stumbleupon.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "name": "stumbleupon.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "d112d2fa32f94326a8b985a72519b081": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_02be9f3caaac476185ee1dad9daaa742",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_49f1291e1eff49fa9427f70cd3c42b8b",
              "IPY_MODEL_0987bf118d95434996b20054797e142e"
            ]
          }
        },
        "02be9f3caaac476185ee1dad9daaa742": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "49f1291e1eff49fa9427f70cd3c42b8b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_6f02d68879bb47ce8cf9fae162e59b58",
            "_dom_classes": [],
            "description": "100%",
            "_model_name": "FloatProgressModel",
            "bar_style": "success",
            "max": 3,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 3,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_09b6acbb811e4d529d16ecdfc33824d7"
          }
        },
        "0987bf118d95434996b20054797e142e": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_390a27ffb16d40d38545a9cf37bad79f",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 3/3 [17:36&lt;00:00, 352.25s/it]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_803a38513c16487aa21ae65b96e2ef4e"
          }
        },
        "6f02d68879bb47ce8cf9fae162e59b58": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "initial",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "09b6acbb811e4d529d16ecdfc33824d7": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "390a27ffb16d40d38545a9cf37bad79f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "803a38513c16487aa21ae65b96e2ef4e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "9f4860dba6644088b0717bb648a6eaff": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_bfe121511d5a4a3987bb7b2da6e3aee0",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_39d3bb67db454e28953b01352f75af49",
              "IPY_MODEL_ea121be80716419d9635854dea15204a"
            ]
          }
        },
        "bfe121511d5a4a3987bb7b2da6e3aee0": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "39d3bb67db454e28953b01352f75af49": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_5ffa101296854249a277c68d2234b9b2",
            "_dom_classes": [],
            "description": "EPOCH 1: 100%",
            "_model_name": "FloatProgressModel",
            "bar_style": "",
            "max": 393,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 393,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_3a3b481bb3d549f8b5bae827f2e54478"
          }
        },
        "ea121be80716419d9635854dea15204a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_b3b4d6a1dd8149489bf73f936f943916",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 393/393 [05:30&lt;00:00,  1.27it/s, training_loss=0.118]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_5184c8176e8548cc92e23fbcb0d32b31"
          }
        },
        "5ffa101296854249a277c68d2234b9b2": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "initial",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "3a3b481bb3d549f8b5bae827f2e54478": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "b3b4d6a1dd8149489bf73f936f943916": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "5184c8176e8548cc92e23fbcb0d32b31": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "376319cac5d649ed9684c5e09c8663c0": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_85e1f6e765b941b5bb71eaf3564fe07f",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_c21eedebbe1c4622af8f5e83eb8159da",
              "IPY_MODEL_1dfe0d45a5d14a1ca89c82b1ebd4f36a"
            ]
          }
        },
        "85e1f6e765b941b5bb71eaf3564fe07f": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "c21eedebbe1c4622af8f5e83eb8159da": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_023274f432284a25a19a428e72edab9e",
            "_dom_classes": [],
            "description": "EPOCH 2: 100%",
            "_model_name": "FloatProgressModel",
            "bar_style": "",
            "max": 393,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 393,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_b5d5a0b20cd9430685c420910098dc24"
          }
        },
        "1dfe0d45a5d14a1ca89c82b1ebd4f36a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_d9789398e4b24bf689c07dec6dfea44d",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 393/393 [05:31&lt;00:00,  1.27it/s, training_loss=0.122]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_269d3b01c10d444dad737525f53fa993"
          }
        },
        "023274f432284a25a19a428e72edab9e": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "initial",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "b5d5a0b20cd9430685c420910098dc24": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "d9789398e4b24bf689c07dec6dfea44d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "269d3b01c10d444dad737525f53fa993": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "7536d9cf1b42484d99a53bd18b0f066c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "state": {
            "_view_name": "HBoxView",
            "_dom_classes": [],
            "_model_name": "HBoxModel",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "box_style": "",
            "layout": "IPY_MODEL_08739579c1914679bdf052730d874e32",
            "_model_module": "@jupyter-widgets/controls",
            "children": [
              "IPY_MODEL_841ea0830b674e1982f2ae01fe0ed1c8",
              "IPY_MODEL_a1920c860eb348c3807e6b1297550ed9"
            ]
          }
        },
        "08739579c1914679bdf052730d874e32": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "841ea0830b674e1982f2ae01fe0ed1c8": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "state": {
            "_view_name": "ProgressView",
            "style": "IPY_MODEL_363fa2f525d74163a713a99bf7165a14",
            "_dom_classes": [],
            "description": "EPOCH 3: 100%",
            "_model_name": "FloatProgressModel",
            "bar_style": "",
            "max": 393,
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": 393,
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "orientation": "horizontal",
            "min": 0,
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_edcadeb2fa5545d0b1cf5e29b34b8610"
          }
        },
        "a1920c860eb348c3807e6b1297550ed9": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "state": {
            "_view_name": "HTMLView",
            "style": "IPY_MODEL_f0fc481347284bf8897f6e428f50fd2f",
            "_dom_classes": [],
            "description": "",
            "_model_name": "HTMLModel",
            "placeholder": "​",
            "_view_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "value": " 393/393 [05:31&lt;00:00,  1.27it/s, training_loss=0.174]",
            "_view_count": null,
            "_view_module_version": "1.5.0",
            "description_tooltip": null,
            "_model_module": "@jupyter-widgets/controls",
            "layout": "IPY_MODEL_bbe1616d7ab74779bfa516a2cd466857"
          }
        },
        "363fa2f525d74163a713a99bf7165a14": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "ProgressStyleModel",
            "description_width": "initial",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "bar_color": null,
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "edcadeb2fa5545d0b1cf5e29b34b8610": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        },
        "f0fc481347284bf8897f6e428f50fd2f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "state": {
            "_view_name": "StyleView",
            "_model_name": "DescriptionStyleModel",
            "description_width": "",
            "_view_module": "@jupyter-widgets/base",
            "_model_module_version": "1.5.0",
            "_view_count": null,
            "_view_module_version": "1.2.0",
            "_model_module": "@jupyter-widgets/controls"
          }
        },
        "bbe1616d7ab74779bfa516a2cd466857": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "state": {
            "_view_name": "LayoutView",
            "grid_template_rows": null,
            "right": null,
            "justify_content": null,
            "_view_module": "@jupyter-widgets/base",
            "overflow": null,
            "_model_module_version": "1.2.0",
            "_view_count": null,
            "flex_flow": null,
            "width": null,
            "min_width": null,
            "border": null,
            "align_items": null,
            "bottom": null,
            "_model_module": "@jupyter-widgets/base",
            "top": null,
            "grid_column": null,
            "overflow_y": null,
            "overflow_x": null,
            "grid_auto_flow": null,
            "grid_area": null,
            "grid_template_columns": null,
            "flex": null,
            "_model_name": "LayoutModel",
            "justify_items": null,
            "grid_row": null,
            "max_height": null,
            "align_content": null,
            "visibility": null,
            "align_self": null,
            "height": null,
            "min_height": null,
            "padding": null,
            "grid_auto_rows": null,
            "grid_gap": null,
            "max_width": null,
            "order": null,
            "_view_module_version": "1.2.0",
            "grid_template_areas": null,
            "object_position": null,
            "object_fit": null,
            "grid_auto_columns": null,
            "margin": null,
            "display": null,
            "left": null
          }
        }
      }
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QlwtLOFSWftl",
        "outputId": "18db9491-fd47-44c9-b510-1d94f18c28fe"
      },
      "source": [
        "!pip install transformers\n",
        "import torch\n",
        "from torch.utils.data import DataLoader, SequentialSampler, TensorDataset, RandomSampler\n",
        "from transformers import BertTokenizer, BertForSequenceClassification, AdamW, get_linear_schedule_with_warmup\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import classification_report, plot_confusion_matrix\n",
        "import numpy as np \n",
        "import pandas as pd \n",
        "import random\n",
        "import os\n",
        "import json\n",
        "from tqdm.notebook import tqdm\n",
        "torch.cuda.empty_cache()"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: transformers in /usr/local/lib/python3.7/dist-packages (4.3.3)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.7/dist-packages (from transformers) (20.9)\n",
            "Requirement already satisfied: tokenizers<0.11,>=0.10.1 in /usr/local/lib/python3.7/dist-packages (from transformers) (0.10.1)\n",
            "Requirement already satisfied: sacremoses in /usr/local/lib/python3.7/dist-packages (from transformers) (0.0.43)\n",
            "Requirement already satisfied: importlib-metadata; python_version < \"3.8\" in /usr/local/lib/python3.7/dist-packages (from transformers) (3.7.0)\n",
            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.7/dist-packages (from transformers) (4.41.1)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from transformers) (3.0.12)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.7/dist-packages (from transformers) (1.19.5)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from transformers) (2019.12.20)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from transformers) (2.23.0)\n",
            "Requirement already satisfied: pyparsing>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging->transformers) (2.4.7)\n",
            "Requirement already satisfied: click in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (7.1.2)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (1.15.0)\n",
            "Requirement already satisfied: joblib in /usr/local/lib/python3.7/dist-packages (from sacremoses->transformers) (1.0.1)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata; python_version < \"3.8\"->transformers) (3.4.0)\n",
            "Requirement already satisfied: typing-extensions>=3.6.4; python_version < \"3.8\" in /usr/local/lib/python3.7/dist-packages (from importlib-metadata; python_version < \"3.8\"->transformers) (3.7.4.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (2020.12.5)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (3.0.4)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (1.24.3)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->transformers) (2.10)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ee2KqBvIWnM-",
        "outputId": "013774d4-ab41-47fe-d0e9-1cdbc9ef517e"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "U796U0wpWtre"
      },
      "source": [
        "seed = 100\n",
        "random.seed(seed)\n",
        "np.random.seed(seed)\n",
        "torch.manual_seed(seed)\n",
        "torch.cuda.manual_seed_all(seed)\n",
        "EPOCH = 3 \n",
        "BATCH_SIZE = 16\n",
        "LEARNING_RATE = 1e-5\n",
        "STEPS = 0\n",
        "LENGTH = 512\n",
        "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
        "trans_model = 'bert-base-uncased'"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9GWEmOp9XKlH"
      },
      "source": [
        "df = pd.read_table('/content/drive/MyDrive/bert/train.tsv')\n",
        "dfTest = pd.read_table('/content/drive/MyDrive/bert/test.tsv')\n",
        "dfSub = pd.read_csv('/content/drive/MyDrive/bert/sampleSubmission.csv')"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "95oda4zOX2N0"
      },
      "source": [
        "def boilerplatePreproc(data):\n",
        "    jsonData = json.loads(data)\n",
        "    try:\n",
        "        x = jsonData['body']\n",
        "        x = ' '.join(x.split(' ')[-400:])\n",
        "    except:\n",
        "        x = jsonData['title']\n",
        "        \n",
        "    return x\n",
        "df['body'] = df.boilerplate.map(boilerplatePreproc)\n",
        "df = df.dropna()\n",
        "dfTest['body'] = dfTest.boilerplate.map(boilerplatePreproc)"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5u0IeBnfX4kz"
      },
      "source": [
        "x_train, x_val, y_train, y_val = train_test_split(df.body.values, df.label.values, test_size=0.15, random_state=seed, stratify=df.label.values)\n",
        "tokenizer = BertTokenizer.from_pretrained(trans_model, do_lower_case=True)\n",
        "encoded_train_data = tokenizer.batch_encode_plus(\n",
        "    list(x_train), \n",
        "    add_special_tokens=True, \n",
        "    return_attention_mask=True, \n",
        "    padding='max_length',\n",
        "    max_length=LENGTH, \n",
        "    return_tensors='pt',\n",
        "    truncation=True\n",
        ")\n",
        "\n",
        "encoded_val_data = tokenizer.batch_encode_plus(\n",
        "    list(x_val), \n",
        "    add_special_tokens=True, \n",
        "    return_attention_mask=True, \n",
        "    padding='max_length', \n",
        "    max_length=LENGTH, \n",
        "    return_tensors='pt',\n",
        "    truncation=True\n",
        ")\n",
        "train_input_ids = encoded_train_data['input_ids']\n",
        "attention_masks_train = encoded_train_data['attention_mask']\n",
        "train_labels = torch.tensor(list(y_train))\n",
        "val_input_ids = encoded_val_data['input_ids']\n",
        "attention_masks_val = encoded_val_data['attention_mask']\n",
        "val_labels = torch.tensor(list(y_val))\n",
        "train_dataset = TensorDataset(train_input_ids, attention_masks_train, train_labels)\n",
        "val_dataset = TensorDataset(val_input_ids, attention_masks_val, val_labels)\n",
        "train_dataloader = DataLoader(train_dataset, sampler=RandomSampler(train_dataset), batch_size=BATCH_SIZE)\n",
        "val_dataloader = DataLoader(val_dataset, sampler=SequentialSampler(val_dataset), batch_size=BATCH_SIZE)"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AwLsiMbLX7fw"
      },
      "source": [
        "def helper():\n",
        "    model = BertForSequenceClassification.from_pretrained(trans_model)\n",
        "    model = model.to(device)\n",
        "    optimizer = AdamW(model.parameters(), lr=LEARNING_RATE, eps=2e-8)\n",
        "    scheduler = get_linear_schedule_with_warmup(optimizer, num_warmup_steps=STEPS, num_training_steps=len(train_dataloader) * EPOCH)  \n",
        "    return model, optimizer, scheduler"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CEu90bJVYHXr"
      },
      "source": [
        "def evaluate():\n",
        "    model.eval()\n",
        "    total_val_loss = 0\n",
        "    predictions, true_vals = [], []\n",
        "    for batch in val_dataloader: \n",
        "        batch = tuple(b.to(device) for b in batch)\n",
        "        inputs = {\n",
        "            'input_ids':      batch[0],\n",
        "            'attention_mask': batch[1],\n",
        "            'labels':         batch[2],\n",
        "        }\n",
        "        with torch.no_grad():        \n",
        "            outputs = model(**inputs)  \n",
        "        loss = outputs[0]\n",
        "        logits = outputs[1]\n",
        "        total_val_loss += loss.item()\n",
        "        logits = logits.detach().cpu().numpy()\n",
        "        label_ids = inputs['labels'].cpu().numpy()\n",
        "        predictions.append(logits)\n",
        "        true_vals.append(label_ids)   \n",
        "    avg_val_loss = total_val_loss/len(val_dataloader)   \n",
        "    predictions = np.concatenate(predictions, axis=0)\n",
        "    true_vals = np.concatenate(true_vals, axis=0)           \n",
        "    return avg_val_loss, predictions, true_vals"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vg-O2JPIYJ5Q"
      },
      "source": [
        "def trainer(EPOCH):\n",
        "    total_train_loss = 0\n",
        "    progress_bar = tqdm(train_dataloader, desc='EPOCH {:1d}'.format(EPOCH), leave=False, disable=False)\n",
        "    for batch in progress_bar:\n",
        "        model.zero_grad()\n",
        "        batch = tuple(b.to(device) for b in batch)\n",
        "        inputs = {\n",
        "            'input_ids':      batch[0],\n",
        "            'attention_mask': batch[1],\n",
        "            'labels':         batch[2],\n",
        "        }       \n",
        "\n",
        "        outputs = model(**inputs)\n",
        "        loss = outputs[0]\n",
        "        total_train_loss += loss.item()\n",
        "        loss.float().backward()\n",
        "        torch.nn.utils.clip_grad_norm_(model.parameters(), 1.0)\n",
        "        optimizer.step()\n",
        "        scheduler.step()\n",
        "        progress_bar.set_postfix({'training_loss': '{:.3f}'.format(loss.item()/len(batch))})   \n",
        "    torch.save(model.state_dict(), f'finetuned_BERT_EPOCH_{EPOCH}.pth')\n",
        "    tqdm.write(f'\\nEPOCH {EPOCH}')\n",
        "    avg_train_loss = total_train_loss/len(train_dataloader)            \n",
        "    tqdm.write(f'Training loss: {avg_train_loss}')\n",
        "    val_loss, predictions, true_vals = evaluate()\n",
        "    "
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 321,
          "referenced_widgets": [
            "d112d2fa32f94326a8b985a72519b081",
            "02be9f3caaac476185ee1dad9daaa742",
            "49f1291e1eff49fa9427f70cd3c42b8b",
            "0987bf118d95434996b20054797e142e",
            "6f02d68879bb47ce8cf9fae162e59b58",
            "09b6acbb811e4d529d16ecdfc33824d7",
            "390a27ffb16d40d38545a9cf37bad79f",
            "803a38513c16487aa21ae65b96e2ef4e",
            "9f4860dba6644088b0717bb648a6eaff",
            "bfe121511d5a4a3987bb7b2da6e3aee0",
            "39d3bb67db454e28953b01352f75af49",
            "ea121be80716419d9635854dea15204a",
            "5ffa101296854249a277c68d2234b9b2",
            "3a3b481bb3d549f8b5bae827f2e54478",
            "b3b4d6a1dd8149489bf73f936f943916",
            "5184c8176e8548cc92e23fbcb0d32b31",
            "376319cac5d649ed9684c5e09c8663c0",
            "85e1f6e765b941b5bb71eaf3564fe07f",
            "c21eedebbe1c4622af8f5e83eb8159da",
            "1dfe0d45a5d14a1ca89c82b1ebd4f36a",
            "023274f432284a25a19a428e72edab9e",
            "b5d5a0b20cd9430685c420910098dc24",
            "d9789398e4b24bf689c07dec6dfea44d",
            "269d3b01c10d444dad737525f53fa993",
            "7536d9cf1b42484d99a53bd18b0f066c",
            "08739579c1914679bdf052730d874e32",
            "841ea0830b674e1982f2ae01fe0ed1c8",
            "a1920c860eb348c3807e6b1297550ed9",
            "363fa2f525d74163a713a99bf7165a14",
            "edcadeb2fa5545d0b1cf5e29b34b8610",
            "f0fc481347284bf8897f6e428f50fd2f",
            "bbe1616d7ab74779bfa516a2cd466857"
          ]
        },
        "id": "ixXRdBpzYMCN",
        "outputId": "52cda1e4-ec17-4884-b9f6-db5c1905cc89"
      },
      "source": [
        "model, optimizer, scheduler = helper()\n",
        "for i in tqdm(range(1, EPOCH+1)):\n",
        "    trainer(i)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Some weights of the model checkpoint at bert-base-uncased were not used when initializing BertForSequenceClassification: ['cls.predictions.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.transform.dense.bias', 'cls.predictions.decoder.weight', 'cls.seq_relationship.weight', 'cls.seq_relationship.bias', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.transform.LayerNorm.bias']\n",
            "- This IS expected if you are initializing BertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
            "- This IS NOT expected if you are initializing BertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
            "Some weights of BertForSequenceClassification were not initialized from the model checkpoint at bert-base-uncased and are newly initialized: ['classifier.weight', 'classifier.bias']\n",
            "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "d112d2fa32f94326a8b985a72519b081",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, max=3.0), HTML(value='')))"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "9f4860dba6644088b0717bb648a6eaff",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='EPOCH 1', max=393.0, style=ProgressStyle(description_widt…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\r\n",
            "EPOCH 1\n",
            "\rTraining loss: 0.4730224645016454\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "376319cac5d649ed9684c5e09c8663c0",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='EPOCH 2', max=393.0, style=ProgressStyle(description_widt…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\r\n",
            "EPOCH 2\n",
            "\rTraining loss: 0.3978565185882966\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "7536d9cf1b42484d99a53bd18b0f066c",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='EPOCH 3', max=393.0, style=ProgressStyle(description_widt…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\r\n",
            "EPOCH 3\n",
            "\rTraining loss: 0.32468659112244164\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4MhKoH_rYOOT"
      },
      "source": [
        "def predLabels(data):\r\n",
        "    encoded_data = tokenizer.batch_encode_plus(\r\n",
        "        data, \r\n",
        "        add_special_tokens=True, \r\n",
        "        return_attention_mask=True, \r\n",
        "        padding='max_length', \r\n",
        "        max_length=LENGTH, \r\n",
        "        return_tensors='pt',\r\n",
        "        truncation=True\r\n",
        "    )\r\n",
        "    \r\n",
        "    input_ids = encoded_data['input_ids']\r\n",
        "    attention_masks = encoded_data['attention_mask']   \r\n",
        "    dataset = TensorDataset(input_ids, attention_masks)\r\n",
        "    dataloader = DataLoader(dataset, sampler=SequentialSampler(dataset), batch_size=1)   \r\n",
        "    model.eval()   \r\n",
        "    predictions = []\r\n",
        "    \r\n",
        "    for batch in dataloader:      \r\n",
        "        batch = tuple(b.to(device) for b in batch)        \r\n",
        "        inputs = {\r\n",
        "            'input_ids':      batch[0],\r\n",
        "            'attention_mask': batch[1],\r\n",
        "        }\r\n",
        "        with torch.no_grad():        \r\n",
        "            outputs = model(**inputs)\r\n",
        "        logits = outputs[0]\r\n",
        "        logits = logits.detach().cpu().numpy()\r\n",
        "        predictions.append(logits)   \r\n",
        "    predictions = np.concatenate(predictions, axis=0)           \r\n",
        "    return np.argmax(predictions, axis=1).flatten()"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "X0b2TZhuWUyq"
      },
      "source": [
        "x_val_list = list(x_val)\r\n",
        "y_val_list = list(y_val)\r\n",
        "pred = predLabels(x_val_list)"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4-XOa-sGWX1d",
        "outputId": "eb2eeaa8-8c52-4485-cd27-731ef6b9f176"
      },
      "source": [
        "print(classification_report(y_val_list, pred))"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.77      0.83      0.80       540\n",
            "           1       0.83      0.77      0.80       570\n",
            "\n",
            "    accuracy                           0.80      1110\n",
            "   macro avg       0.80      0.80      0.80      1110\n",
            "weighted avg       0.80      0.80      0.80      1110\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4CepIY1MXaU9"
      },
      "source": [
        "preds = predLabels(dfTest.body.to_list())\r\n",
        "\r\n",
        "subDict = {\r\n",
        "    'urlid': dfTest.urlid.to_list(),\r\n",
        "    'label': preds,\r\n",
        "}"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PUm8iIupX9HL"
      },
      "source": [
        "submission_df = pd.DataFrame.from_dict(subDict)\r\n",
        "submission_df.to_csv('submission.csv', index = False)"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0gi9v94kYkY8"
      },
      "source": [
        ""
      ],
      "execution_count": 15,
      "outputs": []
    }
  ]
}