{ "nbformat": 4, "nbformat_minor": 0, "metadata": { "colab": { "provenance": [] }, "kernelspec": { "name": "python3", "display_name": "Python 3" }, "language_info": { "name": "python" }, "gpuClass": "standard", "accelerator": "GPU", "widgets": { "application/vnd.jupyter.widget-state+json": { "e4bb6f2f32de48d4b1f6d7ecf97ce376": { "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_3305b30f1bfa48e9b0c1ba3add06094e", "IPY_MODEL_a343619acbb745baa6aa561271ec8815", "IPY_MODEL_c493fc54d9eb421f96d6e8519c8a1b0e" ], "layout": "IPY_MODEL_12fd6daa8e604ecd9ad731b6296815da" } }, "3305b30f1bfa48e9b0c1ba3add06094e": { "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_805f497aa3304353a1be8b4cc87bfb54", "placeholder": "", "style": "IPY_MODEL_594a6d13f81f479eb00fa45fd4094146", "value": "Downloading builder script: 100%" } }, "a343619acbb745baa6aa561271ec8815": { "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_236979048eb8461f9b7d8c4103905eed", "max": 3208, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_4620faf461ca449a88de45e86467e265", "value": 3208 } }, "c493fc54d9eb421f96d6e8519c8a1b0e": { "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_8dc2f0f2e66741edbccab7abaaf634ce", "placeholder": "", "style": "IPY_MODEL_0d49bfb55dfd4090ba57c544eaa97902", "value": " 3.21k/3.21k [00:00<00:00, 139kB/s]" } }, "12fd6daa8e604ecd9ad731b6296815da": { "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 } }, "805f497aa3304353a1be8b4cc87bfb54": { "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 } }, "594a6d13f81f479eb00fa45fd4094146": { "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": "" } }, "236979048eb8461f9b7d8c4103905eed": { "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 } }, "4620faf461ca449a88de45e86467e265": { "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": "" } }, "8dc2f0f2e66741edbccab7abaaf634ce": { "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 } }, "0d49bfb55dfd4090ba57c544eaa97902": { "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": "" } }, "4084f218fca64fc9b765e04d0cc073ac": { "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_fec67d95a5904ac199f6648a34ef1ff9", "IPY_MODEL_a734d44f6baf4a5f8dfda576c09fffca", "IPY_MODEL_3fc2d009da594365854aa11be804b388" ], "layout": "IPY_MODEL_45c7d35932ec44bcb2ccdc73f0ae6b46" } }, "fec67d95a5904ac199f6648a34ef1ff9": { "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_0c1c3db046f24599b27daa44217f48d2", "placeholder": "", "style": "IPY_MODEL_c3f9ed611a154e22b875d0696ef6022d", "value": "Downloading metadata: 100%" } }, "a734d44f6baf4a5f8dfda576c09fffca": { "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_7fd51c34909b41a8884fa358cccdbf48", "max": 1687, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_9d9edc5471de40c2b7c2b9156637997d", "value": 1687 } }, "3fc2d009da594365854aa11be804b388": { "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_02c64bf3ff95438cb43c7dc52034cc43", "placeholder": "", "style": "IPY_MODEL_f0b71ecb6b1c4d1190ca899af7d3e82c", "value": " 1.69k/1.69k [00:00<00:00, 37.7kB/s]" } }, "45c7d35932ec44bcb2ccdc73f0ae6b46": { "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 } }, "0c1c3db046f24599b27daa44217f48d2": { "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 } }, "c3f9ed611a154e22b875d0696ef6022d": { "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": "" } }, "7fd51c34909b41a8884fa358cccdbf48": { "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 } }, "9d9edc5471de40c2b7c2b9156637997d": { "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": "" } }, "02c64bf3ff95438cb43c7dc52034cc43": { "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 } }, "f0b71ecb6b1c4d1190ca899af7d3e82c": { "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": "" } }, "8cae9c49e18f43248072b5e059429f6d": { "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_88c8adca128b44c1bbbec437630c2074", "IPY_MODEL_0f73f5e2c8af41eaae5f1c27f212da8b", "IPY_MODEL_255b4480e11f4b3e892a5d2dc6abfd4b" ], "layout": "IPY_MODEL_a96eab6312f6447b9eff3f914c5a6827" } }, "88c8adca128b44c1bbbec437630c2074": { "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_063059d53dc942d1aee9e3fe2f27687d", "placeholder": "", "style": "IPY_MODEL_ca50704df2cc430fae6b5902c5399414", "value": "Downloading readme: 100%" } }, "0f73f5e2c8af41eaae5f1c27f212da8b": { "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_64f5cdd8d1c14be79278ee4de89993d1", "max": 4872, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_f065dcd7d1d34cb6806f2eb28bb3cd6f", "value": 4872 } }, "255b4480e11f4b3e892a5d2dc6abfd4b": { "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_67663505c87640b58e04d3ce028537ea", "placeholder": "", "style": "IPY_MODEL_f5a17bc6f9f94b2ca119528b0ca2d456", "value": " 4.87k/4.87k [00:00<00:00, 116kB/s]" } }, "a96eab6312f6447b9eff3f914c5a6827": { "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 } }, "063059d53dc942d1aee9e3fe2f27687d": { "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 } }, "ca50704df2cc430fae6b5902c5399414": { "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": "" } }, "64f5cdd8d1c14be79278ee4de89993d1": { "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 } }, "f065dcd7d1d34cb6806f2eb28bb3cd6f": { "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": "" } }, "67663505c87640b58e04d3ce028537ea": { "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 } }, "f5a17bc6f9f94b2ca119528b0ca2d456": { "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": "" } }, "ec0f16c3cbb14d9287e148887127219b": { "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_ba832204e1d4413f8b8a15e10bac7d95", "IPY_MODEL_8179dbec98b7466ea2195affb0568498", "IPY_MODEL_7e9abda7b55c459b8a9888edaf1cc116" ], "layout": "IPY_MODEL_64c8860ae16848af9b04bb41955a8446" } }, "ba832204e1d4413f8b8a15e10bac7d95": { "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_64fe250082bf4d4fb126a319920d2f0a", "placeholder": "", "style": "IPY_MODEL_0b278b6f5da94921afbacb873c15d9c9", "value": "Downloading data: 100%" } }, "8179dbec98b7466ea2195affb0568498": { "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_b688bc7f34e941488831da5d4aed9396", "max": 203415, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_44cec66cbaeb49abb26dbfc5420ceacb", "value": 203415 } }, "7e9abda7b55c459b8a9888edaf1cc116": { "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_67a750dcfa8b44499956572fda3dbacf", "placeholder": "", "style": "IPY_MODEL_edad6f2eb6704468bd06006c50697f86", "value": " 203k/203k [00:00<00:00, 171kB/s]" } }, "64c8860ae16848af9b04bb41955a8446": { "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 } }, "64fe250082bf4d4fb126a319920d2f0a": { "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 } }, "0b278b6f5da94921afbacb873c15d9c9": { "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": "" } }, "b688bc7f34e941488831da5d4aed9396": { "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 } }, "44cec66cbaeb49abb26dbfc5420ceacb": { "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": "" } }, "67a750dcfa8b44499956572fda3dbacf": { "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 } }, "edad6f2eb6704468bd06006c50697f86": { "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": "" } }, "699a1bdf38ca48e2affc3c6bd771852f": { "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_4e5a92d4acdc43d487290ffd8a842ea5", "IPY_MODEL_8bc8c44b6324478a8209094f9b7e9ccd", "IPY_MODEL_e95f31e693674a0aae8de0e167a49daf" ], "layout": "IPY_MODEL_069a68aed2bb4d37a00c9c0feedd3e17" } }, "4e5a92d4acdc43d487290ffd8a842ea5": { "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_9930f171a6db47939e996016cb49fe20", "placeholder": "", "style": "IPY_MODEL_ddd0c0abba074aa7a33b5c825ccf8760", "value": "Generating train split: 100%" } }, "8bc8c44b6324478a8209094f9b7e9ccd": { "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_8bbb7307312648b0afb901f701a4e466", "max": 5574, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_4a2eb48d3583446598fdd1b7175c96fd", "value": 5574 } }, "e95f31e693674a0aae8de0e167a49daf": { "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_b3eae90c5aea409ab1a2c541948658f8", "placeholder": "", "style": "IPY_MODEL_41b5186c2e194402a1e18f1c1a9f18a4", "value": " 5574/5574 [00:12<00:00, 7617.98 examples/s]" } }, "069a68aed2bb4d37a00c9c0feedd3e17": { "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": "hidden", "width": null } }, "9930f171a6db47939e996016cb49fe20": { "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 } }, "ddd0c0abba074aa7a33b5c825ccf8760": { "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": "" } }, "8bbb7307312648b0afb901f701a4e466": { "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 } }, "4a2eb48d3583446598fdd1b7175c96fd": { "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": "" } }, "b3eae90c5aea409ab1a2c541948658f8": { "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 } }, "41b5186c2e194402a1e18f1c1a9f18a4": { "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": "" } }, "3c84850ebe3e45d297d3bfa8a12f1b86": { "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_8a5f71a073ca4b0cb929ba3cf31fd296", "IPY_MODEL_b5be73849b61415fb9187d011261be1e", "IPY_MODEL_46a51fbd984344b1958889c608ea04ed" ], "layout": "IPY_MODEL_0d25092adebd4f94b1799df263ccaf55" } }, "8a5f71a073ca4b0cb929ba3cf31fd296": { "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_e4814d2ee2df4f6a9f411b134ebca546", "placeholder": "", "style": "IPY_MODEL_09669f6ac72b45689e082b4fb489a23f", "value": "100%" } }, "b5be73849b61415fb9187d011261be1e": { "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_7afda94f85794acf882856b760a3eb63", "max": 1, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_a70df5e47adb4a4d8b80a543dedfd708", "value": 1 } }, "46a51fbd984344b1958889c608ea04ed": { "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_140058b69379422797bdc22374192bd6", "placeholder": "", "style": "IPY_MODEL_8aabd23e2fa242e4b8cf4ef43fbebe2e", "value": " 1/1 [00:00<00:00, 13.35it/s]" } }, "0d25092adebd4f94b1799df263ccaf55": { "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 } }, "e4814d2ee2df4f6a9f411b134ebca546": { "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 } }, "09669f6ac72b45689e082b4fb489a23f": { "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": "" } }, "7afda94f85794acf882856b760a3eb63": { "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 } }, "a70df5e47adb4a4d8b80a543dedfd708": { "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": "" } }, "140058b69379422797bdc22374192bd6": { "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 } }, "8aabd23e2fa242e4b8cf4ef43fbebe2e": { "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": "" } }, "040698c1b4be4adebfe751751a64c11d": { "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_11b4ddede4494fe093329c50097b7df5", "IPY_MODEL_7986c625c9c34d039fad240333d0da08", "IPY_MODEL_b35a6f8e81184f81990a0111cc5c6ca8" ], "layout": "IPY_MODEL_2968992398a94adeb626eec2f45a8699" } }, "11b4ddede4494fe093329c50097b7df5": { "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_c9f8f67483fb45c8a6b59fceae40fe42", "placeholder": "", "style": "IPY_MODEL_c5a862e7d71c430c865fa87dc21b1f6d", "value": "Downloading (…)okenizer_config.json: 100%" } }, "7986c625c9c34d039fad240333d0da08": { "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_d69171bdd6544c8ab9e96f3f3dfe7f92", "max": 2537, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_9cca59c67c5f452eb1d9e8dd22296968", "value": 2537 } }, "b35a6f8e81184f81990a0111cc5c6ca8": { "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_0f18ab0690ce4bc3b9b7c2f4d10c2049", "placeholder": "", "style": "IPY_MODEL_af26b98c1e3440daa11e104ed1c8b7e4", "value": " 2.54k/2.54k [00:00<00:00, 97.2kB/s]" } }, "2968992398a94adeb626eec2f45a8699": { "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 } }, "c9f8f67483fb45c8a6b59fceae40fe42": { "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 } }, "c5a862e7d71c430c865fa87dc21b1f6d": { "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": "" } }, "d69171bdd6544c8ab9e96f3f3dfe7f92": { "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 } }, "9cca59c67c5f452eb1d9e8dd22296968": { "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": "" } }, "0f18ab0690ce4bc3b9b7c2f4d10c2049": { "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 } }, "af26b98c1e3440daa11e104ed1c8b7e4": { "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": "" } }, "be9060616d68475ea2e4674f7e460566": { "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_264afd978de54dbeaa1b711e4c0b1c07", "IPY_MODEL_bbcefda6eea74b8ea8313e4f7167df65", "IPY_MODEL_68d85f6957ea4807a1fe7c82c9a7bc06" ], "layout": "IPY_MODEL_cdfaf060f34a4d23afe97243d5f4c709" } }, "264afd978de54dbeaa1b711e4c0b1c07": { "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_9411023294ab44b284894aebf3f8f589", "placeholder": "", "style": "IPY_MODEL_d8bf78a3d7ea47a9824d6e01e70b0237", "value": "Downloading (…)"spiece.model";: 100%" } }, "bbcefda6eea74b8ea8313e4f7167df65": { "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_b95ece9507db467fad710338bdf29177", "max": 791656, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_34a31746a99c4916b1402a2829e71a98", "value": 791656 } }, "68d85f6957ea4807a1fe7c82c9a7bc06": { "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_29b2a7a233a9484c92056034cc70b8ca", "placeholder": "", "style": "IPY_MODEL_c9a72e2599e94e9e9bc2b4912d25877b", "value": " 792k/792k [00:00<00:00, 19.7MB/s]" } }, "cdfaf060f34a4d23afe97243d5f4c709": { "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 } }, "9411023294ab44b284894aebf3f8f589": { "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 } }, "d8bf78a3d7ea47a9824d6e01e70b0237": { "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": "" } }, "b95ece9507db467fad710338bdf29177": { "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 } }, "34a31746a99c4916b1402a2829e71a98": { "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": "" } }, "29b2a7a233a9484c92056034cc70b8ca": { "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 } }, "c9a72e2599e94e9e9bc2b4912d25877b": { "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": "" } }, "2c24af439f3e45db8a0e004686e912ed": { "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_dcb13b35232145fd85be1b6e4442cc5a", "IPY_MODEL_58037f9984bb414a9c6e56337d86215c", "IPY_MODEL_6e9379baaf2049658790e176ca279531" ], "layout": "IPY_MODEL_772e39d516cf43fdbb1b3db001d53d77" } }, "dcb13b35232145fd85be1b6e4442cc5a": { "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_c08c1e0783324c53b7fc02912fa14af9", "placeholder": "", "style": "IPY_MODEL_9bcdda510c0147178f651b66450b48ac", "value": "Downloading (…)/main/tokenizer.json: 100%" } }, "58037f9984bb414a9c6e56337d86215c": { "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_18ab5e8088e04cdca93df7519156a59f", "max": 2424064, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_f502a26154d840b89b5c61a2aae4f827", "value": 2424064 } }, "6e9379baaf2049658790e176ca279531": { "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_7beb993a979443dcb93d26ec6e6718c3", "placeholder": "", "style": "IPY_MODEL_62e60fc862054e4d8d0d18cb1957cf6d", "value": " 2.42M/2.42M [00:01<00:00, 1.56MB/s]" } }, "772e39d516cf43fdbb1b3db001d53d77": { "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 } }, "c08c1e0783324c53b7fc02912fa14af9": { "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 } }, "9bcdda510c0147178f651b66450b48ac": { "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": "" } }, "18ab5e8088e04cdca93df7519156a59f": { "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 } }, "f502a26154d840b89b5c61a2aae4f827": { "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": "" } }, "7beb993a979443dcb93d26ec6e6718c3": { "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 } }, "62e60fc862054e4d8d0d18cb1957cf6d": { "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": "" } }, "bd697213d4fa4c1d9119657c537e78fe": { "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_67f9f97815354675bf3bd435f2ed0436", "IPY_MODEL_27bd6c78e7f74ff385509e9856c2b8d0", "IPY_MODEL_34f670acaa3542eebc8c19018e900ce3" ], "layout": "IPY_MODEL_ec2d082874844b6daf8542824bfde1a0" } }, "67f9f97815354675bf3bd435f2ed0436": { "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_b9df5fc8959447449d873bd17e6696f7", "placeholder": "", "style": "IPY_MODEL_f8489ecaa1a844369bcb427c5f4c95e6", "value": "Downloading (…)cial_tokens_map.json: 100%" } }, "27bd6c78e7f74ff385509e9856c2b8d0": { "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_b21e65a9dff040f4a045580d9989ac20", "max": 2201, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_0efa19170c9e4de891e328365543c916", "value": 2201 } }, "34f670acaa3542eebc8c19018e900ce3": { "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_8c6fa802ddd5491581c092e5422bfeab", "placeholder": "", "style": "IPY_MODEL_42cfc2ada7ac408fab39251add66f6ef", "value": " 2.20k/2.20k [00:00<00:00, 67.2kB/s]" } }, "ec2d082874844b6daf8542824bfde1a0": { "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 } }, "b9df5fc8959447449d873bd17e6696f7": { "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 } }, "f8489ecaa1a844369bcb427c5f4c95e6": { "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": "" } }, "b21e65a9dff040f4a045580d9989ac20": { "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 } }, "0efa19170c9e4de891e328365543c916": { "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": "" } }, "8c6fa802ddd5491581c092e5422bfeab": { "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 } }, "42cfc2ada7ac408fab39251add66f6ef": { "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": "" } }, "3747d0aa68d642449ff32b7efd47d497": { "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_2a84ccf3660a4e24b37bfc1d952f06d9", "IPY_MODEL_43b98452768846eb9b773839a4681cc6", "IPY_MODEL_2dfbcef644a84b558ce99b2ddaf091b6" ], "layout": "IPY_MODEL_9dd02373a1994433a49e0015b76dd858" } }, "2a84ccf3660a4e24b37bfc1d952f06d9": { "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_42a620dfccb4416c95fbd7a76637dc73", "placeholder": "", "style": "IPY_MODEL_9d953b41e24c4263b18e1ff2174eb797", "value": "Downloading (…)lve/main/config.json: 100%" } }, "43b98452768846eb9b773839a4681cc6": { "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_cb409960af114fa690bac72c1d51d2ab", "max": 1404, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_995a94c35b4c441b86598d1976281711", "value": 1404 } }, "2dfbcef644a84b558ce99b2ddaf091b6": { "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_4ea2ccb5fa264dd5a042f570c22db7de", "placeholder": "", "style": "IPY_MODEL_4d5668e5b66d4993b935b077a1dc281c", "value": " 1.40k/1.40k [00:00<00:00, 54.0kB/s]" } }, "9dd02373a1994433a49e0015b76dd858": { "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 } }, "42a620dfccb4416c95fbd7a76637dc73": { "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 } }, "9d953b41e24c4263b18e1ff2174eb797": { "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": "" } }, "cb409960af114fa690bac72c1d51d2ab": { "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 } }, "995a94c35b4c441b86598d1976281711": { "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": "" } }, "4ea2ccb5fa264dd5a042f570c22db7de": { "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 } }, "4d5668e5b66d4993b935b077a1dc281c": { "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": "" } }, "cf36c750119449e8a16aa97a9b66a124": { "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_0de691bf20804830ba5e6710c205c9ac", "IPY_MODEL_7ee532c002784554b12fede964c6c05a", "IPY_MODEL_25e5c76c84a8414495b61663250825aa" ], "layout": "IPY_MODEL_12bd0cd379754967bfd5481d5836b7a4" } }, "0de691bf20804830ba5e6710c205c9ac": { "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_d55d326ffbdc420da0a399c141f7fb56", "placeholder": "", "style": "IPY_MODEL_092323b59b734eada8d88197d9f0eb72", "value": "Downloading (…)"pytorch_model.bin";: 100%" } }, "7ee532c002784554b12fede964c6c05a": { "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_622df288b2ae4f62b776cb101de18b9f", "max": 990402637, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_c72abd216b9444ef9bdb0f8a0a6771b0", "value": 990402637 } }, "25e5c76c84a8414495b61663250825aa": { "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_03d5f2402e464b7cb5244db0f824df1d", "placeholder": "", "style": "IPY_MODEL_4a6e196f590d4b329e0edefc910d4730", "value": " 990M/990M [00:09<00:00, 135MB/s]" } }, "12bd0cd379754967bfd5481d5836b7a4": { "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 } }, "d55d326ffbdc420da0a399c141f7fb56": { "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 } }, "092323b59b734eada8d88197d9f0eb72": { "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": "" } }, "622df288b2ae4f62b776cb101de18b9f": { "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 } }, "c72abd216b9444ef9bdb0f8a0a6771b0": { "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": "" } }, "03d5f2402e464b7cb5244db0f824df1d": { "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 } }, "4a6e196f590d4b329e0edefc910d4730": { "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": "" } }, "9a04f6723e2a40288eb42eea0134dfaf": { "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_4065d0eed87e4d268de8f4536287e225", "IPY_MODEL_bebca147a83446abaf19c3e3db11744e", "IPY_MODEL_cf525a599ca245b19204bfff3fa1bd11" ], "layout": "IPY_MODEL_b60759f0730343849ef3e51d2c8be38c" } }, "4065d0eed87e4d268de8f4536287e225": { "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_dcc795e3fac0401b9a4d2aac3bd6e8cc", "placeholder": "", "style": "IPY_MODEL_ed7ca6da408842b38a466097ec9d4616", "value": "Downloading (…)neration_config.json: 100%" } }, "bebca147a83446abaf19c3e3db11744e": { "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_0335f29f40564adf9b577707dfb40aa9", "max": 147, "min": 0, "orientation": "horizontal", "style": "IPY_MODEL_a200da1478fa46a19695a5b2f2c77fd1", "value": 147 } }, "cf525a599ca245b19204bfff3fa1bd11": { "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_e21e75bbbc4149b4ac85fece44aee355", "placeholder": "", "style": "IPY_MODEL_c014c271cd374f62a0d113efca14001a", "value": " 147/147 [00:00<00:00, 6.16kB/s]" } }, "b60759f0730343849ef3e51d2c8be38c": { "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 } }, "dcc795e3fac0401b9a4d2aac3bd6e8cc": { "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 } }, "ed7ca6da408842b38a466097ec9d4616": { "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": "" } }, "0335f29f40564adf9b577707dfb40aa9": { "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 } }, "a200da1478fa46a19695a5b2f2c77fd1": { "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": "" } }, "e21e75bbbc4149b4ac85fece44aee355": { "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 } }, "c014c271cd374f62a0d113efca14001a": { "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": "" } } } } }, "cells": [ { "cell_type": "markdown", "source": [ "# Instalacja pakietów" ], "metadata": { "id": "ZXsOR6oJOJbd" } }, { "cell_type": "code", "execution_count": 1, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "8l0hzptKNiZS", "outputId": "6ebbbe8e-00ec-4108-d209-e7dd267f6d1e" }, "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[31m47.0 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[31m22.2 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", "Collecting sentencepiece\n", " Downloading sentencepiece-0.1.97-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.3 MB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m15.2 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", "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.8/dist-packages (from transformers) (2022.6.2)\n", "Collecting huggingface-hub<1.0,>=0.11.0\n", " Downloading huggingface_hub-0.12.0-py3-none-any.whl (190 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m190.3/190.3 KB\u001b[0m \u001b[31m13.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hCollecting 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[31m56.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement 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", "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.8/dist-packages (from transformers) (23.0)\n", "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.8/dist-packages (from transformers) (1.21.6)\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[31m4.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: dill<0.3.7 in /usr/local/lib/python3.8/dist-packages (from datasets) (0.3.6)\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[31m8.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hRequirement already satisfied: pyarrow>=6.0.0 in /usr/local/lib/python3.8/dist-packages (from datasets) (9.0.0)\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: aiohttp in /usr/local/lib/python3.8/dist-packages (from datasets) (3.8.3)\n", "Requirement already satisfied: fsspec[http]>=2021.11.1 in /usr/local/lib/python3.8/dist-packages (from datasets) (2023.1.0)\n", "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.8/dist-packages (from torch) (4.4.0)\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: 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: yarl<2.0,>=1.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (1.8.2)\n", "Requirement already satisfied: charset-normalizer<3.0,>=2.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (2.1.1)\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: aiosignal>=1.1.2 in /usr/local/lib/python3.8/dist-packages (from aiohttp->datasets) (1.3.1)\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: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (1.24.3)\n", "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (2022.12.7)\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", "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[31m9.7 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, sentencepiece, 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-0.12.0 multiprocess-0.70.14 responses-0.18.0 sentencepiece-0.1.97 tokenizers-0.13.2 transformers-4.26.1 urllib3-1.26.14 xxhash-3.2.0\n" ] } ], "source": [ "!pip install transformers datasets torch sentencepiece" ] }, { "cell_type": "markdown", "source": [ "# Załadowanie datasetu" ], "metadata": { "id": "dhN0rmb5Oi3d" } }, { "cell_type": "code", "source": [ "from datasets import load_dataset" ], "metadata": { "id": "tnaDkwZ2Pbnn" }, "execution_count": 2, "outputs": [] }, { "cell_type": "code", "source": [ "dataset = load_dataset(\"sms_spam\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 244, "referenced_widgets": [ "e4bb6f2f32de48d4b1f6d7ecf97ce376", "3305b30f1bfa48e9b0c1ba3add06094e", "a343619acbb745baa6aa561271ec8815", "c493fc54d9eb421f96d6e8519c8a1b0e", "12fd6daa8e604ecd9ad731b6296815da", "805f497aa3304353a1be8b4cc87bfb54", "594a6d13f81f479eb00fa45fd4094146", "236979048eb8461f9b7d8c4103905eed", "4620faf461ca449a88de45e86467e265", "8dc2f0f2e66741edbccab7abaaf634ce", "0d49bfb55dfd4090ba57c544eaa97902", "4084f218fca64fc9b765e04d0cc073ac", "fec67d95a5904ac199f6648a34ef1ff9", "a734d44f6baf4a5f8dfda576c09fffca", "3fc2d009da594365854aa11be804b388", "45c7d35932ec44bcb2ccdc73f0ae6b46", "0c1c3db046f24599b27daa44217f48d2", "c3f9ed611a154e22b875d0696ef6022d", "7fd51c34909b41a8884fa358cccdbf48", "9d9edc5471de40c2b7c2b9156637997d", "02c64bf3ff95438cb43c7dc52034cc43", "f0b71ecb6b1c4d1190ca899af7d3e82c", "8cae9c49e18f43248072b5e059429f6d", "88c8adca128b44c1bbbec437630c2074", "0f73f5e2c8af41eaae5f1c27f212da8b", "255b4480e11f4b3e892a5d2dc6abfd4b", "a96eab6312f6447b9eff3f914c5a6827", "063059d53dc942d1aee9e3fe2f27687d", "ca50704df2cc430fae6b5902c5399414", "64f5cdd8d1c14be79278ee4de89993d1", "f065dcd7d1d34cb6806f2eb28bb3cd6f", "67663505c87640b58e04d3ce028537ea", "f5a17bc6f9f94b2ca119528b0ca2d456", "ec0f16c3cbb14d9287e148887127219b", "ba832204e1d4413f8b8a15e10bac7d95", "8179dbec98b7466ea2195affb0568498", "7e9abda7b55c459b8a9888edaf1cc116", "64c8860ae16848af9b04bb41955a8446", "64fe250082bf4d4fb126a319920d2f0a", "0b278b6f5da94921afbacb873c15d9c9", "b688bc7f34e941488831da5d4aed9396", "44cec66cbaeb49abb26dbfc5420ceacb", "67a750dcfa8b44499956572fda3dbacf", "edad6f2eb6704468bd06006c50697f86", "699a1bdf38ca48e2affc3c6bd771852f", "4e5a92d4acdc43d487290ffd8a842ea5", "8bc8c44b6324478a8209094f9b7e9ccd", "e95f31e693674a0aae8de0e167a49daf", "069a68aed2bb4d37a00c9c0feedd3e17", "9930f171a6db47939e996016cb49fe20", "ddd0c0abba074aa7a33b5c825ccf8760", "8bbb7307312648b0afb901f701a4e466", "4a2eb48d3583446598fdd1b7175c96fd", "b3eae90c5aea409ab1a2c541948658f8", "41b5186c2e194402a1e18f1c1a9f18a4", "3c84850ebe3e45d297d3bfa8a12f1b86", "8a5f71a073ca4b0cb929ba3cf31fd296", "b5be73849b61415fb9187d011261be1e", "46a51fbd984344b1958889c608ea04ed", "0d25092adebd4f94b1799df263ccaf55", "e4814d2ee2df4f6a9f411b134ebca546", "09669f6ac72b45689e082b4fb489a23f", "7afda94f85794acf882856b760a3eb63", "a70df5e47adb4a4d8b80a543dedfd708", "140058b69379422797bdc22374192bd6", "8aabd23e2fa242e4b8cf4ef43fbebe2e" ] }, "id": "cCiAuRqrOkvV", "outputId": "394df630-e545-4005-b3a4-82b0341b210b" }, "execution_count": 3, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Downloading builder script: 0%| | 0.00/3.21k [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "e4bb6f2f32de48d4b1f6d7ecf97ce376" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "Downloading metadata: 0%| | 0.00/1.69k [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "4084f218fca64fc9b765e04d0cc073ac" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "Downloading readme: 0%| | 0.00/4.87k [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "8cae9c49e18f43248072b5e059429f6d" } }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Downloading and preparing dataset sms_spam/plain_text to /root/.cache/huggingface/datasets/sms_spam/plain_text/1.0.0/53f051d3b5f62d99d61792c91acefe4f1577ad3e4c216fb0ad39e30b9f20019c...\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "Downloading data: 0%| | 0.00/203k [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "ec0f16c3cbb14d9287e148887127219b" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "Generating train split: 0%| | 0/5574 [00:00, ? examples/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "699a1bdf38ca48e2affc3c6bd771852f" } }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Dataset sms_spam downloaded and prepared to /root/.cache/huggingface/datasets/sms_spam/plain_text/1.0.0/53f051d3b5f62d99d61792c91acefe4f1577ad3e4c216fb0ad39e30b9f20019c. Subsequent calls will reuse this data.\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ " 0%| | 0/1 [00:00, ?it/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "3c84850ebe3e45d297d3bfa8a12f1b86" } }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "dataset['train'][123]" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "JKFHPko3OnAV", "outputId": "423375ec-0be7-431b-8a65-f531df1d94d8" }, "execution_count": 4, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "{'sms': 'Todays Voda numbers ending 7548 are selected to receive a $350 award. If you have a match please call 08712300220 quoting claim code 4041 standard rates app\\n',\n", " 'label': 1}" ] }, "metadata": {}, "execution_count": 4 } ] }, { "cell_type": "markdown", "source": [ "# Modyfikacja datasetu - klasyfikacja zero-shot" ], "metadata": { "id": "l140vJrgYxPr" } }, { "cell_type": "code", "source": [ "parsed_dataset = []\n", "\n", "for row in dataset['train']:\n", " text = \"Answer the question in one word - true if provided text is spam or false, if provided text is not spam.\\n Q: Is this text spam? \\nText: \" + row['sms'] + \"A: \"\n", " new_row = {}\n", " new_row['sms'] = text\n", " if row['label'] == 0:\n", " new_row['label'] = \"true\"\n", " else:\n", " new_row['label'] = \"false\"\n", " parsed_dataset.append(new_row)\n", "\n", "parsed_dataset[0]" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "1boUF-YiY3_y", "outputId": "a7ecfad8-7c97-4de2-8852-80b28ea7c965" }, "execution_count": 5, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "{'sms': 'Answer the question in one word - true if provided text is spam or false, if provided text is not spam.\\n Q: Is this text spam? \\nText: Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there got amore wat...\\nA: ',\n", " 'label': 'true'}" ] }, "metadata": {}, "execution_count": 5 } ] }, { "cell_type": "markdown", "source": [ "# Tokenizer FLAN-T5" ], "metadata": { "id": "O-J-jBDxPJcn" } }, { "cell_type": "code", "source": [ "from transformers import AutoTokenizer" ], "metadata": { "id": "P23AYPX1PZ6g" }, "execution_count": 6, "outputs": [] }, { "cell_type": "code", "source": [ "tokenizer = AutoTokenizer.from_pretrained('google/flan-t5-base')" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 145, "referenced_widgets": [ "040698c1b4be4adebfe751751a64c11d", "11b4ddede4494fe093329c50097b7df5", "7986c625c9c34d039fad240333d0da08", "b35a6f8e81184f81990a0111cc5c6ca8", "2968992398a94adeb626eec2f45a8699", "c9f8f67483fb45c8a6b59fceae40fe42", "c5a862e7d71c430c865fa87dc21b1f6d", "d69171bdd6544c8ab9e96f3f3dfe7f92", "9cca59c67c5f452eb1d9e8dd22296968", "0f18ab0690ce4bc3b9b7c2f4d10c2049", "af26b98c1e3440daa11e104ed1c8b7e4", "be9060616d68475ea2e4674f7e460566", "264afd978de54dbeaa1b711e4c0b1c07", "bbcefda6eea74b8ea8313e4f7167df65", "68d85f6957ea4807a1fe7c82c9a7bc06", "cdfaf060f34a4d23afe97243d5f4c709", "9411023294ab44b284894aebf3f8f589", "d8bf78a3d7ea47a9824d6e01e70b0237", "b95ece9507db467fad710338bdf29177", "34a31746a99c4916b1402a2829e71a98", "29b2a7a233a9484c92056034cc70b8ca", "c9a72e2599e94e9e9bc2b4912d25877b", "2c24af439f3e45db8a0e004686e912ed", "dcb13b35232145fd85be1b6e4442cc5a", "58037f9984bb414a9c6e56337d86215c", "6e9379baaf2049658790e176ca279531", "772e39d516cf43fdbb1b3db001d53d77", "c08c1e0783324c53b7fc02912fa14af9", "9bcdda510c0147178f651b66450b48ac", "18ab5e8088e04cdca93df7519156a59f", "f502a26154d840b89b5c61a2aae4f827", "7beb993a979443dcb93d26ec6e6718c3", "62e60fc862054e4d8d0d18cb1957cf6d", "bd697213d4fa4c1d9119657c537e78fe", "67f9f97815354675bf3bd435f2ed0436", "27bd6c78e7f74ff385509e9856c2b8d0", "34f670acaa3542eebc8c19018e900ce3", "ec2d082874844b6daf8542824bfde1a0", "b9df5fc8959447449d873bd17e6696f7", "f8489ecaa1a844369bcb427c5f4c95e6", "b21e65a9dff040f4a045580d9989ac20", "0efa19170c9e4de891e328365543c916", "8c6fa802ddd5491581c092e5422bfeab", "42cfc2ada7ac408fab39251add66f6ef" ] }, "id": "q5Jz0E_oPMBr", "outputId": "c71131a5-4737-4354-e58f-17aa88116348" }, "execution_count": 7, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Downloading (…)okenizer_config.json: 0%| | 0.00/2.54k [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "040698c1b4be4adebfe751751a64c11d" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "Downloading (…)\"spiece.model\";: 0%| | 0.00/792k [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "be9060616d68475ea2e4674f7e460566" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "Downloading (…)/main/tokenizer.json: 0%| | 0.00/2.42M [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "2c24af439f3e45db8a0e004686e912ed" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "Downloading (…)cial_tokens_map.json: 0%| | 0.00/2.20k [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "bd697213d4fa4c1d9119657c537e78fe" } }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "sms = parsed_dataset[0]['sms']\n", "print('Original: \\n', sms)\n", "print('Tokenized: ', tokenizer.tokenize(sms))\n", "print('Token IDs: ', tokenizer.convert_tokens_to_ids(tokenizer.tokenize(sms)))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "dfxJQpoePsvI", "outputId": "2ce963db-ed94-467a-e859-fd0515849ee2" }, "execution_count": 8, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Original: \n", " Answer the question in one word - true if provided text is spam or false, if provided text is not spam.\n", " Q: Is this text spam? \n", "Text: Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there got amore wat...\n", "A: \n", "Tokenized: ['▁Answer', '▁the', '▁question', '▁in', '▁one', '▁word', '▁', '-', '▁true', '▁', 'if', '▁provided', '▁text', '▁is', '▁spam', '▁or', '▁false', ',', '▁', 'if', '▁provided', '▁text', '▁is', '▁not', '▁spam', '.', '▁Q', ':', '▁I', 's', '▁this', '▁text', '▁spam', '?', '▁Text', ':', '▁Go', '▁until', '▁jur', 'ong', '▁point', ',', '▁crazy', '.', '.', '▁Available', '▁only', '▁in', '▁bug', 'is', '▁', 'n', '▁great', '▁world', '▁la', '▁', 'e', '▁buffet', '...', '▁Cine', '▁there', '▁got', '▁', 'a', 'more', '▁wa', 't', '...', '▁A', ':', '▁']\n", "Token IDs: [11801, 8, 822, 16, 80, 1448, 3, 18, 1176, 3, 99, 937, 1499, 19, 13655, 42, 6136, 6, 3, 99, 937, 1499, 19, 59, 13655, 5, 1593, 10, 27, 7, 48, 1499, 13655, 58, 5027, 10, 1263, 552, 10081, 2444, 500, 6, 6139, 5, 5, 8144, 163, 16, 8143, 159, 3, 29, 248, 296, 50, 3, 15, 15385, 233, 17270, 132, 530, 3, 9, 3706, 8036, 17, 233, 71, 10, 3]\n" ] } ] }, { "cell_type": "markdown", "source": [ "# Check maximum lenght of a sentence" ], "metadata": { "id": "UpluhM8cU5Ir" } }, { "cell_type": "code", "source": [ "max_len = 0\n", "\n", "for sentence in parsed_dataset:\n", " input_ids = tokenizer.encode(sentence['sms'], add_special_tokens=True)\n", " max_len = max(max_len, len(input_ids))\n", "\n", "print('Max sentence length: ', max_len)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "7uNUkixPU85O", "outputId": "352b31bb-164e-42a8-a8b0-6be9d3eca0c4" }, "execution_count": 12, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Max sentence length: 377\n" ] } ] }, { "cell_type": "code", "source": [ "max_label_len = 0\n", "\n", "for sentence in parsed_dataset:\n", " input_ids = tokenizer.encode(sentence['label'], add_special_tokens=True)\n", " max_label_len = max(max_label_len, len(input_ids))\n", "\n", "print('Max sentence length: ', max_label_len)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "lj0issBznZfK", "outputId": "53defde8-ed8d-4927-add4-5d7d63f737df" }, "execution_count": 13, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Max sentence length: 2\n" ] } ] }, { "cell_type": "markdown", "source": [ "# Pre train tokenization" ], "metadata": { "id": "nfw62HdgSERb" } }, { "cell_type": "code", "source": [ "import torch" ], "metadata": { "id": "KTXYalS1VLqH" }, "execution_count": 11, "outputs": [] }, { "cell_type": "code", "source": [ "input_ids = []\n", "target_ids = []\n", "attention_masks = []\n", "\n", "for sentence in parsed_dataset:\n", " encoded_dict = tokenizer.encode_plus(\n", " sentence['sms'],\n", " add_special_tokens = True,\n", " max_length = 380,\n", " padding = 'max_length',\n", " truncation=True,\n", " return_attention_mask = True,\n", " return_tensors = 'pt',\n", " )\n", " \n", " encoded_target_dict = tokenizer.encode_plus(\n", " sentence['label'],\n", " add_special_tokens = True,\n", " max_length = 2,\n", " padding = 'max_length',\n", " truncation=True,\n", " return_attention_mask = True,\n", " return_tensors = 'pt',\n", " )\n", " \n", " input_ids.append(encoded_dict['input_ids'])\n", " target_ids.append(encoded_target_dict['input_ids'])\n", " attention_masks.append(encoded_dict['attention_mask'])\n", "\n", "input_ids = torch.cat(input_ids, dim=0)\n", "target_ids = torch.cat(target_ids, dim=0)\n", "attention_masks = torch.cat(attention_masks, dim=0)\n", "\n", "print('Original: ', parsed_dataset[0])\n", "print('Token IDs:', input_ids[0])\n", "print('Label token IDs:', target_ids[0])" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Z28QYfLnSGxR", "outputId": "eb9d48d0-cb2d-4596-c752-14b18f6e3590" }, "execution_count": 14, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Original: {'sms': 'Answer the question in one word - true if provided text is spam or false, if provided text is not spam.\\n Q: Is this text spam? \\nText: Go until jurong point, crazy.. Available only in bugis n great world la e buffet... Cine there got amore wat...\\nA: ', 'label': 'true'}\n", "Token IDs: tensor([11801, 8, 822, 16, 80, 1448, 3, 18, 1176, 3,\n", " 99, 937, 1499, 19, 13655, 42, 6136, 6, 3, 99,\n", " 937, 1499, 19, 59, 13655, 5, 1593, 10, 27, 7,\n", " 48, 1499, 13655, 58, 5027, 10, 1263, 552, 10081, 2444,\n", " 500, 6, 6139, 5, 5, 8144, 163, 16, 8143, 159,\n", " 3, 29, 248, 296, 50, 3, 15, 15385, 233, 17270,\n", " 132, 530, 3, 9, 3706, 8036, 17, 233, 71, 10,\n", " 3, 1, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,\n", " 0, 0, 0, 0, 0, 0, 0, 0, 0, 0])\n", "Label token IDs: tensor([1176, 1])\n" ] } ] }, { "cell_type": "markdown", "source": [ "# Split dataset" ], "metadata": { "id": "qD_t0y0KVVSy" } }, { "cell_type": "code", "source": [ "from torch.utils.data import TensorDataset, random_split" ], "metadata": { "id": "vN_SatRIVa4c" }, "execution_count": 15, "outputs": [] }, { "cell_type": "code", "source": [ "dataset = TensorDataset(input_ids, attention_masks, target_ids)\n", "\n", "test_size = 1000\n", "dataset_len = len(dataset)\n", "train_size = int(0.9 * (dataset_len-test_size))\n", "val_size = (dataset_len-test_size) - train_size\n", "\n", "test_dataset, train_dataset, val_dataset = random_split(dataset, [test_size, train_size, val_size])\n", "\n", "print('{:>5,} test samples'.format(test_size))\n", "print('{:>5,} training samples'.format(train_size))\n", "print('{:>5,} validation samples'.format(val_size))" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Mm6vc6lLVW3l", "outputId": "023efb5b-eab3-4675-9900-3918aedae90f" }, "execution_count": 16, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "1,000 test samples\n", "4,116 training samples\n", " 458 validation samples\n" ] } ] }, { "cell_type": "markdown", "source": [ "# Create train and validation loaders" ], "metadata": { "id": "bmgQOP4EVfA1" } }, { "cell_type": "code", "source": [ "from torch.utils.data import DataLoader, RandomSampler, SequentialSampler" ], "metadata": { "id": "CxnQ3cmIVlNh" }, "execution_count": 17, "outputs": [] }, { "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": "0hcpO_onVjEC" }, "execution_count": 18, "outputs": [] }, { "cell_type": "markdown", "source": [ "# Device check" ], "metadata": { "id": "efwhqLyyVu9z" } }, { "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": "ANBCfNGnVwVk", "outputId": "6192e88f-5e61-4de6-b476-de9a6e3a59a6" }, "execution_count": 19, "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": [ "# Load FLAN-T5 model" ], "metadata": { "id": "okTx_ynMV0rH" } }, { "cell_type": "code", "source": [ "from transformers import AutoModelForSeq2SeqLM" ], "metadata": { "id": "Eu-7Eed8WgN0" }, "execution_count": 20, "outputs": [] }, { "cell_type": "code", "source": [ "model = AutoModelForSeq2SeqLM.from_pretrained('google/flan-t5-base')\n", "\n", "model.cuda()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000, "referenced_widgets": [ "3747d0aa68d642449ff32b7efd47d497", "2a84ccf3660a4e24b37bfc1d952f06d9", "43b98452768846eb9b773839a4681cc6", "2dfbcef644a84b558ce99b2ddaf091b6", "9dd02373a1994433a49e0015b76dd858", "42a620dfccb4416c95fbd7a76637dc73", "9d953b41e24c4263b18e1ff2174eb797", "cb409960af114fa690bac72c1d51d2ab", "995a94c35b4c441b86598d1976281711", "4ea2ccb5fa264dd5a042f570c22db7de", "4d5668e5b66d4993b935b077a1dc281c", "cf36c750119449e8a16aa97a9b66a124", "0de691bf20804830ba5e6710c205c9ac", "7ee532c002784554b12fede964c6c05a", "25e5c76c84a8414495b61663250825aa", "12bd0cd379754967bfd5481d5836b7a4", "d55d326ffbdc420da0a399c141f7fb56", "092323b59b734eada8d88197d9f0eb72", "622df288b2ae4f62b776cb101de18b9f", "c72abd216b9444ef9bdb0f8a0a6771b0", "03d5f2402e464b7cb5244db0f824df1d", "4a6e196f590d4b329e0edefc910d4730", "9a04f6723e2a40288eb42eea0134dfaf", "4065d0eed87e4d268de8f4536287e225", "bebca147a83446abaf19c3e3db11744e", "cf525a599ca245b19204bfff3fa1bd11", "b60759f0730343849ef3e51d2c8be38c", "dcc795e3fac0401b9a4d2aac3bd6e8cc", "ed7ca6da408842b38a466097ec9d4616", "0335f29f40564adf9b577707dfb40aa9", "a200da1478fa46a19695a5b2f2c77fd1", "e21e75bbbc4149b4ac85fece44aee355", "c014c271cd374f62a0d113efca14001a" ] }, "id": "JKv9O8kfV2zZ", "outputId": "6893e79a-48f7-4713-c4a4-a9558acbcf7c" }, "execution_count": 21, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "Downloading (…)lve/main/config.json: 0%| | 0.00/1.40k [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "3747d0aa68d642449ff32b7efd47d497" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "Downloading (…)\"pytorch_model.bin\";: 0%| | 0.00/990M [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "cf36c750119449e8a16aa97a9b66a124" } }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "Downloading (…)neration_config.json: 0%| | 0.00/147 [00:00, ?B/s]" ], "application/vnd.jupyter.widget-view+json": { "version_major": 2, "version_minor": 0, "model_id": "9a04f6723e2a40288eb42eea0134dfaf" } }, "metadata": {} }, { "output_type": "execute_result", "data": { "text/plain": [ "T5ForConditionalGeneration(\n", " (shared): Embedding(32128, 768)\n", " (encoder): T5Stack(\n", " (embed_tokens): Embedding(32128, 768)\n", " (block): ModuleList(\n", " (0): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " (relative_attention_bias): Embedding(32, 12)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (1): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (2): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (3): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (4): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (5): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (6): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (7): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (8): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (9): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (10): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (11): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " )\n", " (final_layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (decoder): T5Stack(\n", " (embed_tokens): Embedding(32128, 768)\n", " (block): ModuleList(\n", " (0): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " (relative_attention_bias): Embedding(32, 12)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerCrossAttention(\n", " (EncDecAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (2): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (1): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerCrossAttention(\n", " (EncDecAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (2): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (2): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerCrossAttention(\n", " (EncDecAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (2): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (3): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerCrossAttention(\n", " (EncDecAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (2): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (4): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerCrossAttention(\n", " (EncDecAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (2): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (5): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerCrossAttention(\n", " (EncDecAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (2): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (6): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerCrossAttention(\n", " (EncDecAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (2): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (7): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerCrossAttention(\n", " (EncDecAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (2): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (8): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerCrossAttention(\n", " (EncDecAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (2): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (9): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerCrossAttention(\n", " (EncDecAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (2): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (10): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerCrossAttention(\n", " (EncDecAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (2): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " (11): T5Block(\n", " (layer): ModuleList(\n", " (0): T5LayerSelfAttention(\n", " (SelfAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (1): T5LayerCrossAttention(\n", " (EncDecAttention): T5Attention(\n", " (q): Linear(in_features=768, out_features=768, bias=False)\n", " (k): Linear(in_features=768, out_features=768, bias=False)\n", " (v): Linear(in_features=768, out_features=768, bias=False)\n", " (o): Linear(in_features=768, out_features=768, bias=False)\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (2): T5LayerFF(\n", " (DenseReluDense): T5DenseGatedActDense(\n", " (wi_0): Linear(in_features=768, out_features=2048, bias=False)\n", " (wi_1): Linear(in_features=768, out_features=2048, bias=False)\n", " (wo): Linear(in_features=2048, out_features=768, bias=False)\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " (act): NewGELUActivation()\n", " )\n", " (layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " )\n", " )\n", " )\n", " (final_layer_norm): T5LayerNorm()\n", " (dropout): Dropout(p=0.1, inplace=False)\n", " )\n", " (lm_head): Linear(in_features=768, out_features=32128, bias=False)\n", ")" ] }, "metadata": {}, "execution_count": 21 } ] }, { "cell_type": "markdown", "source": [ "# Helper functions" ], "metadata": { "id": "F_SDAwxoawDy" } }, { "cell_type": "code", "source": [ "import datetime\n", "import numpy as np" ], "metadata": { "id": "s-q6_F38bLVA" }, "execution_count": 22, "outputs": [] }, { "cell_type": "code", "source": [ "def calculate_accuracy(preds, target):\n", " results_ok = 0.0\n", " results_false = 0.0\n", "\n", " for idx, pred in enumerate(preds):\n", " if pred == target[idx]:\n", " results_ok += 1.0\n", " else:\n", " results_false += 1.0\n", "\n", " return results_ok / (results_ok + results_false)\n", "\n", "def format_time(elapsed):\n", " '''\n", " Takes a time in seconds and returns a string hh:mm:ss\n", " '''\n", " elapsed_rounded = int(round((elapsed)))\n", " return str(datetime.timedelta(seconds=elapsed_rounded))" ], "metadata": { "id": "FzUi8908ax61" }, "execution_count": 23, "outputs": [] }, { "cell_type": "markdown", "source": [ "# Init training" ], "metadata": { "id": "ucChBa-9bXJy" } }, { "cell_type": "code", "source": [ "from transformers import get_linear_schedule_with_warmup" ], "metadata": { "id": "c9e7rbGwbdEp" }, "execution_count": 24, "outputs": [] }, { "cell_type": "code", "source": [ "optimizer = torch.optim.AdamW(model.parameters(),\n", " lr = 3e-4,\n", " eps = 1e-8\n", " )\n", "\n", "epochs = 4\n", "\n", "total_steps = len(train_dataloader) * epochs\n", "\n", "scheduler = get_linear_schedule_with_warmup(optimizer, \n", " num_warmup_steps = 0,\n", " num_training_steps = total_steps)" ], "metadata": { "id": "A7XUF4PNbYy8" }, "execution_count": 25, "outputs": [] }, { "cell_type": "markdown", "source": [ "# Training" ], "metadata": { "id": "DAzQWODja0A3" } }, { "cell_type": "code", "source": [ "import random\n", "import time" ], "metadata": { "id": "Hoa7NlU0bI7G" }, "execution_count": 26, "outputs": [] }, { "cell_type": "code", "source": [ "# This training code is based on the `run_glue.py` script here:\n", "# https://github.com/huggingface/transformers/blob/5bfcd0485ece086ebcbed2d008813037968a9e58/examples/run_glue.py#L128\n", "\n", "seed_val = 42\n", "\n", "random.seed(seed_val)\n", "np.random.seed(seed_val)\n", "torch.manual_seed(seed_val)\n", "torch.cuda.manual_seed_all(seed_val)\n", "\n", "training_stats = []\n", "total_t0 = time.time()\n", "\n", "for epoch_i in range(0, epochs):\n", " \n", " # ========================================\n", " # Training\n", " # ========================================\n", "\n", " print(\"\")\n", " print('======== Epoch {:} / {:} ========'.format(epoch_i + 1, epochs))\n", " print('Training...')\n", "\n", " t0 = time.time()\n", "\n", " total_train_loss = 0\n", " total_train_acc = 0\n", "\n", " model.train()\n", "\n", " for step, batch in enumerate(train_dataloader):\n", " if step % 40 == 0 and not step == 0:\n", " elapsed = format_time(time.time() - t0)\n", " print(' Batch {:>5,} of {:>5,}. Elapsed: {:}.'.format(step, len(train_dataloader), elapsed))\n", "\n", "\n", " b_input_ids = batch[0].to(device)\n", " b_input_mask = batch[1].to(device)\n", "\n", " y = batch[2].to(device)\n", " y_ids = y[:, :-1].contiguous()\n", " lm_labels = y[:, 1:].clone().detach()\n", " lm_labels[y[:, 1:] == tokenizer.pad_token_id] = -100\n", "\n", " model.zero_grad() \n", "\n", " outputs = model(\n", " input_ids=b_input_ids,\n", " attention_mask=b_input_mask,\n", " decoder_input_ids=y_ids,\n", " labels=lm_labels\n", " )\n", "\n", " generated_ids = model.generate(\n", " input_ids = b_input_ids,\n", " attention_mask = b_input_mask, \n", " max_length=2, \n", " num_beams=2,\n", " repetition_penalty=2.5, \n", " length_penalty=1.0, \n", " early_stopping=True\n", " )\n", "\n", " preds = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=True) for g in generated_ids]\n", " target = [tokenizer.decode(t, skip_special_tokens=True, clean_up_tokenization_spaces=True) for t in y]\n", " total_train_acc += calculate_accuracy(preds, target) \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", " avg_train_acc = total_train_acc / len(train_dataloader) \n", " \n", " training_time = format_time(time.time() - t0)\n", "\n", " print(\"\")\n", " print(\" Average training loss: {0:.2f}\".format(avg_train_loss))\n", " print(\" Average training acc: {0:.2f}\".format(avg_train_acc))\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_loss = 0\n", " total_eval_accuracy = 0\n", "\n", " for batch in validation_dataloader:\n", "\n", " b_input_ids = batch[0].to(device)\n", " b_input_mask = batch[1].to(device)\n", "\n", " y = batch[2].to(device)\n", " y_ids = y[:, :-1].contiguous()\n", " lm_labels = y[:, 1:].clone().detach()\n", " lm_labels[y[:, 1:] == tokenizer.pad_token_id] = -100\n", " \n", " with torch.no_grad(): \n", "\n", " outputs = model(\n", " input_ids=b_input_ids,\n", " attention_mask=b_input_mask,\n", " decoder_input_ids=y_ids,\n", " labels=lm_labels\n", " )\n", "\n", " loss = outputs['loss']\n", " total_eval_loss += loss.item()\n", "\n", " generated_ids = model.generate(\n", " input_ids = b_input_ids,\n", " attention_mask = b_input_mask, \n", " max_length=2, \n", " num_beams=2,\n", " repetition_penalty=2.5, \n", " length_penalty=1.0, \n", " early_stopping=True\n", " )\n", "\n", " preds = [tokenizer.decode(g, skip_special_tokens=True, clean_up_tokenization_spaces=True) for g in generated_ids]\n", " target = [tokenizer.decode(t, skip_special_tokens=True, clean_up_tokenization_spaces=True) for t in y]\n", " total_eval_accuracy += calculate_accuracy(preds, target) \n", "\n", " avg_val_loss = total_eval_loss / len(validation_dataloader)\n", "\n", " avg_val_accuracy = total_eval_accuracy / len(validation_dataloader)\n", " print(\" Accuracy: {0:.2f}\".format(avg_val_accuracy))\n", " \n", " validation_time = format_time(time.time() - t0)\n", " print(\" Validation took: {:}\".format(validation_time))\n", " print(\" Validation Loss: {0:.2f}\".format(avg_val_loss))\n", "\n", " training_stats.append(\n", " {\n", " 'epoch': epoch_i + 1,\n", " 'Training Loss': avg_train_loss,\n", " 'Training Accur.': avg_train_acc,\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": "xsHxfslka1u5", "outputId": "28c30ee0-6f41-4ede-eb3a-eebd4269c332" }, "execution_count": 27, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "======== Epoch 1 / 4 ========\n", "Training...\n", " Batch 40 of 515. Elapsed: 0:00:46.\n", " Batch 80 of 515. Elapsed: 0:01:30.\n", " Batch 120 of 515. Elapsed: 0:02:14.\n", " Batch 160 of 515. Elapsed: 0:02:59.\n", " Batch 200 of 515. Elapsed: 0:03:44.\n", " Batch 240 of 515. Elapsed: 0:04:28.\n", " Batch 280 of 515. Elapsed: 0:05:13.\n", " Batch 320 of 515. Elapsed: 0:05:57.\n", " Batch 360 of 515. Elapsed: 0:06:42.\n", " Batch 400 of 515. Elapsed: 0:07:26.\n", " Batch 440 of 515. Elapsed: 0:08:11.\n", " Batch 480 of 515. Elapsed: 0:08:55.\n", "\n", " Average training loss: 0.01\n", " Average training acc: 0.59\n", " Training epcoh took: 0:09:34\n", "\n", "Running Validation...\n", " Accuracy: 0.47\n", " Validation took: 0:00:31\n", " Validation Loss: 0.00\n", "\n", "======== Epoch 2 / 4 ========\n", "Training...\n", " Batch 40 of 515. Elapsed: 0:00:44.\n", " Batch 80 of 515. Elapsed: 0:01:29.\n", " Batch 120 of 515. Elapsed: 0:02:13.\n", " Batch 160 of 515. Elapsed: 0:02:58.\n", " Batch 200 of 515. Elapsed: 0:03:42.\n", " Batch 240 of 515. Elapsed: 0:04:27.\n", " Batch 280 of 515. Elapsed: 0:05:11.\n", " Batch 320 of 515. Elapsed: 0:05:56.\n", " Batch 360 of 515. Elapsed: 0:06:40.\n", " Batch 400 of 515. Elapsed: 0:07:25.\n", " Batch 440 of 515. Elapsed: 0:08:09.\n", " Batch 480 of 515. Elapsed: 0:08:54.\n", "\n", " Average training loss: 0.00\n", " Average training acc: 0.59\n", " Training epcoh took: 0:09:32\n", "\n", "Running Validation...\n", " Accuracy: 0.46\n", " Validation took: 0:00:31\n", " Validation Loss: 0.00\n", "\n", "======== Epoch 3 / 4 ========\n", "Training...\n", " Batch 40 of 515. Elapsed: 0:00:44.\n", " Batch 80 of 515. Elapsed: 0:01:34.\n", " Batch 120 of 515. Elapsed: 0:02:20.\n", " Batch 160 of 515. Elapsed: 0:03:05.\n", " Batch 200 of 515. Elapsed: 0:03:49.\n", " Batch 240 of 515. Elapsed: 0:04:34.\n", " Batch 280 of 515. Elapsed: 0:05:18.\n", " Batch 320 of 515. Elapsed: 0:06:03.\n", " Batch 360 of 515. Elapsed: 0:06:47.\n", " Batch 400 of 515. Elapsed: 0:07:32.\n", " Batch 440 of 515. Elapsed: 0:08:16.\n", " Batch 480 of 515. Elapsed: 0:09:00.\n", "\n", " Average training loss: 0.00\n", " Average training acc: 0.59\n", " Training epcoh took: 0:09:39\n", "\n", "Running Validation...\n", " Accuracy: 0.46\n", " Validation took: 0:00:31\n", " Validation Loss: 0.00\n", "\n", "======== Epoch 4 / 4 ========\n", "Training...\n", " Batch 40 of 515. Elapsed: 0:00:45.\n", " Batch 80 of 515. Elapsed: 0:01:29.\n", " Batch 120 of 515. Elapsed: 0:02:14.\n", " Batch 160 of 515. Elapsed: 0:02:58.\n", " Batch 200 of 515. Elapsed: 0:03:42.\n", " Batch 240 of 515. Elapsed: 0:04:27.\n", " Batch 280 of 515. Elapsed: 0:05:11.\n", " Batch 320 of 515. Elapsed: 0:05:56.\n", " Batch 360 of 515. Elapsed: 0:06:40.\n", " Batch 400 of 515. Elapsed: 0:07:24.\n", " Batch 440 of 515. Elapsed: 0:08:09.\n", " Batch 480 of 515. Elapsed: 0:08:53.\n", "\n", " Average training loss: 0.00\n", " Average training acc: 0.58\n", " Training epcoh took: 0:09:32\n", "\n", "Running Validation...\n", " Accuracy: 0.46\n", " Validation took: 0:00:31\n", " Validation Loss: 0.00\n", "\n", "Training complete!\n", "Total training took 0:40:22 (h:mm:ss)\n" ] } ] }, { "cell_type": "markdown", "source": [ "# Train summary" ], "metadata": { "id": "xIpFPoRb91Or" } }, { "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": 206 }, "id": "GjYqBrrO93Oh", "outputId": "0087ee68-c017-41fd-db84-ca6e0d25fb12" }, "execution_count": 28, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " Training Loss Training Accur. Valid. Loss Valid. Accur. \\\n", "epoch \n", "1 5.27e-03 0.59 0.0 0.47 \n", "2 2.74e-08 0.59 0.0 0.46 \n", "3 1.58e-08 0.59 0.0 0.46 \n", "4 1.55e-08 0.58 0.0 0.46 \n", "\n", " Training Time Validation Time \n", "epoch \n", "1 0:09:34 0:00:31 \n", "2 0:09:32 0:00:31 \n", "3 0:09:39 0:00:31 \n", "4 0:09:32 0:00:31 " ], "text/html": [ "\n", "
\n", " | Training Loss | \n", "Training Accur. | \n", "Valid. Loss | \n", "Valid. Accur. | \n", "Training Time | \n", "Validation Time | \n", "
---|---|---|---|---|---|---|
epoch | \n", "\n", " | \n", " | \n", " | \n", " | \n", " | \n", " |
1 | \n", "5.27e-03 | \n", "0.59 | \n", "0.0 | \n", "0.47 | \n", "0:09:34 | \n", "0:00:31 | \n", "
2 | \n", "2.74e-08 | \n", "0.59 | \n", "0.0 | \n", "0.46 | \n", "0:09:32 | \n", "0:00:31 | \n", "
3 | \n", "1.58e-08 | \n", "0.59 | \n", "0.0 | \n", "0.46 | \n", "0:09:39 | \n", "0:00:31 | \n", "
4 | \n", "1.55e-08 | \n", "0.58 | \n", "0.0 | \n", "0.46 | \n", "0:09:32 | \n", "0:00:31 | \n", "