset_text_field = \"text\",\n",
        "    max_seq_length = max_seq_length,\n",
        "    tokenizer = tokenizer,\n",
        "    args = TrainingArguments(\n",
        "        per_device_train_batch_size = batch_size,\n",
        "        gradient_accumulation_steps = gradient_accumulation_steps,\n",
        "        warmup_steps = warmup_steps,\n",
        "        max_steps = max_steps,\n",
        "        learning_rate = learning_rate,\n",
        "        fp16 = not HAS_BFLOAT16,\n",
        "        bf16 = HAS_BFLOAT16,\n",
        "        logging_steps = 1,\n",
        "        output_dir = \"outputs\",\n",
        "        optim = optimizer,\n",
        "        weight_decay = weight_decay,\n",
        "        lr_scheduler_type = lr_scheduler_type,\n",
        "        seed = random_state,\n",
        "    ),\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XEKvSiA5QBF6",
        "outputId": "d2bcf231-774f-48ad-896f-465c12afa99e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "GPU = NVIDIA A100-SXM4-40GB. Max memory = 39.564 GB.\n",
            "4.66 GB of memory reserved.\n"
          ]
        }
      ],
      "source": [
        "gpu_stats = torch.cuda.get_device_properties(0)\n",
        "start_gpu_memory = round(torch.cuda.max_memory_reserved() / 1024 / 1024 / 1024, 3)\n",
        "max_memory = round(gpu_stats.total_memory / 1024 / 1024 / 1024, 3)\n",
        "print(f\"GPU = {gpu_stats.name}. Max memory = {max_memory} GB.\")\n",
        "print(f\"{start_gpu_memory} GB of memory reserved.\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "2jZyjKIUQCvL",
        "outputId": "57895ab9-76d3-4dc7-a71a-f8e7b49ac38c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "***** Running training *****\n",
            "  Num examples = 517,982\n",
            "  Num Epochs = 1\n",
            "  Instantaneous batch size per device = 4\n",
            "  Total train batch size (w. parallel, distributed & accumulation) = 16\n",
            "  Gradient Accumulation steps = 4\n",
            "  Total optimization steps = 240\n",
            "  Number of trainable parameters = 41,943,040\n",
            "You're using a LlamaTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.\n",
            "`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "    <div>\n",
              "      \n",
              "      <progress value='240' max='240' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [240/240 13:52, Epoch 0/1]\n",
              "    </div>\n",
              "    <table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              " <tr style=\"text-align: left;\">\n",
              "      <th>Step</th>\n",
              "      <th>Training Loss</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>1</td>\n",
              "      <td>1.552500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>1.779400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>1.569100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>1.774800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>5</td>\n",
              "      <td>1.795500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>6</td>\n",
              "      <td>1.866500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>7</td>\n",
              "      <td>1.530300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>8</td>\n",
              "      <td>1.516400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>9</td>\n",
              "      <td>1.605200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>10</td>\n",
              "      <td>1.591100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>11</td>\n",
              "      <td>1.444400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>12</td>\n",
              "      <td>1.217200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>13</td>\n",
              "      <td>1.355600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>14</td>\n",
              "      <td>1.466400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>15</td>\n",
              "      <td>1.278000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>16</td>\n",
              "      <td>1.488500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>17</td>\n",
              "      <td>1.372900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>18</td>\n",
              "      <td>1.186300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>19</td>\n",
              "      <td>1.289100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>20</td>\n",
              "      <td>1.413300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>21</td>\n",
              "      <td>1.358300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>22</td>\n",
              "      <td>1.299600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>23</td>\n",
              "      <td>1.317100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>24</td>\n",
              "      <td>1.239900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>25</td>\n",
              "      <td>1.395100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>26</td>\n",
              "      <td>1.092000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>27</td>\n",
              "      <td>1.441800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>28</td>\n",
              "      <td>1.269800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>29</td>\n",
              "      <td>1.323500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>30</td>\n",
              "      <td>1.335300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>31</td>\n",
              "      <td>1.084600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>32</td>\n",
              "      <td>1.225900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>33</td>\n",
              "      <td>1.060800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>34</td>\n",
              "      <td>1.336900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>35</td>\n",
              "      <td>1.092100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>36</td>\n",
              "      <td>1.494900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>37</td>\n",
              "      <td>1.085600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>38</td>\n",
              "      <td>1.292000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>39</td>\n",
              "      <td>1.228200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>40</td>\n",
              "      <td>1.283000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>41</td>\n",
              "      <td>1.150900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>42</td>\n",
              "      <td>1.176500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>43</td>\n",
              "      <td>1.136000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>44</td>\n",
              "      <td>1.184900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>45</td>\n",
              "      <td>1.372800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>46</td>\n",
              "      <td>1.372500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>47</td>\n",
              "      <td>1.195100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>48</td>\n",
              "      <td>1.069500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>49</td>\n",
              "      <td>1.070300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>50</td>\n",
              "      <td>1.297400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>51</td>\n",
              "      <td>1.222500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>52</td>\n",
              "      <td>1.486600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>53</td>\n",
              "      <td>1.270500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>54</td>\n",
              "      <td>1.086500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>55</td>\n",
              "      <td>1.431400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>56</td>\n",
              "      <td>1.073100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>57</td>\n",
              "      <td>1.332200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>58</td>\n",
              "      <td>1.201600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>59</td>\n",
              "      <td>1.412600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>60</td>\n",
              "      <td>1.190400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>61</td>\n",
              "      <td>1.161300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>62</td>\n",
              "      <td>1.483000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>63</td>\n",
              "      <td>1.439100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>64</td>\n",
              "      <td>1.312900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>65</td>\n",
              "      <td>1.268800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>66</td>\n",
              "      <td>0.987000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>67</td>\n",
              "      <td>1.109400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>68</td>\n",
              "      <td>1.079400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>69</td>\n",
              "      <td>1.639400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>70</td>\n",
              "      <td>1.294700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>71</td>\n",
              "      <td>1.219300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>72</td>\n",
              "      <td>1.095500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>73</td>\n",
              "      <td>1.195800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>74</td>\n",
              "      <td>1.240200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>75</td>\n",
              "      <td>1.243800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>76</td>\n",
              "      <td>0.986700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>77</td>\n",
              "      <td>1.190100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>78</td>\n",
              "      <td>1.305200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>79</td>\n",
              "      <td>1.011700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>80</td>\n",
              "      <td>1.178700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>81</td>\n",
              "      <td>1.344100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>82</td>\n",
              "      <td>1.350800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>83</td>\n",
              "      <td>1.138100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>84</td>\n",
              "      <td>1.093900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>85</td>\n",
              "      <td>1.387900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>86</td>\n",
              "      <td>1.035500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>87</td>\n",
              "      <td>1.238000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>88</td>\n",
              "      <td>1.092700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>89</td>\n",
              "      <td>1.082000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>90</td>\n",
              "      <td>1.248000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>91</td>\n",
              "      <td>1.041900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>92</td>\n",
              "      <td>1.103000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>93</td>\n",
              "      <td>1.292200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>94</td>\n",
              "      <td>1.072500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>95</td>\n",
              "      <td>1.356700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>96</td>\n",
              "      <td>0.944600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>97</td>\n",
              "      <td>1.103600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>98</td>\n",
              "      <td>1.156600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>99</td>\n",
              "      <td>1.083400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>100</td>\n",
              "      <td>1.179400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>101</td>\n",
              "      <td>1.405100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>102</td>\n",
              "      <td>1.336600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>103</td>\n",
              "      <td>1.268500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>104</td>\n",
              "      <td>0.948500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>105</td>\n",
              "      <td>1.263600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>106</td>\n",
              "      <td>1.265100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>107</td>\n",
              "      <td>1.116100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>108</td>\n",
              "      <td>1.163800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>109</td>\n",
              "      <td>0.966400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>110</td>\n",
              "      <td>1.187000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>111</td>\n",
              "      <td>1.058800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>112</td>\n",
              "      <td>1.213900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>113</td>\n",
              "      <td>1.496700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>114</td>\n",
              "      <td>1.100400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>115</td>\n",
              "      <td>0.939600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>116</td>\n",
              "      <td>1.388400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>117</td>\n",
              "      <td>1.188900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>118</td>\n",
              "      <td>1.096900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>119</td>\n",
              "      <td>1.003100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>120</td>\n",
              "      <td>1.102000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>121</td>\n",
              "      <td>1.224300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>122</td>\n",
              "      <td>1.077500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>123</td>\n",
              "      <td>1.125300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>124</td>\n",
              "      <td>1.282900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>125</td>\n",
              "      <td>1.245800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>126</td>\n",
              "      <td>1.289300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>127</td>\n",
              "      <td>1.108500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>128</td>\n",
              "      <td>1.232800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>129</td>\n",
              "      <td>1.266600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>130</td>\n",
              "      <td>1.206000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>131</td>\n",
              "      <td>1.090300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>132</td>\n",
              "      <td>1.048300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>133</td>\n",
              "      <td>1.361200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>134</td>\n",
              "      <td>1.082600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>135</td>\n",
              "      <td>1.121800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>136</td>\n",
              "      <td>1.391600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>137</td>\n",
              "      <td>1.010600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>138</td>\n",
              "      <td>1.314200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>139</td>\n",
              "      <td>1.266100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>140</td>\n",
              "      <td>1.171300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>141</td>\n",
              "      <td>1.121600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>142</td>\n",
              "      <td>1.046800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>143</td>\n",
              "      <td>1.102600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>144</td>\n",
              "      <td>1.313000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>145</td>\n",
              "      <td>1.164900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>146</td>\n",
              "      <td>1.398100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>147</td>\n",
              "      <td>1.231400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>148</td>\n",
              "      <td>1.401100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>149</td>\n",
              "      <td>1.141800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>150</td>\n",
              "      <td>1.027000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>151</td>\n",
              "      <td>1.063100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>152</td>\n",
              "      <td>1.093600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>153</td>\n",
              "      <td>1.173100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>154</td>\n",
              "      <td>1.340900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>155</td>\n",
              "      <td>1.112500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>156</td>\n",
              "      <td>0.949600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>157</td>\n",
              "      <td>1.240400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>158</td>\n",
              "      <td>1.254200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>159</td>\n",
              "      <td>1.012200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>160</td>\n",
              "      <td>1.144900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>161</td>\n",
              "      <td>1.134200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>162</td>\n",
              "      <td>1.183200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>163</td>\n",
              "      <td>1.360200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>164</td>\n",
              "      <td>1.050600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>165</td>\n",
              "      <td>1.078500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>166</td>\n",
              "      <td>1.453000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>167</td>\n",
              "      <td>0.978100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>168</td>\n",
              "      <td>1.141100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>169</td>\n",
              "      <td>1.157600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>170</td>\n",
              "      <td>1.174500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>171</td>\n",
              "      <td>1.280600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>172</td>\n",
              "      <td>1.255900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>173</td>\n",
              "      <td>1.173200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>174</td>\n",
              "      <td>1.347100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>175</td>\n",
              "      <td>1.296500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>176</td>\n",
              "      <td>1.120500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>177</td>\n",
              "      <td>1.178300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>178</td>\n",
              "      <td>1.395000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>179</td>\n",
              "      <td>1.244200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>180</td>\n",
              "      <td>1.156300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>181</td>\n",
              "      <td>1.119300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>182</td>\n",
              "      <td>1.066700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>183</td>\n",
              "      <td>1.059200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>184</td>\n",
              "      <td>1.155300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>185</td>\n",
              "      <td>0.981700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>186</td>\n",
              "      <td>1.210900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>187</td>\n",
              "      <td>1.153100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>188</td>\n",
              "      <td>1.282400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>189</td>\n",
              "      <td>0.934600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>190</td>\n",
              "      <td>1.165200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>191</td>\n",
              "      <td>1.033400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>192</td>\n",
              "      <td>1.078700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>193</td>\n",
              "      <td>1.103400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>194</td>\n",
              "      <td>1.008200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>195</td>\n",
              "      <td>1.033300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>196</td>\n",
              "      <td>1.112500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>197</td>\n",
              "      <td>1.239600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>198</td>\n",
              "      <td>1.141800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>199</td>\n",
              "      <td>0.937200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>200</td>\n",
              "      <td>1.238600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>201</td>\n",
              "      <td>1.013600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>202</td>\n",
              "      <td>0.885900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>203</td>\n",
              "      <td>0.869400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>204</td>\n",
              "      <td>1.174800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>205</td>\n",
              "      <td>0.954300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>206</td>\n",
              "      <td>1.159600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>207</td>\n",
              "      <td>1.257900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>208</td>\n",
              "      <td>1.078800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>209</td>\n",
              "      <td>0.993300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>210</td>\n",
              "      <td>1.126300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>211</td>\n",
              "      <td>1.184200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>212</td>\n",
              "      <td>1.157400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>213</td>\n",
              "      <td>1.178500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>214</td>\n",
              "      <td>1.407300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>215</td>\n",
              "      <td>0.975500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>216</td>\n",
              "      <td>1.048400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>217</td>\n",
              "      <td>1.183000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>218</td>\n",
              "      <td>1.351600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>219</td>\n",
              "      <td>1.130900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>220</td>\n",
              "      <td>1.243500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>221</td>\n",
              "      <td>1.209700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>222</td>\n",
              "      <td>1.159300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>223</td>\n",
              "      <td>1.064900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>224</td>\n",
              "      <td>0.966900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>225</td>\n",
              "      <td>1.064000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>226</td>\n",
              "      <td>1.184900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>227</td>\n",
              "      <td>0.977400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>228</td>\n",
              "      <td>1.316900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>229</td>\n",
              "      <td>1.075300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>230</td>\n",
              "      <td>0.973300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>231</td>\n",
              "      <td>1.085200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>232</td>\n",
              "      <td>1.079400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>233</td>\n",
              "      <td>1.274400</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>234</td>\n",
              "      <td>1.237100</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>235</td>\n",
              "      <td>1.086600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>236</td>\n",
              "      <td>1.107000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>237</td>\n",
              "      <td>1.028000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>238</td>\n",
              "      <td>1.137700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>239</td>\n",
              "      <td>1.085000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>240</td>\n",
              "      <td>1.331400</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table><p>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n",
            "\n",
            "Training completed. Do not forget to share your model on huggingface.co/models =)\n",
            "\n",
            "\n"
          ]
        }
      ],
      "source": [
        "trainer_stats = trainer.train()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gup9SDYzQDyg",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "e7acbe94-1fcd-4a11-bf59-9a2902bffb81"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "841.9962 seconds used for training.\n",
            "14.03 minutes used for training.\n",
            "Mon Dec 11 16:17:04 2023       \n",
            "+-----------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 525.105.17   Driver Version: 525.105.17   CUDA Version: 12.0     |\n",
            "|-------------------------------+----------------------+----------------------+\n",
            "| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                               |                      |               MIG M. |\n",
            "|===============================+======================+======================|\n",
            "|   0  NVIDIA A100-SXM...  Off  | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   69C    P0   105W / 400W |  12465MiB / 40960MiB |    100%      Default |\n",
            "|                               |                      |             Disabled |\n",
            "+-------------------------------+----------------------+----------------------+\n",
            "                                                                               \n",
            "+-----------------------------------------------------------------------------+\n",
            "| Processes:                                                                  |\n",
            "|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |\n",
            "|        ID   ID                                                   Usage      |\n",
            "|=============================================================================|\n",
            "+-----------------------------------------------------------------------------+\n"
          ]
        }
      ],
      "source": [
        "print(f\"{trainer_stats.metrics['train_runtime']} seconds used for training.\")\n",
        "print(f\"{round(trainer_stats.metrics['train_runtime']/60, 2)} minutes used for training.\")\n",
        "!nvidia-smi"
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