{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "provenance": [] }, "kernelspec": { "name": "python3", "display_name": "Python 3" }, "language_info": { "name": "python" }, "gpuClass": "standard", "widgets": { "application/vnd.jupyter.widget-state+json": { "562b2df63fee469eab344732405d0341": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_f90233e79de4458fb6e5e4414d1f319f", "IPY_MODEL_da72fb505ad3414680bd29008dc8a285", "IPY_MODEL_6318027214494b38a5145e1fc2dded91" ], "layout": "IPY_MODEL_b96a09347ffe417da8bf8161b4d35c3b" } }, "f90233e79de4458fb6e5e4414d1f319f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c96b32196ffe4fb78199fa8c856ecda0", "placeholder": "​", "style": "IPY_MODEL_e02dd4691fcb4fd7a38db769acd9e675", "value": "Downloading builder script: 100%" } }, "da72fb505ad3414680bd29008dc8a285": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f1cdfa643b024356909426c57e6c7f6c", "max": 3208, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_70162009566c46f5ac4680cc13907e8b", "value": 3208 } }, "6318027214494b38a5145e1fc2dded91": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_28f4807f01df47fc86c2e1bf3f12848a", "placeholder": "​", "style": "IPY_MODEL_d653b1742fbc40e28fc1a0390c4392c8", "value": " 3.21k/3.21k [00:00<00:00, 121kB/s]" } }, "b96a09347ffe417da8bf8161b4d35c3b": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "c96b32196ffe4fb78199fa8c856ecda0": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "e02dd4691fcb4fd7a38db769acd9e675": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "f1cdfa643b024356909426c57e6c7f6c": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "70162009566c46f5ac4680cc13907e8b": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "28f4807f01df47fc86c2e1bf3f12848a": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "d653b1742fbc40e28fc1a0390c4392c8": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "5d658fd2b4ca452981f37d78e5a839ac": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_a08f108560f445389475c3c9816053dc", "IPY_MODEL_ed00365457a8496385e99d3b8545e71f", "IPY_MODEL_179a41119493452c9af8bd4a2591d47c" ], "layout": "IPY_MODEL_615083b133e84ea0abc862c2945b0a4c" } }, "a08f108560f445389475c3c9816053dc": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_2220b6b5230447018481fd546a0f8c30", "placeholder": "​", "style": "IPY_MODEL_1a35f271378e4d8f84147a39dc311cb5", "value": "Downloading metadata: 100%" } }, "ed00365457a8496385e99d3b8545e71f": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e20d4fbfae75456da6c44ab2f4834ddf", "max": 1687, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_d074053ea5d14c58a1209ce99688178d", "value": 1687 } }, "179a41119493452c9af8bd4a2591d47c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_eb3237ab419c44ee8b9a56543cdc1186", "placeholder": "​", "style": "IPY_MODEL_e4d702bd0e074d009d4a86f0d872fa97", "value": " 1.69k/1.69k [00:00<00:00, 117kB/s]" } }, "615083b133e84ea0abc862c2945b0a4c": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "2220b6b5230447018481fd546a0f8c30": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "1a35f271378e4d8f84147a39dc311cb5": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "e20d4fbfae75456da6c44ab2f4834ddf": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "d074053ea5d14c58a1209ce99688178d": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "eb3237ab419c44ee8b9a56543cdc1186": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "e4d702bd0e074d009d4a86f0d872fa97": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "1a84c9f0d4c34ab9bfb8e6c1632e1aab": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_4d1fbcd786ea4724a8302f6fa373a4c5", "IPY_MODEL_c4262c9d665c43fc95f5d651272e05ac", "IPY_MODEL_eaa840ba44e5468d863d701b7a887cb0" ], "layout": "IPY_MODEL_836cc5fb2aac4814975222e4cb3eb509" } }, "4d1fbcd786ea4724a8302f6fa373a4c5": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_cc0ff055c7e348bfb7442e1da9c2d283", "placeholder": "​", "style": "IPY_MODEL_453451afd5a041cf8bd7b9bebae95e1a", "value": "Downloading readme: 100%" } }, "c4262c9d665c43fc95f5d651272e05ac": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e377724de4ea48dcb3a35d35100f77c2", "max": 4872, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_2fa10546eb11424eb1376773fd6ce8c3", "value": 4872 } }, "eaa840ba44e5468d863d701b7a887cb0": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0b03f0f260f142b6a6333f234ba7b64a", "placeholder": "​", "style": "IPY_MODEL_21e668a45d514c51b87d5888bc0d3f04", "value": " 4.87k/4.87k [00:00<00:00, 264kB/s]" } }, "836cc5fb2aac4814975222e4cb3eb509": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "cc0ff055c7e348bfb7442e1da9c2d283": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "453451afd5a041cf8bd7b9bebae95e1a": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "e377724de4ea48dcb3a35d35100f77c2": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "2fa10546eb11424eb1376773fd6ce8c3": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "0b03f0f260f142b6a6333f234ba7b64a": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "21e668a45d514c51b87d5888bc0d3f04": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "94bed16fdbbe42ab89e2417d0bc2f6be": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_ea9d739338bc46e7b6aa9edfc90db7ee", "IPY_MODEL_cc4d58df01594e258fede64937001ccc", "IPY_MODEL_bdf2b2471bec4a519b62171990b90751" ], "layout": "IPY_MODEL_49298f7943c2412f891932c2a62598b3" } }, "ea9d739338bc46e7b6aa9edfc90db7ee": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f92d4941bc304dbfbaec3a15954a2216", "placeholder": "​", "style": "IPY_MODEL_17fad956c06a43a7bb57313168431b2f", "value": "Downloading data: 100%" } }, "cc4d58df01594e258fede64937001ccc": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_5ab0d18b923d4918ba0a3d9de7398235", "max": 203415, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_9838107a69dc444084a8cbc5a97c69b5", "value": 203415 } }, "bdf2b2471bec4a519b62171990b90751": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0f52a0bf45bf4840b74f50ef0e1ed104", "placeholder": "​", "style": "IPY_MODEL_a7669275b5474a45b79e810a51fa773c", "value": " 203k/203k [00:00<00:00, 375kB/s]" } }, "49298f7943c2412f891932c2a62598b3": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "f92d4941bc304dbfbaec3a15954a2216": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "17fad956c06a43a7bb57313168431b2f": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "5ab0d18b923d4918ba0a3d9de7398235": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "9838107a69dc444084a8cbc5a97c69b5": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "0f52a0bf45bf4840b74f50ef0e1ed104": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "a7669275b5474a45b79e810a51fa773c": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "98405dc577ee4a5e8827123916074b67": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_19b3e634059f478986f5dfb4ab34875e", "IPY_MODEL_4a3004ebe922475d9476d91e50ddb0c4", "IPY_MODEL_00ccecda328f47408f98dfbb498c241a" ], "layout": "IPY_MODEL_50a6f2294627414f80816e08c425d997" } }, "19b3e634059f478986f5dfb4ab34875e": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_1d994423cee14277899cf0e2e21252a4", "placeholder": "​", "style": "IPY_MODEL_7a1a268464a5405bb96d2cd7f1f4a411", "value": "Generating train split: 100%" } }, "4a3004ebe922475d9476d91e50ddb0c4": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c8390fdbd4824593a5ca3505b3ff7481", "max": 5574, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_fb35b00db49e4fb49199ffd6c5b1c1f0", "value": 5574 } }, "00ccecda328f47408f98dfbb498c241a": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_e82ebc90a3884176a59c903e746b6728", "placeholder": "​", "style": "IPY_MODEL_ba525ced60344562922dfcd1563b295e", "value": " 5574/5574 [00:11<00:00, 14535.59 examples/s]" } }, "50a6f2294627414f80816e08c425d997": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "1d994423cee14277899cf0e2e21252a4": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "7a1a268464a5405bb96d2cd7f1f4a411": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "c8390fdbd4824593a5ca3505b3ff7481": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "fb35b00db49e4fb49199ffd6c5b1c1f0": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "e82ebc90a3884176a59c903e746b6728": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "ba525ced60344562922dfcd1563b295e": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "dcb1f03aab3e47bcaef73337578e90aa": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_00c77aa4d05c46939141db3fc8ec4e0c", "IPY_MODEL_81e81ff88979470190cbf98ad198fded", "IPY_MODEL_4a2a80e4c40c49d383472d2161b8397f" ], "layout": "IPY_MODEL_7f1c2ba12eba4f94b6b763701c7b83fc" } }, "00c77aa4d05c46939141db3fc8ec4e0c": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_3cfc5529a1e844a5876336436c787062", "placeholder": "​", "style": "IPY_MODEL_bbaf7eb0bfdc47bea197e32ede2bd5df", "value": "100%" } }, "81e81ff88979470190cbf98ad198fded": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_7040bba8c540494d8fd3eb09e4aa87f4", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_7b645af074de4ce89e521c4e32aaf790", "value": 1 } }, "4a2a80e4c40c49d383472d2161b8397f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_049cd54da01a47d29fcbfadcb31e1122", "placeholder": "​", "style": "IPY_MODEL_707d4cadc9ae45a998d4db6f022b860e", "value": " 1/1 [00:00<00:00, 15.24it/s]" } }, "7f1c2ba12eba4f94b6b763701c7b83fc": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "3cfc5529a1e844a5876336436c787062": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "bbaf7eb0bfdc47bea197e32ede2bd5df": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "7040bba8c540494d8fd3eb09e4aa87f4": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "7b645af074de4ce89e521c4e32aaf790": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "049cd54da01a47d29fcbfadcb31e1122": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "707d4cadc9ae45a998d4db6f022b860e": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "c975281b288e4eb580cf5f97c44759f8": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_8aa4e156456648b89e1d198edf848cab", "IPY_MODEL_0e4014a5797c4dd4b9cef7a415784fb7", "IPY_MODEL_5deddfa5ec384b999a406cd9761c5b15" ], "layout": "IPY_MODEL_ccb20b15603d4adb977d436a04b7f22f" } }, "8aa4e156456648b89e1d198edf848cab": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_abca5ac8660749c3a85f0cf4231f7e3a", "placeholder": "​", "style": "IPY_MODEL_e2b8031555b743ad86f1b3292e8be6a7", "value": "Downloading (…)olve/main/vocab.json: 100%" } }, "0e4014a5797c4dd4b9cef7a415784fb7": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_0f1a0ff8193c4bcf8a5a4f855c7cdef9", "max": 1042301, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_b12a405cb522492f97ce1b300328bd24", "value": 1042301 } }, "5deddfa5ec384b999a406cd9761c5b15": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_84f46d78887b4b0982de0b6c0f208d78", "placeholder": "​", "style": "IPY_MODEL_663b9294d4b54a969afbfbe5eb9e27c6", "value": " 1.04M/1.04M [00:00<00:00, 2.01MB/s]" } }, "ccb20b15603d4adb977d436a04b7f22f": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "abca5ac8660749c3a85f0cf4231f7e3a": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "e2b8031555b743ad86f1b3292e8be6a7": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "0f1a0ff8193c4bcf8a5a4f855c7cdef9": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "b12a405cb522492f97ce1b300328bd24": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "84f46d78887b4b0982de0b6c0f208d78": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "663b9294d4b54a969afbfbe5eb9e27c6": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "97d18f182fa24bf79709aaaa319bc386": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_1bf36407ad944361aed5439377339ddf", "IPY_MODEL_2a00cb65c14b4ad3b58a035abd74c08b", "IPY_MODEL_15ed7e2f50ee4bb4ac08754c07a9e703" ], "layout": "IPY_MODEL_0074ea0bdbdd42e48d71395cf489db75" } }, "1bf36407ad944361aed5439377339ddf": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_8d976387182945da82a6b88268f04c2e", "placeholder": "​", "style": "IPY_MODEL_3b7e5bbeba9a4fe6a72541478c2b3233", "value": "Downloading (…)olve/main/merges.txt: 100%" } }, "2a00cb65c14b4ad3b58a035abd74c08b": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_f0dcd590e27a474895fa9dde14cfb585", "max": 456318, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_4ab6997444d04a37b491c90af229d9d3", "value": 456318 } }, "15ed7e2f50ee4bb4ac08754c07a9e703": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_165e45626e594a7f9bceeaac7c757eb6", "placeholder": "​", "style": "IPY_MODEL_ab158071f37645799c948471957cb5d5", "value": " 456k/456k [00:00<00:00, 1.07MB/s]" } }, "0074ea0bdbdd42e48d71395cf489db75": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "8d976387182945da82a6b88268f04c2e": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "3b7e5bbeba9a4fe6a72541478c2b3233": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "f0dcd590e27a474895fa9dde14cfb585": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "4ab6997444d04a37b491c90af229d9d3": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "165e45626e594a7f9bceeaac7c757eb6": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "ab158071f37645799c948471957cb5d5": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "3e1c6fd0adc642209160f8d0787cc119": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_cd06d7c3bd3e49c9a54f8d26767ac83f", "IPY_MODEL_00b32d689601497ba083d89d482f8bc0", "IPY_MODEL_55c24dad2d274095a9dea608b81fe08e" ], "layout": "IPY_MODEL_c0dfcfb6e20a4ea1b233ff8d643d75f0" } }, "cd06d7c3bd3e49c9a54f8d26767ac83f": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_86f28cc51d2b453e8635e5459eee023c", "placeholder": "​", "style": "IPY_MODEL_67cf3e6850f243479962aa7339861798", "value": "Downloading (…)lve/main/config.json: 100%" } }, "00b32d689601497ba083d89d482f8bc0": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_310e98af244f41d3a7cdb61f8288568b", "max": 665, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_debee430506e4c29878250bd9143ae31", "value": 665 } }, "55c24dad2d274095a9dea608b81fe08e": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_a6e553a2b36b42eb843149ab3614f1e8", "placeholder": "​", "style": "IPY_MODEL_4b0c3d9ca62b4aa9ab79710b28dbaca1", "value": " 665/665 [00:00<00:00, 9.78kB/s]" } }, "c0dfcfb6e20a4ea1b233ff8d643d75f0": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "86f28cc51d2b453e8635e5459eee023c": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "67cf3e6850f243479962aa7339861798": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "310e98af244f41d3a7cdb61f8288568b": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "debee430506e4c29878250bd9143ae31": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "a6e553a2b36b42eb843149ab3614f1e8": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "4b0c3d9ca62b4aa9ab79710b28dbaca1": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "e18707f0d4be4cf1bf2fd448c465a49a": { "model_module": "@jupyter-widgets/controls", "model_name": "HBoxModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HBoxView", "box_style": "", "children": [ "IPY_MODEL_8f9ca17cef4b491fab0ba086eddeee06", "IPY_MODEL_291394dabaf4461abc7d116c34a62972", "IPY_MODEL_79d4d0a4e6914963988862a457fe5004" ], "layout": "IPY_MODEL_3fb7ae428a654adb9639dca54c8487ca" } }, "8f9ca17cef4b491fab0ba086eddeee06": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_c5a0d019aa454525b975be7b8125af52", "placeholder": "​", "style": "IPY_MODEL_bd2d006b7df94f52be982c93e6591ed9", "value": "Downloading (…)"pytorch_model.bin";: 100%" } }, "291394dabaf4461abc7d116c34a62972": { "model_module": "@jupyter-widgets/controls", "model_name": "FloatProgressModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_8cf28f0e3d22453f9b1293f7309373a1", "max": 548118077, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_2ffeb0a10a69433689ca87de39f760b6", "value": 548118077 } }, "79d4d0a4e6914963988862a457fe5004": { "model_module": "@jupyter-widgets/controls", "model_name": "HTMLModel", "model_module_version": "1.5.0", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "1.5.0", "_view_name": "HTMLView", "description": "", "description_tooltip": null, "layout": "IPY_MODEL_d2183878e1b343abb962b16a2615c0a5", "placeholder": "​", "style": "IPY_MODEL_68e1e4d6f5ce456398f333041eb00151", "value": " 548M/548M [00:02<00:00, 284MB/s]" } }, "3fb7ae428a654adb9639dca54c8487ca": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "c5a0d019aa454525b975be7b8125af52": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "bd2d006b7df94f52be982c93e6591ed9": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } }, "8cf28f0e3d22453f9b1293f7309373a1": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "2ffeb0a10a69433689ca87de39f760b6": { "model_module": "@jupyter-widgets/controls", "model_name": "ProgressStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "bar_color": null, "description_width": "" } }, "d2183878e1b343abb962b16a2615c0a5": { "model_module": "@jupyter-widgets/base", "model_name": "LayoutModel", "model_module_version": "1.2.0", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "1.2.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "overflow_x": null, "overflow_y": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null } }, "68e1e4d6f5ce456398f333041eb00151": { "model_module": "@jupyter-widgets/controls", "model_name": "DescriptionStyleModel", "model_module_version": "1.5.0", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "1.5.0", "_model_name": "DescriptionStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "1.2.0", "_view_name": "StyleView", "description_width": "" } } } }, "accelerator": "GPU" }, "cells": [ { "cell_type": "markdown", "source": [ "# Instalacja pakietów" ], "metadata": { "id": "t2xXKpOpcZg_" } }, { "cell_type": "code", "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "fdpN7ugfauLD", "outputId": "ebd6755e-3403-4922-98a8-c2006b210152" }, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n", "Collecting transformers\n", " Downloading transformers-4.26.1-py3-none-any.whl (6.3 MB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m6.3/6.3 MB\u001b[0m \u001b[31m57.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hCollecting datasets\n", " Downloading datasets-2.9.0-py3-none-any.whl (462 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m462.8/462.8 KB\u001b[0m \u001b[31m5.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: torch in /usr/local/lib/python3.8/dist-packages (1.13.1+cu116)\n", "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.8/dist-packages (from transformers) (2022.6.2)\n", "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.8/dist-packages (from transformers) (1.21.6)\n", "Requirement already satisfied: filelock in /usr/local/lib/python3.8/dist-packages (from transformers) (3.9.0)\n", "Requirement already satisfied: requests in /usr/local/lib/python3.8/dist-packages (from transformers) (2.25.1)\n", "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.8/dist-packages (from transformers) (4.64.1)\n", "Collecting tokenizers!=0.11.3,<0.14,>=0.11.1\n", " Downloading tokenizers-0.13.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (7.6 MB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m7.6/7.6 MB\u001b[0m \u001b[31m31.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.8/dist-packages (from transformers) (6.0)\n", "Collecting huggingface-hub<1.0,>=0.11.0\n", " Downloading huggingface_hub-0.12.1-py3-none-any.whl (190 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m190.3/190.3 KB\u001b[0m \u001b[31m9.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.8/dist-packages (from transformers) (23.0)\n", "Requirement already satisfied: dill<0.3.7 in /usr/local/lib/python3.8/dist-packages (from datasets) (0.3.6)\n", "Requirement already satisfied: pandas in /usr/local/lib/python3.8/dist-packages (from datasets) (1.3.5)\n", "Collecting responses<0.19\n", " Downloading responses-0.18.0-py3-none-any.whl (38 kB)\n", "Requirement already satisfied: pyarrow>=6.0.0 in /usr/local/lib/python3.8/dist-packages (from datasets) (9.0.0)\n", "Collecting xxhash\n", " Downloading xxhash-3.2.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (213 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m213.0/213.0 KB\u001b[0m \u001b[31m9.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: aiohttp in /usr/local/lib/python3.8/dist-packages (from datasets) (3.8.4)\n", "Requirement already satisfied: fsspec[http]>=2021.11.1 in /usr/local/lib/python3.8/dist-packages (from datasets) (2023.1.0)\n", "Collecting multiprocess\n", " Downloading multiprocess-0.70.14-py38-none-any.whl (132 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m132.0/132.0 KB\u001b[0m \u001b[31m10.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: typing-extensions in /usr/local/lib/python3.8/dist-packages (from torch) (4.5.0)\n", "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (1.3.1)\n", "Requirement already satisfied: charset-normalizer<4.0,>=2.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (3.0.1)\n", "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (1.8.2)\n", "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (1.3.3)\n", "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (22.2.0)\n", "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (6.0.4)\n", "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (4.0.2)\n", "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (1.24.3)\n", "Requirement already satisfied: chardet<5,>=3.0.2 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (4.0.0)\n", "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (2.10)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (2022.12.7)\n", "Collecting urllib3<1.27,>=1.21.1\n", " Downloading urllib3-1.26.14-py2.py3-none-any.whl (140 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m140.6/140.6 KB\u001b[0m \u001b[31m6.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.8/dist-packages (from pandas->datasets) (2.8.2)\n", "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.8/dist-packages (from pandas->datasets) (2022.7.1)\n", "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.8/dist-packages (from python-dateutil>=2.7.3->pandas->datasets) (1.15.0)\n", "Installing collected packages: tokenizers, xxhash, urllib3, multiprocess, responses, huggingface-hub, transformers, datasets\n", " Attempting uninstall: urllib3\n", " Found existing installation: urllib3 1.24.3\n", " Uninstalling urllib3-1.24.3:\n", " Successfully uninstalled urllib3-1.24.3\n", "Successfully installed datasets-2.9.0 huggingface-hub-0.12.1 multiprocess-0.70.14 responses-0.18.0 tokenizers-0.13.2 transformers-4.26.1 urllib3-1.26.14 xxhash-3.2.0\n" ] } ], "source": [ "!pip install transformers datasets torch" ] }, { "cell_type": "markdown", "source": [ "# Załadowanie pakietów" ], "metadata": { "id": "s8cfdy_6ldCn" } }, { "cell_type": "code", "source": [ "from datasets import load_dataset\n", "from transformers import GPT2Tokenizer\n", "import torch\n", "from torch.utils.data import TensorDataset, random_split\n", "from torch.utils.data import DataLoader, RandomSampler, SequentialSampler\n", "from transformers import get_linear_schedule_with_warmup\n", "import numpy as np\n", "import time\n", "import datetime\n", "import random" ], "metadata": { "id": "yLS_x9DIlgSs" }, "execution_count": 2, "outputs": [] }, { "cell_type": "markdown", "source": [ "# Załadowanie datasetu\n", "sms_spam" ], "metadata": { "id": "fPwDyJd5cdaE" } }, { "cell_type": "code", "source": [ "dataset = load_dataset(\"sms_spam\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 263, "referenced_widgets": [ "562b2df63fee469eab344732405d0341", "f90233e79de4458fb6e5e4414d1f319f", "da72fb505ad3414680bd29008dc8a285", "6318027214494b38a5145e1fc2dded91", "b96a09347ffe417da8bf8161b4d35c3b", "c96b32196ffe4fb78199fa8c856ecda0", "e02dd4691fcb4fd7a38db769acd9e675", "f1cdfa643b024356909426c57e6c7f6c", "70162009566c46f5ac4680cc13907e8b", "28f4807f01df47fc86c2e1bf3f12848a", "d653b1742fbc40e28fc1a0390c4392c8", "5d658fd2b4ca452981f37d78e5a839ac", "a08f108560f445389475c3c9816053dc", "ed00365457a8496385e99d3b8545e71f", "179a41119493452c9af8bd4a2591d47c", "615083b133e84ea0abc862c2945b0a4c", "2220b6b5230447018481fd546a0f8c30", "1a35f271378e4d8f84147a39dc311cb5", "e20d4fbfae75456da6c44ab2f4834ddf", "d074053ea5d14c58a1209ce99688178d", "eb3237ab419c44ee8b9a56543cdc1186", "e4d702bd0e074d009d4a86f0d872fa97", "1a84c9f0d4c34ab9bfb8e6c1632e1aab", "4d1fbcd786ea4724a8302f6fa373a4c5", "c4262c9d665c43fc95f5d651272e05ac", "eaa840ba44e5468d863d701b7a887cb0", "836cc5fb2aac4814975222e4cb3eb509", "cc0ff055c7e348bfb7442e1da9c2d283", "453451afd5a041cf8bd7b9bebae95e1a", "e377724de4ea48dcb3a35d35100f77c2", "2fa10546eb11424eb1376773fd6ce8c3", "0b03f0f260f142b6a6333f234ba7b64a", "21e668a45d514c51b87d5888bc0d3f04", "94bed16fdbbe42ab89e2417d0bc2f6be", "ea9d739338bc46e7b6aa9edfc90db7ee", "cc4d58df01594e258fede64937001ccc", "bdf2b2471bec4a519b62171990b90751", "49298f7943c2412f891932c2a62598b3", "f92d4941bc304dbfbaec3a15954a2216", "17fad956c06a43a7bb57313168431b2f", "5ab0d18b923d4918ba0a3d9de7398235", "9838107a69dc444084a8cbc5a97c69b5", "0f52a0bf45bf4840b74f50ef0e1ed104", "a7669275b5474a45b79e810a51fa773c", "98405dc577ee4a5e8827123916074b67", "19b3e634059f478986f5dfb4ab34875e", "4a3004ebe922475d9476d91e50ddb0c4", "00ccecda328f47408f98dfbb498c241a", "50a6f2294627414f80816e08c425d997", "1d994423cee14277899cf0e2e21252a4", "7a1a268464a5405bb96d2cd7f1f4a411", "c8390fdbd4824593a5ca3505b3ff7481", "fb35b00db49e4fb49199ffd6c5b1c1f0", "e82ebc90a3884176a59c903e746b6728", "ba525ced60344562922dfcd1563b295e", "dcb1f03aab3e47bcaef73337578e90aa", "00c77aa4d05c46939141db3fc8ec4e0c", "81e81ff88979470190cbf98ad198fded", "4a2a80e4c40c49d383472d2161b8397f", "7f1c2ba12eba4f94b6b763701c7b83fc", "3cfc5529a1e844a5876336436c787062", "bbaf7eb0bfdc47bea197e32ede2bd5df", "7040bba8c540494d8fd3eb09e4aa87f4", "7b645af074de4ce89e521c4e32aaf790", "049cd54da01a47d29fcbfadcb31e1122", "707d4cadc9ae45a998d4db6f022b860e" ] }, "id": "N1EWeM0KcYtO", "outputId": "2b89ef33-01b2-4bc2-b217-fcd1464c1da9" }, "execution_count": 3, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Downloading builder script: 0%| | 0.00/3.21k [00:005,} test samples'.format(test_size))\n", "print(\"Ratio: {}\\n\".format(check_class_balance(test_dataset)))\n", "print('{:>5,} training samples'.format(train_size))\n", "print(\"Ratio: {}\\n\".format(check_class_balance(train_dataset)))\n", "print('{:>5,} validation samples'.format(val_size))\n", "print(\"Ratio: {}\\n\".format(check_class_balance(val_dataset)))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "vH3yXhA0hT3n", "outputId": "0ec353c2-39c6-4581-9a9c-375709ed7b14" }, "execution_count": 10, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Spam to not spam messages ratio: 0.15475450590428838\n", "\n", "1,000 test samples\n", "Ratio: 0.13895216400911162\n", "\n", "4,116 training samples\n", "Ratio: 0.16074450084602368\n", "\n", " 458 validation samples\n", "Ratio: 0.13647642679900746\n", "\n" ] } ] }, { "cell_type": "markdown", "source": [ "# Create train and validation loaders" ], "metadata": { "id": "z1hVsejihpO2" } }, { "cell_type": "code", "source": [ "batch_size = 8\n", "\n", "train_dataloader = DataLoader(\n", " train_dataset,\n", " sampler = RandomSampler(train_dataset),\n", " batch_size = batch_size\n", " )\n", "\n", "validation_dataloader = DataLoader(\n", " val_dataset,\n", " sampler = SequentialSampler(val_dataset),\n", " batch_size = batch_size\n", " )" ], "metadata": { "id": "k4pXght6hre3" }, "execution_count": 11, "outputs": [] }, { "cell_type": "markdown", "source": [ "# Device check" ], "metadata": { "id": "MnErwHAbl_rF" } }, { "cell_type": "code", "source": [ "if torch.cuda.is_available(): \n", " device = torch.device(\"cuda\")\n", "\n", " print('There are %d GPU(s) available.' % torch.cuda.device_count())\n", " print('We will use the GPU:', torch.cuda.get_device_name(0))\n", "\n", "else:\n", " print('No GPU available, using the CPU instead.')\n", " device = torch.device(\"cpu\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "aUvyBFxzmBUy", "outputId": "dff6ae93-d79c-4d97-e6f1-91bd533cc167" }, "execution_count": 12, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "There are 1 GPU(s) available.\n", "We will use the GPU: Tesla T4\n" ] } ] }, { "cell_type": "markdown", "source": [ "# Create custom GPT2 model\n", "Compared to GPT2ForSeqienceClassification - 2 additional linear layers.\n", "https://github.com/huggingface/transformers/blob/bd469c40659ce76c81f69c7726759d249b4aef49/src/transformers/models/gpt2/modeling_gpt2.py#L1328" ], "metadata": { "id": "o-YrojT-iIfY" } }, { "cell_type": "code", "source": [ "from transformers import GPT2ForSequenceClassification, GPT2Config, GPT2Model\n", "from torch import nn" ], "metadata": { "id": "QxEE2YTIr7L0" }, "execution_count": 13, "outputs": [] }, { "cell_type": "code", "source": [ "# in original model - no custom head just linear layer\n", "# self.score = nn.Linear(config.n_embd, self.num_labels, bias=False)\n", "\n", "class GPT2ClassificationHeadCustom(nn.Module):\n", " def __init__(self, config):\n", " super().__init__()\n", " self.dense_1 = nn.Linear(config.n_embd, config.n_embd)\n", " self.dense_2 = nn.Linear(config.n_embd, config.n_embd)\n", " self.dense_3 = nn.Linear(config.n_embd, config.num_labels)\n", "\n", " def forward(self, x):\n", " x = self.dense_1(x)\n", " x = torch.relu(x)\n", "\n", " x = self.dense_2(x)\n", " x = torch.relu(x)\n", "\n", " x = self.dense_3(x)\n", " x = torch.relu(x)\n", " return x\n", "\n", "class GPT2ForSequenceClassificationCustom(GPT2ForSequenceClassification):\n", " def __init__(self, config):\n", " super().__init__(config)\n", " self.num_labels = config.num_labels\n", " self.transformer = GPT2Model(config)\n", " self.score = GPT2ClassificationHeadCustom(config)\n", "\n", " self.init_weights()\n", "\n", " # Model parallel\n", " self.model_parallel = False\n", " self.device_map = None\n", "\n", "model = GPT2ForSequenceClassificationCustom.from_pretrained(\n", " 'gpt2',\n", " num_labels = 2,\n", ")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 103, "referenced_widgets": [ "e18707f0d4be4cf1bf2fd448c465a49a", "8f9ca17cef4b491fab0ba086eddeee06", "291394dabaf4461abc7d116c34a62972", "79d4d0a4e6914963988862a457fe5004", "3fb7ae428a654adb9639dca54c8487ca", "c5a0d019aa454525b975be7b8125af52", "bd2d006b7df94f52be982c93e6591ed9", "8cf28f0e3d22453f9b1293f7309373a1", "2ffeb0a10a69433689ca87de39f760b6", "d2183878e1b343abb962b16a2615c0a5", "68e1e4d6f5ce456398f333041eb00151" ] }, "id": "sIP3VGZmiK9s", "outputId": "e944fc5f-2abb-4c2f-d201-cbc8fc98e976" }, "execution_count": 14, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Downloading (…)\"pytorch_model.bin\";: 0%| | 0.00/548M [00:005,} of {:>5,}. Elapsed: {:}.'.format(step, len(train_dataloader), elapsed))\n", "\n", " b_input_ids = batch[0].to(device)\n", " b_input_mask = batch[1].to(device)\n", " b_labels = batch[2].to(device)\n", "\n", " model.zero_grad() \n", "\n", " outputs = model(b_input_ids, \n", " token_type_ids=None, \n", " attention_mask=b_input_mask, \n", " labels=b_labels)\n", "\n", " loss = outputs['loss']\n", " total_train_loss += loss.item()\n", "\n", " loss.backward()\n", " torch.nn.utils.clip_grad_norm_(model.parameters(), 1.0)\n", "\n", " optimizer.step()\n", " scheduler.step()\n", "\n", " avg_train_loss = total_train_loss / len(train_dataloader) \n", " training_time = format_time(time.time() - t0)\n", "\n", " print(\"\")\n", " print(\" Average training loss: {0:.2f}\".format(avg_train_loss))\n", " print(\" Training epcoh took: {:}\".format(training_time))\n", " \n", " # ========================================\n", " # Validation\n", " # ========================================\n", "\n", " print(\"\")\n", " print(\"Running Validation...\")\n", "\n", " t0 = time.time()\n", " model.eval()\n", "\n", " total_eval_accuracy = 0\n", " total_eval_loss = 0\n", " nb_eval_steps = 0\n", "\n", " for batch in validation_dataloader:\n", " b_input_ids = batch[0].to(device)\n", " b_input_mask = batch[1].to(device)\n", " b_labels = batch[2].to(device)\n", " \n", " with torch.no_grad(): \n", " outputs = model(b_input_ids, \n", " token_type_ids=None, \n", " attention_mask=b_input_mask,\n", " labels=b_labels)\n", " loss = outputs['loss']\n", " logits = outputs['logits']\n", " \n", " total_eval_loss += loss.item()\n", "\n", " logits = logits.detach().cpu().numpy()\n", " label_ids = b_labels.to('cpu').numpy()\n", "\n", " total_eval_accuracy += flat_accuracy(logits, label_ids)\n", " \n", " avg_val_accuracy = total_eval_accuracy / len(validation_dataloader)\n", " print(\" Accuracy: {0:.2f}\".format(avg_val_accuracy))\n", "\n", " avg_val_loss = total_eval_loss / len(validation_dataloader)\n", " validation_time = format_time(time.time() - t0)\n", " \n", " print(\" Validation Loss: {0:.2f}\".format(avg_val_loss))\n", " print(\" Validation took: {:}\".format(validation_time))\n", "\n", " training_stats.append(\n", " {\n", " 'epoch': epoch_i + 1,\n", " 'Training Loss': avg_train_loss,\n", " 'Valid. Loss': avg_val_loss,\n", " 'Valid. Accur.': avg_val_accuracy,\n", " 'Training Time': training_time,\n", " 'Validation Time': validation_time\n", " }\n", " )\n", "\n", "print(\"\")\n", "print(\"Training complete!\")\n", "\n", "print(\"Total training took {:} (h:mm:ss)\".format(format_time(time.time()-total_t0)))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "hnq-2iztdYie", "outputId": "36eeffb8-2aaa-4db8-c2d3-17e7addaa693" }, "execution_count": 18, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "======== Epoch 1 / 4 ========\n", "Training...\n", " Batch 40 of 515. Elapsed: 0:00:19.\n", " Batch 80 of 515. Elapsed: 0:00:36.\n", " Batch 120 of 515. Elapsed: 0:00:53.\n", " Batch 160 of 515. Elapsed: 0:01:11.\n", " Batch 200 of 515. Elapsed: 0:01:28.\n", " Batch 240 of 515. Elapsed: 0:01:45.\n", " Batch 280 of 515. Elapsed: 0:02:02.\n", " Batch 320 of 515. Elapsed: 0:02:19.\n", " Batch 360 of 515. Elapsed: 0:02:36.\n", " Batch 400 of 515. Elapsed: 0:02:53.\n", " Batch 440 of 515. Elapsed: 0:03:10.\n", " Batch 480 of 515. Elapsed: 0:03:27.\n", "\n", " Average training loss: 0.09\n", " Training epcoh took: 0:03:42\n", "\n", "Running Validation...\n", " Accuracy: 0.99\n", " Validation Loss: 0.03\n", " Validation took: 0:00:08\n", "\n", "======== Epoch 2 / 4 ========\n", "Training...\n", " Batch 40 of 515. Elapsed: 0:00:17.\n", " Batch 80 of 515. Elapsed: 0:00:34.\n", " Batch 120 of 515. Elapsed: 0:00:51.\n", " Batch 160 of 515. Elapsed: 0:01:08.\n", " Batch 200 of 515. Elapsed: 0:01:25.\n", " Batch 240 of 515. Elapsed: 0:01:42.\n", " Batch 280 of 515. Elapsed: 0:01:59.\n", " Batch 320 of 515. Elapsed: 0:02:16.\n", " Batch 360 of 515. Elapsed: 0:02:33.\n", " Batch 400 of 515. Elapsed: 0:02:50.\n", " Batch 440 of 515. Elapsed: 0:03:07.\n", " Batch 480 of 515. Elapsed: 0:03:24.\n", "\n", " Average training loss: 0.04\n", " Training epcoh took: 0:03:39\n", "\n", "Running Validation...\n", " Accuracy: 0.99\n", " Validation Loss: 0.04\n", " Validation took: 0:00:08\n", "\n", "======== Epoch 3 / 4 ========\n", "Training...\n", " Batch 40 of 515. Elapsed: 0:00:17.\n", " Batch 80 of 515. Elapsed: 0:00:34.\n", " Batch 120 of 515. Elapsed: 0:00:51.\n", " Batch 160 of 515. Elapsed: 0:01:08.\n", " Batch 200 of 515. Elapsed: 0:01:25.\n", " Batch 240 of 515. Elapsed: 0:01:42.\n", " Batch 280 of 515. Elapsed: 0:01:59.\n", " Batch 320 of 515. Elapsed: 0:02:16.\n", " Batch 360 of 515. Elapsed: 0:02:33.\n", " Batch 400 of 515. Elapsed: 0:02:50.\n", " Batch 440 of 515. Elapsed: 0:03:07.\n", " Batch 480 of 515. Elapsed: 0:03:24.\n", "\n", " Average training loss: 0.02\n", " Training epcoh took: 0:03:39\n", "\n", "Running Validation...\n", " Accuracy: 0.99\n", " Validation Loss: 0.04\n", " Validation took: 0:00:08\n", "\n", "======== Epoch 4 / 4 ========\n", "Training...\n", " Batch 40 of 515. Elapsed: 0:00:17.\n", " Batch 80 of 515. Elapsed: 0:00:34.\n", " Batch 120 of 515. Elapsed: 0:00:51.\n", " Batch 160 of 515. Elapsed: 0:01:08.\n", " Batch 200 of 515. Elapsed: 0:01:25.\n", " Batch 240 of 515. Elapsed: 0:01:42.\n", " Batch 280 of 515. Elapsed: 0:01:59.\n", " Batch 320 of 515. Elapsed: 0:02:16.\n", " Batch 360 of 515. Elapsed: 0:02:33.\n", " Batch 400 of 515. Elapsed: 0:02:50.\n", " Batch 440 of 515. Elapsed: 0:03:07.\n", " Batch 480 of 515. Elapsed: 0:03:24.\n", "\n", " Average training loss: 0.01\n", " Training epcoh took: 0:03:39\n", "\n", "Running Validation...\n", " Accuracy: 0.99\n", " Validation Loss: 0.04\n", " Validation took: 0:00:08\n", "\n", "Training complete!\n", "Total training took 0:15:09 (h:mm:ss)\n" ] } ] }, { "cell_type": "markdown", "source": [ "# Train summary" ], "metadata": { "id": "z3nngo5DgZe4" } }, { "cell_type": "code", "source": [ "import pandas as pd\n", "\n", "pd.set_option('precision', 2)\n", "df_stats = pd.DataFrame(data=training_stats)\n", "\n", "df_stats = df_stats.set_index('epoch')\n", "df_stats" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 204 }, "id": "qVSGSZ5-gbnV", "outputId": "ecc3e8b1-e4cb-4f36-c90b-2802f4ce31a1" }, "execution_count": 19, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " Training Loss Valid. Loss Valid. Accur. Training Time Validation Time\n", "epoch \n", "1 9.19e-02 0.03 0.99 0:03:42 0:00:08\n", "2 3.62e-02 0.04 0.99 0:03:39 0:00:08\n", "3 1.78e-02 0.04 0.99 0:03:39 0:00:08\n", "4 8.69e-03 0.04 0.99 0:03:39 0:00:08" ], "text/html": [ "\n", "
\n", "
\n", "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
Training LossValid. LossValid. Accur.Training TimeValidation Time
epoch
19.19e-020.030.990:03:420:00:08
23.62e-020.040.990:03:390:00:08
31.78e-020.040.990:03:390:00:08
48.69e-030.040.990:03:390:00:08
\n", "
\n", " \n", " \n", " \n", "\n", " \n", "
\n", "
\n", " " ] }, "metadata": {}, "execution_count": 19 } ] }, { "cell_type": "code", "source": [ "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "\n", "import seaborn as sns\n", "\n", "sns.set(style='darkgrid')\n", "\n", "sns.set(font_scale=1.5)\n", "plt.rcParams[\"figure.figsize\"] = (12,6)\n", "\n", "plt.plot(df_stats['Training Loss'], 'b-o', label=\"Training\")\n", "plt.plot(df_stats['Valid. Loss'], 'g-o', label=\"Validation\")\n", "\n", "plt.title(\"Training & Validation Loss\")\n", "plt.xlabel(\"Epoch\")\n", "plt.ylabel(\"Loss\")\n", "plt.legend()\n", "plt.xticks([1, 2, 3, 4])\n", "\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 427 }, "id": "qhDALEePhHp1", "outputId": "b3b86c25-2525-47ff-a65c-37abc3080da3" }, "execution_count": 20, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "# Create test loader" ], "metadata": { "id": "7gwWvjFwhJen" } }, { "cell_type": "code", "source": [ "prediction_dataloader = DataLoader(\n", " test_dataset,\n", " sampler = SequentialSampler(test_dataset),\n", " batch_size = batch_size\n", " )" ], "metadata": { "id": "du6qCdHyhMms" }, "execution_count": 21, "outputs": [] }, { "cell_type": "markdown", "source": [ "# Evaluate on test dataset" ], "metadata": { "id": "n9E84sH2hOt7" } }, { "cell_type": "code", "source": [ "print('Predicting labels for {:,} test sentences...'.format(len(test_dataset)))\n", "\n", "model.eval()\n", "predictions , true_labels = [], []\n", "\n", "for batch in prediction_dataloader:\n", " batch = tuple(t.to(device) for t in batch)\n", " \n", " b_input_ids, b_input_mask, b_labels = batch\n", " \n", " with torch.no_grad():\n", " outputs = model(b_input_ids, token_type_ids=None, \n", " attention_mask=b_input_mask)\n", "\n", " logits = outputs['logits']\n", "\n", " logits = logits.detach().cpu().numpy()\n", " label_ids = b_labels.to('cpu').numpy()\n", "\n", " predictions.append(logits)\n", " true_labels.append(label_ids)\n", "\n", "print(' DONE.')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "s3nFSXgbhRs1", "outputId": "81c4eefb-1d2a-4007-8a91-797578e496a8" }, "execution_count": 22, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Predicting labels for 1,000 test sentences...\n", " DONE.\n" ] } ] }, { "cell_type": "code", "source": [ "results_ok = 0\n", "results_false = 0\n", "for idx, true_labels_batch in enumerate(true_labels):\n", " predictions_i = np.argmax(predictions[idx], axis=1).flatten()\n", " for bidx, true_label in enumerate(true_labels_batch):\n", " if true_label == predictions_i[bidx]:\n", " results_ok += 1\n", " else:\n", " results_false += 1\n", "\n", "print(\"Correct predictions: {}, incorrect results: {}, accuracy: {}\".format(results_ok, results_false, float(results_ok) / (results_ok + results_false)))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "eNMYIt7RhWYM", "outputId": "08ce9721-edd9-41e0-dd15-2b9620283f37" }, "execution_count": 23, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Correct predictions: 991, incorrect results: 9, accuracy: 0.991\n" ] } ] }, { "cell_type": "markdown", "source": [ "# MCC Score" ], "metadata": { "id": "SwHJwpqKhZ51" } }, { "cell_type": "code", "source": [ "from sklearn.metrics import matthews_corrcoef\n", "\n", "matthews_set = []\n", "print('Calculating Matthews Corr. Coef. for each batch...')\n", "\n", "for i in range(len(true_labels)):\n", " pred_labels_i = np.argmax(predictions[i], axis=1).flatten()\n", " \n", " matthews = matthews_corrcoef(true_labels[i], pred_labels_i) \n", " matthews_set.append(matthews)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "oqfHjUXThb2J", "outputId": "c74b1bfe-1c97-4cc5-f0c4-e9a8cc45da28" }, "execution_count": 24, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Calculating Matthews Corr. Coef. for each batch...\n" ] } ] }, { "cell_type": "code", "source": [ "ax = sns.barplot(x=list(range(len(matthews_set))), y=matthews_set, ci=None)\n", "\n", "plt.title('MCC Score per Batch')\n", "plt.ylabel('MCC Score (-1 to +1)')\n", "plt.xlabel('Batch #')\n", "\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 427 }, "id": "JJoRzvr0hePf", "outputId": "38fe5dad-17bb-4e0b-839b-2d69d42a9e1c" }, "execution_count": 25, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": "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\n" }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "flat_predictions = np.concatenate(predictions, axis=0)\n", "flat_predictions = np.argmax(flat_predictions, axis=1).flatten()\n", "\n", "flat_true_labels = np.concatenate(true_labels, axis=0)\n", "\n", "mcc = matthews_corrcoef(flat_true_labels, flat_predictions)\n", "\n", "print('Total MCC: %.3f' % mcc)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "8XER3sOFhfny", "outputId": "b59467dc-3459-42a4-da12-f8abc5be4f95" }, "execution_count": 26, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Total MCC: 0.958\n" ] } ] }, { "cell_type": "markdown", "source": [ "# Save model" ], "metadata": { "id": "ZTd3f1yKhhkP" } }, { "cell_type": "code", "source": [ "from google.colab import drive\n", "\n", "drive.mount('/content/gdrive/', force_remount=True)\n", "\n", "output_dir = '/content/gdrive/My Drive/UAM/Przetwarzanie-tekstu/GPT2_custom_model'\n", "print(\"Saving model to %s\" % output_dir)\n", "\n", "model_to_save = model.module if hasattr(model, 'module') else model\n", "model_to_save.save_pretrained(output_dir)\n", "tokenizer.save_pretrained(output_dir)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "gqSUWqCqhizx", "outputId": "22b21cb7-8401-4b58-eb64-c33af55b9de7" }, "execution_count": 27, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Mounted at /content/gdrive/\n", "Saving model to /content/gdrive/My Drive/UAM/Przetwarzanie-tekstu/GPT2_custom_model\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "('/content/gdrive/My Drive/UAM/Przetwarzanie-tekstu/GPT2_custom_model/tokenizer_config.json',\n", " '/content/gdrive/My Drive/UAM/Przetwarzanie-tekstu/GPT2_custom_model/special_tokens_map.json',\n", " '/content/gdrive/My Drive/UAM/Przetwarzanie-tekstu/GPT2_custom_model/vocab.json',\n", " '/content/gdrive/My Drive/UAM/Przetwarzanie-tekstu/GPT2_custom_model/merges.txt',\n", " '/content/gdrive/My Drive/UAM/Przetwarzanie-tekstu/GPT2_custom_model/added_tokens.json')" ] }, "metadata": {}, "execution_count": 27 } ] }, { "cell_type": "markdown", "source": [ "# Bibliografia\n", "- https://gmihaila.github.io/tutorial_notebooks/gpt2_finetune_classification/\n", "- https://mccormickml.com/2019/07/22/BERT-fine-tuning/#a1-saving--loading-fine-tuned-model" ], "metadata": { "id": "Er-thm7dkbIW" } } ] }