small_hf_flax_from_dataset.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "HF-ByT5.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HIGlCDONbvs5"
      },
      "source": [
        "## Dependencies"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aSWGVUwKSUin"
      },
      "source": [
        "%%capture\n",
        "! git clone https://github.com/huggingface/transformers\n",
        "! cd transformers && pip install ."
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oDIc9gPlTUqm",
        "outputId": "62428acb-abe6-4a5d-e41a-ca6ca5ce75bc"
      },
      "source": [
        "! wget https://huggingface.co/google/byt5-small/raw/main/config.json"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2021-07-11 21:53:51--  https://huggingface.co/google/byt5-small/raw/main/config.json\n",
            "Resolving huggingface.co (huggingface.co)... 15.197.130.34\n",
            "Connecting to huggingface.co (huggingface.co)|15.197.130.34|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 698 [application/json]\n",
            "Saving to: ‘config.json’\n",
            "\n",
            "config.json         100%[===================>]     698  --.-KB/s    in 0s      \n",
            "\n",
            "2021-07-11 21:53:51 (68.8 MB/s) - ‘config.json’ saved [698/698]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mM1w8VKkTm19"
      },
      "source": [
        "%%capture\n",
        "! pip install datasets flax sentencepiece"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "g7pTvZcwbxdJ"
      },
      "source": [
        "## Training"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VVWdLOYoS8T7",
        "outputId": "688513b9-ee2c-4f58-ff3f-1b460b925675"
      },
      "source": [
        "# with edits\n",
        "! cd transformers/examples/flax/language-modeling && python run_t5_mlm_flax.py \\\n",
        "    --output_dir=\"/content/sample\" \\\n",
        "    --model_type=\"byt5\" \\\n",
        "    --config_name=\"/content/config.json\" \\\n",
        "    --tokenizer_name=\"google/byt5-small\" \\\n",
        "    --dataset_name=\"thaisum\" \\\n",
        "    --dataset_config_name=\"thaisum\" \\\n",
        "    --max_seq_length=\"256\" \\\n",
        "    --per_device_train_batch_size=\"8\" \\\n",
        "    --per_device_eval_batch_size=\"8\" \\\n",
        "    --learning_rate=\"1e-3\" \\\n",
        "    --weight_decay=\"0.001\" \\\n",
        "    --warmup_steps=\"5000\" \\\n",
        "    --overwrite_output_dir \\\n",
        "    --num_train_epochs=\"7\" \\\n",
        "    --logging_steps=\"500\" \\\n",
        "    --save_steps=\"2500\" \\\n",
        "    --eval_steps=\"2500\""
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
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            "                                          \n",
            "\u001b[AStep... (7500 | Loss: 1.4696273803710938, Learning Rate: 0.0009854617528617382)\n",
            "Epoch ... (1/7):   0% 0/7 [49:39<?, ?it/s]\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
            "Evaluating ...:  36% 267/732 [00:39<01:07,  6.84it/s]\u001b[A\u001b[A\n",
            "\n",
            "Evaluating ...:  37% 268/732 [00:39<01:08,  6.73it/s]\u001b[A\u001b[A\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
            "Evaluating ...:  58% 428/732 [01:02<00:43,  6.98it/s]\u001b[A\u001b[A\n",
            "\n",
            "Evaluating ...:  59% 429/732 [01:02<00:44,  6.85it/s]\u001b[A\u001b[A\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
            "Evaluating ...:  73% 531/732 [01:17<00:28,  7.07it/s]\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
            "Evaluating ...:  80% 585/732 [01:25<00:21,  6.79it/s]\u001b[A\u001b[A\n",
            "\n",
            "Evaluating ...:  80% 586/732 [01:25<00:22,  6.53it/s]\u001b[A\u001b[A\n",
            "\n",
            "Evaluating ...:  80% 587/732 [01:25<00:21,  6.74it/s]\u001b[A\u001b[A\n",
            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
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            "\n",
            "Evaluating ...: 100% 732/732 [01:46<00:00,  6.86it/s]\n",
            "                                          \n",
            "\u001b[AStep... (7500 | Loss: 1.4269956350326538, Acc: 0.38395339250564575)\n",
            "Epoch ... (1/7):   0% 0/7 [51:27<?, ?it/s]\n",
            "Training...:  30% 7500/25280 [50:58<1:46:28,  2.78it/s]\u001b[A\n",
            "Training...:  30% 7501/25280 [51:07<175:38:09, 35.56s/it]\u001b[A\n",
            "Training...:  30% 7502/25280 [51:07<123:12:58, 24.95s/it]\u001b[A\n",
            "Training...:  30% 7503/25280 [51:08<86:46:16, 17.57s/it] \u001b[A\n",
            "Training...:  30% 7504/25280 [51:08<61:14:34, 12.40s/it]\u001b[A\n",
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            "Training...:  30% 7509/25280 [51:10<11:48:10,  2.39s/it]\u001b[A\n",
            "Training...:  30% 7510/25280 [51:10<8:46:09,  1.78s/it] \u001b[A\n",
            "Training...:  30% 7511/25280 [51:11<6:39:30,  1.35s/it]\u001b[A\n",
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            "Training...:  33% 8298/25280 [55:52<1:39:28,  2.85it/s]\u001b[A"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}