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  "cells": [
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      "cell_type": "markdown",
      "metadata": {
        "id": "XKGPcDdJKeib"
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      "source": [
        "# Installing *biome.text*"
      ]
    },
    {
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      "metadata": {
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        "id": "A7o6tpvZnuTK",
        "outputId": "5e53d3e9-9598-4037-8602-df2baeb21fdc"
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      "source": [
        "!pip install -U pip\n",
        "!pip install -U biome-text\n",
        "exit(0)"
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            "\u001b[?25hInstalling collected packages: pip\n",
            "  Found existing installation: pip 19.3.1\n",
            "    Uninstalling pip-19.3.1:\n",
            "      Successfully uninstalled pip-19.3.1\n",
            "Successfully installed pip-21.0.1\n",
            "Collecting biome-text\n",
            "  Downloading biome_text-2.0.0-py3-none-any.whl (1.8 MB)\n",
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            "\u001b[K     |████████████████████████████████| 121 kB 34.8 MB/s \n",
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            "Building wheels for collected packages: overrides, flatdict, jsonnet, databricks-cli, sqlalchemy, idna-ssl, alembic, contextvars, gpustat, Mako, prometheus-flask-exporter, sacremoses\n",
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            "Installing collected packages: urllib3, multidict, immutables, yarl, soupsieve, jmespath, idna-ssl, contextvars, async-timeout, tqdm, smmap, opencensus-context, isodate, hiredis, botocore, blessings, beautifulsoup4, aiohttp, websocket-client, tokenizers, thinc, sqlalchemy, sacremoses, s3transfer, redis, python-editor, py-spy, opencensus, msrest, Mako, gpustat, gitdb, cryptography, colorful, colorama, azure-core, aioredis, aiohttp-cors, zope.interface, zope.event, xxhash, websockets, uvloop, transformers, tensorboardX, starlette, spacy, sentencepiece, ray, querystring-parser, pydantic, pyarrow, prometheus-flask-exporter, overrides, jsonpickle, jsonnet, httptools, h11, gunicorn, greenlet, gorilla, gitpython, fsspec, docker, databricks-cli, boto3, azure-storage-blob, alembic, xlrd, uvicorn, s3fs, mlflow, lxml, ipywidgets, gevent, flatdict, flask-cors, fastapi, elasticsearch, distributed, datasets, captum, cachey, allennlp, biome-text\n",
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            "    Found existing installation: beautifulsoup4 4.6.3\n",
            "    Uninstalling beautifulsoup4-4.6.3:\n",
            "      Successfully uninstalled beautifulsoup4-4.6.3\n",
            "  Attempting uninstall: thinc\n",
            "    Found existing installation: thinc 7.4.0\n",
            "    Uninstalling thinc-7.4.0:\n",
            "      Successfully uninstalled thinc-7.4.0\n",
            "  Attempting uninstall: sqlalchemy\n",
            "    Found existing installation: SQLAlchemy 1.3.23\n",
            "    Uninstalling SQLAlchemy-1.3.23:\n",
            "      Successfully uninstalled SQLAlchemy-1.3.23\n",
            "  Attempting uninstall: spacy\n",
            "    Found existing installation: spacy 2.2.4\n",
            "    Uninstalling spacy-2.2.4:\n",
            "      Successfully uninstalled spacy-2.2.4\n",
            "  Attempting uninstall: pyarrow\n",
            "    Found existing installation: pyarrow 0.14.1\n",
            "    Uninstalling pyarrow-0.14.1:\n",
            "      Successfully uninstalled pyarrow-0.14.1\n",
            "  Attempting uninstall: xlrd\n",
            "    Found existing installation: xlrd 1.1.0\n",
            "    Uninstalling xlrd-1.1.0:\n",
            "      Successfully uninstalled xlrd-1.1.0\n",
            "  Attempting uninstall: lxml\n",
            "    Found existing installation: lxml 4.2.6\n",
            "    Uninstalling lxml-4.2.6:\n",
            "      Successfully uninstalled lxml-4.2.6\n",
            "  Attempting uninstall: ipywidgets\n",
            "    Found existing installation: ipywidgets 7.6.3\n",
            "    Uninstalling ipywidgets-7.6.3:\n",
            "      Successfully uninstalled ipywidgets-7.6.3\n",
            "  Attempting uninstall: distributed\n",
            "    Found existing installation: distributed 1.25.3\n",
            "    Uninstalling distributed-1.25.3:\n",
            "      Successfully uninstalled distributed-1.25.3\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\u001b[0m\n",
            "Successfully installed Mako-1.1.4 aiohttp-3.7.3 aiohttp-cors-0.7.0 aioredis-1.3.1 alembic-1.5.4 allennlp-1.3.0 async-timeout-3.0.1 azure-core-1.11.0 azure-storage-blob-12.7.1 beautifulsoup4-4.9.3 biome-text-2.0.0 blessings-1.7 boto3-1.17.8 botocore-1.20.8 cachey-0.2.1 captum-0.2.0 colorama-0.4.4 colorful-0.5.4 contextvars-2.4 cryptography-3.4.5 databricks-cli-0.14.1 datasets-1.1.3 distributed-2.17.0 docker-4.4.2 elasticsearch-7.1.0 fastapi-0.55.1 flask-cors-3.0.10 flatdict-4.0.1 fsspec-0.8.5 gevent-20.9.0 gitdb-4.0.5 gitpython-3.1.13 gorilla-0.3.0 gpustat-0.6.0 greenlet-1.0.0 gunicorn-20.0.4 h11-0.9.0 hiredis-1.1.0 httptools-0.1.1 idna-ssl-1.1.0 immutables-0.15 ipywidgets-7.5.1 isodate-0.6.0 jmespath-0.10.0 jsonnet-0.17.0 jsonpickle-2.0.0 lxml-4.5.2 mlflow-1.9.1 msrest-0.6.21 multidict-5.1.0 opencensus-0.7.12 opencensus-context-0.1.2 overrides-3.1.0 prometheus-flask-exporter-0.18.1 py-spy-0.3.4 pyarrow-3.0.0 pydantic-1.7.3 python-editor-1.0.4 querystring-parser-1.2.4 ray-1.0.1.post1 redis-3.4.1 s3fs-0.4.2 s3transfer-0.3.4 sacremoses-0.0.43 sentencepiece-0.1.95 smmap-3.0.5 soupsieve-2.2 spacy-2.3.5 sqlalchemy-1.3.13 starlette-0.13.2 tensorboardX-2.1 thinc-7.4.5 tokenizers-0.9.4 tqdm-4.49.0 transformers-4.0.1 urllib3-1.25.11 uvicorn-0.11.8 uvloop-0.14.0 websocket-client-0.57.0 websockets-8.1 xlrd-1.2.0 xxhash-2.0.0 yarl-1.6.3 zope.event-4.5.0 zope.interface-5.2.0\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.colab-display-data+json": {
              "pip_warning": {
                "packages": [
                  "ipywidgets"
                ]
              }
            }
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MLMLYh6rKkji"
      },
      "source": [
        "# Downloading the data\n",
        "\n",
        "Here we download the preprocessed data and the pre trained word vectors."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PmWnzfEfn-G1",
        "outputId": "4a513f2a-ea02-43f2-b4f0-6aeac42b419b"
      },
      "source": [
        "!git clone https://github.com/recognai/cantemist-ner/"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'cantemist-ner'...\n",
            "remote: Enumerating objects: 39, done.\u001b[K\n",
            "remote: Counting objects: 100% (39/39), done.\u001b[K\n",
            "remote: Compressing objects: 100% (25/25), done.\u001b[K\n",
            "remote: Total 39 (delta 12), reused 29 (delta 8), pack-reused 0\u001b[K\n",
            "Unpacking objects: 100% (39/39), done.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "18zRDgbX2HfJ",
        "outputId": "5581f445-6464-4b9b-8180-00381ac81e65"
      },
      "source": [
        "!wget https://dl.fbaipublicfiles.com/fasttext/vectors-crawl/cc.es.300.vec.gz"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2021-02-16 09:26:27--  https://dl.fbaipublicfiles.com/fasttext/vectors-crawl/cc.es.300.vec.gz\n",
            "Resolving dl.fbaipublicfiles.com (dl.fbaipublicfiles.com)... 104.22.75.142, 104.22.74.142, 172.67.9.4, ...\n",
            "Connecting to dl.fbaipublicfiles.com (dl.fbaipublicfiles.com)|104.22.75.142|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 1285580896 (1.2G) [binary/octet-stream]\n",
            "Saving to: ‘cc.es.300.vec.gz’\n",
            "\n",
            "cc.es.300.vec.gz    100%[===================>]   1.20G  11.8MB/s    in 1m 45s  \n",
            "\n",
            "2021-02-16 09:28:13 (11.7 MB/s) - ‘cc.es.300.vec.gz’ saved [1285580896/1285580896]\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EihBMi8jKo0z"
      },
      "source": [
        "# Training the system"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EaKVqIh-0BQl"
      },
      "source": [
        "from biome.text import Pipeline, Dataset, VocabularyConfiguration, TrainerConfiguration"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "XQ4ClmKnM-O8"
      },
      "source": [
        "## Loading the datasets\n",
        "\n",
        "These datasets were created using the *NER_dataprep.ipynb* and *NER_dataprep_test.ipynb* notebooks in our [cantemist-ner](https://github.com/recognai/cantemist-ner) repo."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 191,
          "referenced_widgets": [
            "7173294ffab24e46b53df2fa0666a33b",
            "ca0f54db1f28426a98516d7aeb5bb96d",
            "0094f3a750794863b7b59a8eafe3dcb4",
            "b8563aaf7bc2418491dbfa84e3b09f03",
            "862d290ea0d44cbda0826d4cc2d2783b",
            "3e9cafd2c69b48569f0032704c51e52b",
            "36166c6e49db4dca8970ce6ba44237db",
            "0bf55f5a088f41718d62138ecd0b6ed1",
            "3a766b5e1b504ea3af4d803b76df9bcf",
            "3416eb0c17c246b9bdf2ac94cf778c77",
            "6a7f00f9765f40d89b5964dd60846f47",
            "ad486879437e419296bd0905a5e38c3d",
            "cab604a3b0644f19a291993c18df3f6d",
            "437a266364464761bd454abbf0c70b1f",
            "99b9486cd1c7453c92707a9b78a9746b",
            "b58ce9536d8c45fd92677ee8554fc4e2",
            "d8882ebe8aed41e9bd1e813119151404",
            "65d0c49e06f04db8be062f36f1dea28e",
            "1d7634199eb243eea81f5c86dcaf7a4d",
            "c2385f6f051e4ce58bce47e2d3b42998",
            "1ec8c4f82bae43b482b748565574c517",
            "82f75783d24a4095b346a1d8d526b928",
            "97e2d36bd90b45e580b7cf46077d106a",
            "3f995cb880284051ac1cbf85a1dcae90"
          ]
        },
        "id": "pcmstXIU0FHc",
        "outputId": "c443cd94-dd21-4f06-f16c-1a7d794d4fde"
      },
      "source": [
        "train_ds = Dataset.from_json(\"cantemist-ner/data/NER/train_full.json\")\n",
        "# This test dataset was released after the competition ended:\n",
        "test_ds = Dataset.from_json(\"cantemist-ner/data/NER/gold_test.json\")\n",
        "\n",
        "# for biome.text v2 we need to rename the \"labels\" column containing the NER tags\n",
        "train_ds.rename_column_(\"labels\", \"tags\")\n",
        "test_ds.rename_column_(\"labels\", \"tags\")"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "7173294ffab24e46b53df2fa0666a33b",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=1202.0, style=ProgressStyle(description…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Using custom data configuration default\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\n",
            "Downloading and preparing dataset json/default-4ecdc33b48e84d7c (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/json/default-4ecdc33b48e84d7c/0.0.0/70d89ed4db1394f028c651589fcab6d6b28dddcabbe39d3b21b4d41f9a708514...\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "3a766b5e1b504ea3af4d803b76df9bcf",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=1.0, bar_style='info', layout=Layout(width='20px'), max=1.0), HTML(value=''…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Dataset json downloaded and prepared to /root/.cache/huggingface/datasets/json/default-4ecdc33b48e84d7c/0.0.0/70d89ed4db1394f028c651589fcab6d6b28dddcabbe39d3b21b4d41f9a708514. Subsequent calls will reuse this data.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "Using custom data configuration default\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Downloading and preparing dataset json/default-bbf39d6db3ce5216 (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /root/.cache/huggingface/datasets/json/default-bbf39d6db3ce5216/0.0.0/70d89ed4db1394f028c651589fcab6d6b28dddcabbe39d3b21b4d41f9a708514...\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "d8882ebe8aed41e9bd1e813119151404",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=1.0, bar_style='info', layout=Layout(width='20px'), max=1.0), HTML(value=''…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Dataset json downloaded and prepared to /root/.cache/huggingface/datasets/json/default-bbf39d6db3ce5216/0.0.0/70d89ed4db1394f028c651589fcab6d6b28dddcabbe39d3b21b4d41f9a708514. Subsequent calls will reuse this data.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "D0zg_ZJYNE3E"
      },
      "source": [
        "## Defining the pipeline\n",
        "\n",
        "The architecture and hyerparameters were found by means of a random search HPO."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g99nbFic0SkL"
      },
      "source": [
        "pipeline_config = {\n",
        "  'name': 'candemist-ner-first-hpo',\n",
        "  'features': {\n",
        "    'word': {\n",
        "      'embedding_dim': 300,\n",
        "      'lowercase_tokens': True,\n",
        "      'trainable': True,\n",
        "      'weights_file': \"/content/cc.es.300.vec.gz\"\n",
        "    },\n",
        "    'char': {\n",
        "      'embedding_dim': 64,\n",
        "      'lowercase_characters': True,\n",
        "      'encoder': {\n",
        "        'bidirectional': True,\n",
        "        'hidden_size': 128,\n",
        "        'num_layers': 1,\n",
        "        'type': 'gru'\n",
        "      },\n",
        "    'dropout': 0.16517050992687604\n",
        "    },\n",
        "  },\n",
        "  'encoder': {\n",
        "    'bidirectional': True,\n",
        "    'hidden_size': 512,\n",
        "    'input_size': 556,\n",
        "    'num_layers': 1,\n",
        "    'type': 'lstm'\n",
        "  },  \n",
        "  'head': {\n",
        "    'dropout': 0.2689579604286324,\n",
        "    'labels': ['MORFOLOGIA_NEOPLASIA'],\n",
        "    'type': 'TokenClassification'\n",
        "  },\n",
        "}"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y69teacP1mG9",
        "outputId": "e1067889-4dd4-4a81-c829-620d20ad6d0f"
      },
      "source": [
        "pl = Pipeline.from_config(pipeline_config)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[38;5;2m✔ Download and installation successful\u001b[0m\n",
            "You can now load the model via spacy.load('en_core_web_sm')\n",
            "\u001b[38;5;2m✔ Linking successful\u001b[0m\n",
            "/usr/local/lib/python3.6/dist-packages/en_core_web_sm -->\n",
            "/usr/local/lib/python3.6/dist-packages/spacy/data/en\n",
            "You can now load the model via spacy.load('en')\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vJ7X7UawNSwZ"
      },
      "source": [
        "## Defining the vocabulary\n",
        "\n",
        "Only include words that appear at least two times in the `train_ds` dataset."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iRTjjJp63bV6"
      },
      "source": [
        "vocab_config = VocabularyConfiguration(\n",
        "    datasets=[train_ds], min_count={\"word\": 2}\n",
        ")"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yI7bPZS7NJGE"
      },
      "source": [
        "## Defining the trainer\n",
        "\n",
        "The hyerparameters were found by means of a random search HPO."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2BFgdSL73mic"
      },
      "source": [
        "trainer_dict={\n",
        "    \"optimizer\": {\n",
        "        \"type\": \"adamw\",\n",
        "        \"lr\": 0.0038931174186587806,\n",
        "        \"weight_decay\": 0.01,\n",
        "    },\n",
        "    \"learning_rate_scheduler\": {\n",
        "      \"type\": \"step\",\n",
        "      \"step_size\":2, \n",
        "      \"gamma\":0.1\n",
        "    },\n",
        "    \"batch_size\": 32,\n",
        "    \"num_epochs\": 4,\n",
        "    \"validation_metric\": \"+f1-measure-overall\",\n",
        "    \"patience\":3\n",
        "}"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "aAE9SsCQMxAZ"
      },
      "source": [
        "trainer_config = TrainerConfiguration(**trainer_dict)"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gEY3z0qSNcQ5"
      },
      "source": [
        "## Training the pipeline"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "3b8208d3d0f94fa8aa61c0c2947f6117",
            "e0cff70183a8488c80848902ce090f8a",
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        },
        "id": "lwyb6SdW3wPL",
        "outputId": "2a734e68-1127-494e-846c-34cf1eedad21"
      },
      "source": [
        "pl.train(\n",
        "    output=\"output\",\n",
        "    training=train_ds,\n",
        "    test=test_ds,\n",
        "    trainer=trainer_config,\n",
        "    vocab_config=vocab_config,\n",
        ")"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2021-02-16 09:40:03,935 - allennlp.data.vocabulary - INFO - Fitting token dictionary from dataset.\n",
            "building vocab: 0it [00:00, ?it/s]"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "3b8208d3d0f94fa8aa61c0c2947f6117",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='Loading instances into memory', max=35877.0, style=Progre…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "2021-02-16 09:40:10,106 - biome.text.dataset - INFO - Caching instances to /root/.cache/huggingface/datasets/json/default-7b14c7191bb43b2a/0.0.0/70d89ed4db1394f028c651589fcab6d6b28dddcabbe39d3b21b4d41f9a708514/76729142bb3937f9.instance_list)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "building vocab: 35877it [00:16, 2162.79it/s]\n",
            "2021-02-16 09:40:20,566 - allennlp.modules.token_embedders.embedding - INFO - Reading pretrained embeddings from file\n",
            "2021-02-16 09:40:20,571 - allennlp.modules.token_embedders.embedding - INFO - Recognized a header line in the embedding file with number of tokens: 2000000\n",
            "100%|##########| 2000000/2000000 [00:30<00:00, 66292.26it/s]\n",
            "2021-02-16 09:40:50,764 - allennlp.modules.token_embedders.embedding - INFO - Initializing pre-trained embedding layer\n",
            "2021-02-16 09:40:50,940 - allennlp.modules.token_embedders.embedding - INFO - Pretrained embeddings were found for 11989 out of 14126 tokens\n",
            "WARNING:root:Embedding at model_path, _head.backbone.embedder.token_embedder_char._embedding._module cannot locate the pretrained_file.  If you are fine-tuning and want to use using pretrained_file for embedding extension, please pass the mapping by --embedding-sources argument.\n",
            "2021-02-16 09:40:50,971 - biome.text.dataset - WARNING - Reusing cached instances (/root/.cache/huggingface/datasets/json/default-7b14c7191bb43b2a/0.0.0/70d89ed4db1394f028c651589fcab6d6b28dddcabbe39d3b21b4d41f9a708514/76729142bb3937f9.instance_list)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "be8fc467d391413084e19fbbda430bed",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='Loading instances into memory', max=10774.0, style=Progre…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "2021-02-16 09:40:56,399 - biome.text.dataset - INFO - Caching instances to /root/.cache/huggingface/datasets/json/default-cffa4ea9ee35ebae/0.0.0/70d89ed4db1394f028c651589fcab6d6b28dddcabbe39d3b21b4d41f9a708514/90e04dc5c0c285ee.instance_list)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "2021-02-16 09:40:57,962 - allennlp.common.params - INFO - random_seed = 13370\n",
            "2021-02-16 09:40:57,963 - allennlp.common.params - INFO - numpy_seed = 1337\n",
            "2021-02-16 09:40:57,964 - allennlp.common.params - INFO - pytorch_seed = 133\n",
            "2021-02-16 09:40:57,973 - allennlp.common.checks - INFO - Pytorch version: 1.7.0+cu101\n",
            "2021-02-16 09:40:58,008 - allennlp.common.params - INFO - type = gradient_descent\n",
            "2021-02-16 09:40:58,008 - allennlp.common.params - INFO - local_rank = 0\n",
            "2021-02-16 09:40:58,009 - allennlp.common.params - INFO - patience = 3\n",
            "2021-02-16 09:40:58,010 - allennlp.common.params - INFO - validation_metric = +f1-measure-overall\n",
            "2021-02-16 09:40:58,012 - allennlp.common.params - INFO - num_epochs = 4\n",
            "2021-02-16 09:40:58,013 - allennlp.common.params - INFO - cuda_device = None\n",
            "2021-02-16 09:40:58,015 - allennlp.common.params - INFO - grad_norm = None\n",
            "2021-02-16 09:40:58,018 - allennlp.common.params - INFO - grad_clipping = None\n",
            "2021-02-16 09:40:58,020 - allennlp.common.params - INFO - distributed = False\n",
            "2021-02-16 09:40:58,020 - allennlp.common.params - INFO - world_size = 1\n",
            "2021-02-16 09:40:58,022 - allennlp.common.params - INFO - num_gradient_accumulation_steps = 1\n",
            "2021-02-16 09:40:58,024 - allennlp.common.params - INFO - use_amp = False\n",
            "2021-02-16 09:40:58,026 - allennlp.common.params - INFO - no_grad = None\n",
            "2021-02-16 09:40:58,027 - allennlp.common.params - INFO - momentum_scheduler = None\n",
            "2021-02-16 09:40:58,028 - allennlp.common.params - INFO - moving_average = None\n",
            "2021-02-16 09:40:58,030 - allennlp.common.params - INFO - batch_callbacks = None\n",
            "2021-02-16 09:40:58,031 - allennlp.common.params - INFO - end_callbacks = None\n",
            "2021-02-16 09:40:58,033 - allennlp.common.params - INFO - trainer_callbacks = None\n",
            "2021-02-16 09:41:12,094 - allennlp.common.params - INFO - optimizer.type = adamw\n",
            "2021-02-16 09:41:12,095 - allennlp.common.params - INFO - optimizer.parameter_groups = None\n",
            "2021-02-16 09:41:12,096 - allennlp.common.params - INFO - optimizer.lr = 0.0038931174186587806\n",
            "2021-02-16 09:41:12,103 - allennlp.common.params - INFO - optimizer.betas = (0.9, 0.999)\n",
            "2021-02-16 09:41:12,104 - allennlp.common.params - INFO - optimizer.eps = 1e-08\n",
            "2021-02-16 09:41:12,106 - allennlp.common.params - INFO - optimizer.weight_decay = 0.01\n",
            "2021-02-16 09:41:12,107 - allennlp.common.params - INFO - optimizer.amsgrad = False\n",
            "2021-02-16 09:41:12,108 - allennlp.training.optimizers - INFO - Number of trainable parameters: 8781136\n",
            "2021-02-16 09:41:12,112 - allennlp.common.util - INFO - The following parameters are Frozen (without gradient):\n",
            "2021-02-16 09:41:12,113 - allennlp.common.util - INFO - _head._crf._constraint_mask\n",
            "2021-02-16 09:41:12,114 - allennlp.common.util - INFO - The following parameters are Tunable (with gradient):\n",
            "2021-02-16 09:41:12,115 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_word.weight\n",
            "2021-02-16 09:41:12,116 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_char._embedding._module.weight\n",
            "2021-02-16 09:41:12,117 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_char._encoder._module._module.weight_ih_l0\n",
            "2021-02-16 09:41:12,118 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_char._encoder._module._module.weight_hh_l0\n",
            "2021-02-16 09:41:12,119 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_char._encoder._module._module.bias_ih_l0\n",
            "2021-02-16 09:41:12,119 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_char._encoder._module._module.bias_hh_l0\n",
            "2021-02-16 09:41:12,120 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_char._encoder._module._module.weight_ih_l0_reverse\n",
            "2021-02-16 09:41:12,121 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_char._encoder._module._module.weight_hh_l0_reverse\n",
            "2021-02-16 09:41:12,121 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_char._encoder._module._module.bias_ih_l0_reverse\n",
            "2021-02-16 09:41:12,122 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_char._encoder._module._module.bias_hh_l0_reverse\n",
            "2021-02-16 09:41:12,123 - allennlp.common.util - INFO - _head.backbone.encoder._module.weight_ih_l0\n",
            "2021-02-16 09:41:12,124 - allennlp.common.util - INFO - _head.backbone.encoder._module.weight_hh_l0\n",
            "2021-02-16 09:41:12,124 - allennlp.common.util - INFO - _head.backbone.encoder._module.bias_ih_l0\n",
            "2021-02-16 09:41:12,125 - allennlp.common.util - INFO - _head.backbone.encoder._module.bias_hh_l0\n",
            "2021-02-16 09:41:12,126 - allennlp.common.util - INFO - _head.backbone.encoder._module.weight_ih_l0_reverse\n",
            "2021-02-16 09:41:12,126 - allennlp.common.util - INFO - _head.backbone.encoder._module.weight_hh_l0_reverse\n",
            "2021-02-16 09:41:12,127 - allennlp.common.util - INFO - _head.backbone.encoder._module.bias_ih_l0_reverse\n",
            "2021-02-16 09:41:12,127 - allennlp.common.util - INFO - _head.backbone.encoder._module.bias_hh_l0_reverse\n",
            "2021-02-16 09:41:12,128 - allennlp.common.util - INFO - _head._label_projection_layer._module.weight\n",
            "2021-02-16 09:41:12,129 - allennlp.common.util - INFO - _head._label_projection_layer._module.bias\n",
            "2021-02-16 09:41:12,130 - allennlp.common.util - INFO - _head._crf.transitions\n",
            "2021-02-16 09:41:12,131 - allennlp.common.util - INFO - _head._crf.start_transitions\n",
            "2021-02-16 09:41:12,131 - allennlp.common.util - INFO - _head._crf.end_transitions\n",
            "2021-02-16 09:41:12,132 - allennlp.common.params - INFO - learning_rate_scheduler.type = step\n",
            "2021-02-16 09:41:12,133 - allennlp.common.params - INFO - learning_rate_scheduler.step_size = 2\n",
            "2021-02-16 09:41:12,134 - allennlp.common.params - INFO - learning_rate_scheduler.gamma = 0.1\n",
            "2021-02-16 09:41:12,134 - allennlp.common.params - INFO - learning_rate_scheduler.last_epoch = -1\n",
            "2021-02-16 09:41:12,135 - allennlp.common.params - INFO - checkpointer.type = default\n",
            "2021-02-16 09:41:12,136 - allennlp.common.params - INFO - checkpointer.keep_serialized_model_every_num_seconds = None\n",
            "2021-02-16 09:41:12,137 - allennlp.common.params - INFO - checkpointer.num_serialized_models_to_keep = 1\n",
            "2021-02-16 09:41:12,138 - allennlp.common.params - INFO - checkpointer.model_save_interval = None\n",
            "2021-02-16 09:41:12,138 - allennlp.common.params - INFO - tensorboard_writer.summary_interval = 100\n",
            "2021-02-16 09:41:12,139 - allennlp.common.params - INFO - tensorboard_writer.histogram_interval = None\n",
            "2021-02-16 09:41:12,140 - allennlp.common.params - INFO - tensorboard_writer.batch_size_interval = None\n",
            "2021-02-16 09:41:12,141 - allennlp.common.params - INFO - tensorboard_writer.should_log_parameter_statistics = True\n",
            "2021-02-16 09:41:12,141 - allennlp.common.params - INFO - tensorboard_writer.should_log_learning_rate = True\n",
            "2021-02-16 09:41:12,142 - allennlp.common.params - INFO - tensorboard_writer.get_batch_num_total = None\n",
            "2021-02-16 09:41:12,158 - allennlp.training.trainer - INFO - Beginning training.\n",
            "2021-02-16 09:41:12,158 - allennlp.training.trainer - INFO - Epoch 0/3\n",
            "2021-02-16 09:41:12,159 - allennlp.training.trainer - INFO - Worker 0 memory usage: 3.6G\n",
            "2021-02-16 09:41:12,162 - allennlp.training.trainer - INFO - GPU 0 memory usage: 50M\n",
            "2021-02-16 09:41:12,163 - allennlp.training.trainer - INFO - Training\n",
            "accuracy: 0.9830, precision-MORFOLOGIA_NEOPLASIA: 0.7023, recall-MORFOLOGIA_NEOPLASIA: 0.6747, f1-measure-MORFOLOGIA_NEOPLASIA: 0.6882, precision-overall: 0.7023, recall-overall: 0.6747, f1-measure-overall: 0.6882, batch_loss: 0.2842, loss: 35.1975 ||: 100%|##########| 1122/1122 [03:23<00:00,  5.51it/s]\n",
            "2021-02-16 09:44:36,072 - allennlp.training.tensorboard_writer - INFO -                                     Training |  Validation\n",
            "2021-02-16 09:44:36,073 - allennlp.training.tensorboard_writer - INFO - accuracy                        |     0.983  |       N/A\n",
            "2021-02-16 09:44:36,076 - allennlp.training.tensorboard_writer - INFO - f1-measure-MORFOLOGIA_NEOPLASIA |     0.688  |       N/A\n",
            "2021-02-16 09:44:36,080 - allennlp.training.tensorboard_writer - INFO - f1-measure-overall              |     0.688  |       N/A\n",
            "2021-02-16 09:44:36,082 - allennlp.training.tensorboard_writer - INFO - gpu_0_memory_MB                 |    50.197  |       N/A\n",
            "2021-02-16 09:44:36,084 - allennlp.training.tensorboard_writer - INFO - loss                            |    35.198  |       N/A\n",
            "2021-02-16 09:44:36,086 - allennlp.training.tensorboard_writer - INFO - precision-MORFOLOGIA_NEOPLASIA  |     0.702  |       N/A\n",
            "2021-02-16 09:44:36,087 - allennlp.training.tensorboard_writer - INFO - precision-overall               |     0.702  |       N/A\n",
            "2021-02-16 09:44:36,088 - allennlp.training.tensorboard_writer - INFO - recall-MORFOLOGIA_NEOPLASIA     |     0.675  |       N/A\n",
            "2021-02-16 09:44:36,091 - allennlp.training.tensorboard_writer - INFO - recall-overall                  |     0.675  |       N/A\n",
            "2021-02-16 09:44:36,092 - allennlp.training.tensorboard_writer - INFO - worker_0_memory_MB              |  3660.348  |       N/A\n",
            "2021-02-16 09:44:36,249 - allennlp.training.checkpointer - INFO - Best validation performance so far. Copying weights to 'output/best.th'.\n",
            "2021-02-16 09:44:36,344 - allennlp.training.trainer - INFO - Epoch duration: 0:03:24.185749\n",
            "2021-02-16 09:44:36,361 - allennlp.training.trainer - INFO - Estimated training time remaining: 0:10:12\n",
            "2021-02-16 09:44:36,362 - allennlp.training.trainer - INFO - Epoch 1/3\n",
            "2021-02-16 09:44:36,363 - allennlp.training.trainer - INFO - Worker 0 memory usage: 3.7G\n",
            "2021-02-16 09:44:36,366 - allennlp.training.trainer - INFO - GPU 0 memory usage: 302M\n",
            "2021-02-16 09:44:36,373 - allennlp.training.trainer - INFO - Training\n",
            "accuracy: 0.9899, precision-MORFOLOGIA_NEOPLASIA: 0.8509, recall-MORFOLOGIA_NEOPLASIA: 0.8340, f1-measure-MORFOLOGIA_NEOPLASIA: 0.8424, precision-overall: 0.8509, recall-overall: 0.8340, f1-measure-overall: 0.8424, batch_loss: 0.2272, loss: 10.3158 ||: 100%|##########| 1122/1122 [03:21<00:00,  5.58it/s]\n",
            "2021-02-16 09:47:57,480 - allennlp.training.tensorboard_writer - INFO -                                     Training |  Validation\n",
            "2021-02-16 09:47:57,482 - allennlp.training.tensorboard_writer - INFO - accuracy                        |     0.990  |       N/A\n",
            "2021-02-16 09:47:57,486 - allennlp.training.tensorboard_writer - INFO - f1-measure-MORFOLOGIA_NEOPLASIA |     0.842  |       N/A\n",
            "2021-02-16 09:47:57,491 - allennlp.training.tensorboard_writer - INFO - f1-measure-overall              |     0.842  |       N/A\n",
            "2021-02-16 09:47:57,492 - allennlp.training.tensorboard_writer - INFO - gpu_0_memory_MB                 |   301.758  |       N/A\n",
            "2021-02-16 09:47:57,494 - allennlp.training.tensorboard_writer - INFO - loss                            |    10.316  |       N/A\n",
            "2021-02-16 09:47:57,496 - allennlp.training.tensorboard_writer - INFO - precision-MORFOLOGIA_NEOPLASIA  |     0.851  |       N/A\n",
            "2021-02-16 09:47:57,498 - allennlp.training.tensorboard_writer - INFO - precision-overall               |     0.851  |       N/A\n",
            "2021-02-16 09:47:57,499 - allennlp.training.tensorboard_writer - INFO - recall-MORFOLOGIA_NEOPLASIA     |     0.834  |       N/A\n",
            "2021-02-16 09:47:57,500 - allennlp.training.tensorboard_writer - INFO - recall-overall                  |     0.834  |       N/A\n",
            "2021-02-16 09:47:57,501 - allennlp.training.tensorboard_writer - INFO - worker_0_memory_MB              |  3741.727  |       N/A\n",
            "2021-02-16 09:47:57,665 - allennlp.training.checkpointer - INFO - Best validation performance so far. Copying weights to 'output/best.th'.\n",
            "2021-02-16 09:47:57,752 - allennlp.training.trainer - INFO - Epoch duration: 0:03:21.389377\n",
            "2021-02-16 09:47:57,758 - allennlp.training.trainer - INFO - Estimated training time remaining: 0:06:45\n",
            "2021-02-16 09:47:57,764 - allennlp.training.trainer - INFO - Epoch 2/3\n",
            "2021-02-16 09:47:57,768 - allennlp.training.trainer - INFO - Worker 0 memory usage: 3.7G\n",
            "2021-02-16 09:47:57,772 - allennlp.training.trainer - INFO - GPU 0 memory usage: 302M\n",
            "2021-02-16 09:47:57,775 - allennlp.training.trainer - INFO - Training\n",
            "accuracy: 0.9936, precision-MORFOLOGIA_NEOPLASIA: 0.9033, recall-MORFOLOGIA_NEOPLASIA: 0.8959, f1-measure-MORFOLOGIA_NEOPLASIA: 0.8996, precision-overall: 0.9033, recall-overall: 0.8959, f1-measure-overall: 0.8996, batch_loss: 0.0923, loss: 5.5999 ||: 100%|##########| 1122/1122 [03:22<00:00,  5.54it/s]\n",
            "2021-02-16 09:51:20,366 - allennlp.training.tensorboard_writer - INFO -                                     Training |  Validation\n",
            "2021-02-16 09:51:20,367 - allennlp.training.tensorboard_writer - INFO - accuracy                        |     0.994  |       N/A\n",
            "2021-02-16 09:51:20,371 - allennlp.training.tensorboard_writer - INFO - f1-measure-MORFOLOGIA_NEOPLASIA |     0.900  |       N/A\n",
            "2021-02-16 09:51:20,378 - allennlp.training.tensorboard_writer - INFO - f1-measure-overall              |     0.900  |       N/A\n",
            "2021-02-16 09:51:20,380 - allennlp.training.tensorboard_writer - INFO - gpu_0_memory_MB                 |   301.758  |       N/A\n",
            "2021-02-16 09:51:20,381 - allennlp.training.tensorboard_writer - INFO - loss                            |     5.600  |       N/A\n",
            "2021-02-16 09:51:20,382 - allennlp.training.tensorboard_writer - INFO - precision-MORFOLOGIA_NEOPLASIA  |     0.903  |       N/A\n",
            "2021-02-16 09:51:20,384 - allennlp.training.tensorboard_writer - INFO - precision-overall               |     0.903  |       N/A\n",
            "2021-02-16 09:51:20,386 - allennlp.training.tensorboard_writer - INFO - recall-MORFOLOGIA_NEOPLASIA     |     0.896  |       N/A\n",
            "2021-02-16 09:51:20,388 - allennlp.training.tensorboard_writer - INFO - recall-overall                  |     0.896  |       N/A\n",
            "2021-02-16 09:51:20,389 - allennlp.training.tensorboard_writer - INFO - worker_0_memory_MB              |  3741.727  |       N/A\n",
            "2021-02-16 09:51:20,560 - allennlp.training.checkpointer - INFO - Best validation performance so far. Copying weights to 'output/best.th'.\n",
            "2021-02-16 09:51:20,642 - allennlp.training.trainer - INFO - Epoch duration: 0:03:22.878299\n",
            "2021-02-16 09:51:20,643 - allennlp.training.trainer - INFO - Estimated training time remaining: 0:03:22\n",
            "2021-02-16 09:51:20,647 - allennlp.training.trainer - INFO - Epoch 3/3\n",
            "2021-02-16 09:51:20,648 - allennlp.training.trainer - INFO - Worker 0 memory usage: 3.7G\n",
            "2021-02-16 09:51:20,650 - allennlp.training.trainer - INFO - GPU 0 memory usage: 302M\n",
            "2021-02-16 09:51:20,652 - allennlp.training.trainer - INFO - Training\n",
            "accuracy: 0.9951, precision-MORFOLOGIA_NEOPLASIA: 0.9216, recall-MORFOLOGIA_NEOPLASIA: 0.9212, f1-measure-MORFOLOGIA_NEOPLASIA: 0.9214, precision-overall: 0.9216, recall-overall: 0.9212, f1-measure-overall: 0.9214, batch_loss: 0.0623, loss: 4.3251 ||: 100%|##########| 1122/1122 [03:21<00:00,  5.57it/s]\n",
            "2021-02-16 09:54:42,325 - allennlp.training.tensorboard_writer - INFO -                                     Training |  Validation\n",
            "2021-02-16 09:54:42,328 - allennlp.training.tensorboard_writer - INFO - accuracy                        |     0.995  |       N/A\n",
            "2021-02-16 09:54:42,331 - allennlp.training.tensorboard_writer - INFO - f1-measure-MORFOLOGIA_NEOPLASIA |     0.921  |       N/A\n",
            "2021-02-16 09:54:42,335 - allennlp.training.tensorboard_writer - INFO - f1-measure-overall              |     0.921  |       N/A\n",
            "2021-02-16 09:54:42,341 - allennlp.training.tensorboard_writer - INFO - gpu_0_memory_MB                 |   301.758  |       N/A\n",
            "2021-02-16 09:54:42,342 - allennlp.training.tensorboard_writer - INFO - loss                            |     4.325  |       N/A\n",
            "2021-02-16 09:54:42,344 - allennlp.training.tensorboard_writer - INFO - precision-MORFOLOGIA_NEOPLASIA  |     0.922  |       N/A\n",
            "2021-02-16 09:54:42,346 - allennlp.training.tensorboard_writer - INFO - precision-overall               |     0.922  |       N/A\n",
            "2021-02-16 09:54:42,355 - allennlp.training.tensorboard_writer - INFO - recall-MORFOLOGIA_NEOPLASIA     |     0.921  |       N/A\n",
            "2021-02-16 09:54:42,356 - allennlp.training.tensorboard_writer - INFO - recall-overall                  |     0.921  |       N/A\n",
            "2021-02-16 09:54:42,357 - allennlp.training.tensorboard_writer - INFO - worker_0_memory_MB              |  3741.727  |       N/A\n",
            "2021-02-16 09:54:42,520 - allennlp.training.checkpointer - INFO - Best validation performance so far. Copying weights to 'output/best.th'.\n",
            "2021-02-16 09:54:42,597 - allennlp.training.trainer - INFO - Epoch duration: 0:03:21.950207\n",
            "2021-02-16 09:54:42,599 - allennlp.training.checkpointer - INFO - loading best weights\n",
            "2021-02-16 09:54:42,632 - biome.text._helpers - INFO - The model will be evaluated using the best epoch weights.\n",
            "2021-02-16 09:54:42,634 - allennlp.training.util - INFO - Iterating over dataset\n",
            "accuracy: 0.99, precision-MORFOLOGIA_NEOPLASIA: 0.85, recall-MORFOLOGIA_NEOPLASIA: 0.85, f1-measure-MORFOLOGIA_NEOPLASIA: 0.85, precision-overall: 0.85, recall-overall: 0.85, f1-measure-overall: 0.85, loss: 9.58 ||: : 337it [00:35,  9.54it/s]\n",
            "2021-02-16 09:55:17,957 - allennlp.models.archival - INFO - archiving weights and vocabulary to output/model.tar.gz\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "TrainingResults(model_path='output/model.tar.gz', metrics={'best_epoch': 3, 'peak_worker_0_memory_MB': 3741.7265625, 'peak_gpu_0_memory_MB': 301.75830078125, 'training_duration': '0:13:30.199669', 'training_start_epoch': 0, 'training_epochs': 3, 'epoch': 3, 'training_accuracy': 0.995057364799209, 'training_precision-MORFOLOGIA_NEOPLASIA': 0.9215686274509803, 'training_recall-MORFOLOGIA_NEOPLASIA': 0.9211907495489585, 'training_f1-measure-MORFOLOGIA_NEOPLASIA': 0.9213796497559276, 'training_precision-overall': 0.9215686274509803, 'training_recall-overall': 0.9211907495489585, 'training_f1-measure-overall': 0.9213796497559276, 'training_loss': 4.325106642038002, 'training_worker_0_memory_MB': 3741.7265625, 'training_gpu_0_memory_MB': 301.75830078125, 'test_accuracy': 0.9906576845947861, 'test_precision-MORFOLOGIA_NEOPLASIA': 0.8508845829823083, 'test_recall-MORFOLOGIA_NEOPLASIA': 0.8530405405405406, 'test_f1-measure-MORFOLOGIA_NEOPLASIA': 0.8519611978067827, 'test_precision-overall': 0.8508845829823083, 'test_recall-overall': 0.8530405405405406, 'test_f1-measure-overall': 0.8519611978067827, 'test_loss': 9.579528078481069})"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mVNE3-exZZ_Y"
      },
      "source": [
        "# Appendix: BETO model with an f1 score of 0.861\n",
        "\n",
        "In a quick follow-up work, we experimented with the pretrained \"*BETO: Spanish Bert*\" model, used by the winner (f1: 0.87) and the runner-up (f1: 0.869) of the Cantemist NER competition, and were able to achieve similar results. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "w7HZcoom36TW"
      },
      "source": [
        "pipeline_dict = {\n",
        "    \"name\": \"\",\n",
        "    \"features\": {\n",
        "        \"transformers\": {\n",
        "            \"model_name\": \"dccuchile/bert-base-spanish-wwm-cased\",\n",
        "            #\"mismatched\": True,  # False for wordpiece tokens, True for word tokens\n",
        "            \"trainable\": True,\n",
        "            \"max_length\": 512\n",
        "        },\n",
        "    },\n",
        "    \"head\": {\n",
        "        \"type\": \"TokenClassification\",\n",
        "        \"labels\": [\"MORFOLOGIA_NEOPLASIA\"]\n",
        "    }\n",
        "}"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417,
          "referenced_widgets": [
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        },
        "id": "qhnKMl2darIx",
        "outputId": "d84fe9e9-28fd-41b3-84c5-229055719c06"
      },
      "source": [
        "pl = Pipeline.from_config(pipeline_dict)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[38;5;2m✔ Download and installation successful\u001b[0m\n",
            "You can now load the model via spacy.load('en_core_web_sm')\n",
            "\u001b[38;5;2m✔ Linking successful\u001b[0m\n",
            "/usr/local/lib/python3.6/dist-packages/en_core_web_sm -->\n",
            "/usr/local/lib/python3.6/dist-packages/spacy/data/en\n",
            "You can now load the model via spacy.load('en')\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "9ad130b1906249968ce1b22bd40b43d5",
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              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=456.0, style=ProgressStyle(description_…"
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          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f04c5c58365c4c71aaa76ce16e2dca94",
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              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=242120.0, style=ProgressStyle(descripti…"
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          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "13ad2ebbc764446ba97ed4bdf2528798",
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              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=2.0, style=ProgressStyle(description_wi…"
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          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "b885828987de42be84e7354f745f7426",
              "version_minor": 0,
              "version_major": 2
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              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=112.0, style=ProgressStyle(description_…"
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          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "ff56b9af47394d00aaf7410e7c1d76b5",
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              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=43.0, style=ProgressStyle(description_w…"
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          "metadata": {
            "tags": []
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        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "ceffc699d08d48f593b24f32c4bab027",
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              "HBox(children=(FloatProgress(value=0.0, description='Downloading', max=441944381.0, style=ProgressStyle(descri…"
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          "metadata": {
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        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gyIGvlgIRyjr"
      },
      "source": [
        "# The hyperparameters were found by means of a random search HPO\n",
        "trainer_dict = {\n",
        "    \"optimizer\": {\n",
        "        \"type\": \"adamw\",\n",
        "        \"lr\": 3e-5\n",
        "    },\n",
        "    \"batch_size\": 8,\n",
        "    \"patience\": 2,\n",
        "    \"num_epochs\": 8,\n",
        "    \"validation_metric\" : \"+f1-measure-overall\",\n",
        "    \"learning_rate_scheduler\": {\n",
        "        \"type\": \"linear_with_warmup\",\n",
        "        \"num_epochs\": 8,\n",
        "        \"num_steps_per_epoch\": 4485,\n",
        "        \"warmup_steps\": 100,\n",
        "    }\n",
        "}"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yT82bmTaSD8D"
      },
      "source": [
        "trainer = TrainerConfiguration(**trainer_dict)"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
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        "id": "bvycLqpvbDjS",
        "outputId": "22a59b65-f028-4442-8f4a-5fb9a4bc1d1d"
      },
      "source": [
        "pl.train(\n",
        "    output=\"output_beto\",\n",
        "    training=train_ds,\n",
        "    test=test_ds,\n",
        "    trainer=trainer,\n",
        ")"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "2aab94cc49fc4b92b5abc635465e714c",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='Loading instances into memory', max=35877.0, style=Progre…"
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          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "2021-02-16 10:45:51,602 - biome.text.dataset - INFO - Caching instances to /root/.cache/huggingface/datasets/json/default-4ecdc33b48e84d7c/0.0.0/70d89ed4db1394f028c651589fcab6d6b28dddcabbe39d3b21b4d41f9a708514/eced6fb3a0f87050.instance_list)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "712d68b39ce84eb5b2b27358c883547f",
              "version_minor": 0,
              "version_major": 2
            },
            "text/plain": [
              "HBox(children=(FloatProgress(value=0.0, description='Loading instances into memory', max=10774.0, style=Progre…"
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          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "2021-02-16 10:45:59,999 - biome.text.dataset - INFO - Caching instances to /root/.cache/huggingface/datasets/json/default-bbf39d6db3ce5216/0.0.0/70d89ed4db1394f028c651589fcab6d6b28dddcabbe39d3b21b4d41f9a708514/49415b21c2db4666.instance_list)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "2021-02-16 10:46:01,860 - allennlp.common.params - INFO - random_seed = 13370\n",
            "2021-02-16 10:46:01,861 - allennlp.common.params - INFO - numpy_seed = 1337\n",
            "2021-02-16 10:46:01,862 - allennlp.common.params - INFO - pytorch_seed = 133\n",
            "2021-02-16 10:46:01,869 - allennlp.common.checks - INFO - Pytorch version: 1.7.0+cu101\n",
            "2021-02-16 10:46:01,963 - allennlp.common.params - INFO - type = gradient_descent\n",
            "2021-02-16 10:46:01,965 - allennlp.common.params - INFO - local_rank = 0\n",
            "2021-02-16 10:46:01,966 - allennlp.common.params - INFO - patience = 2\n",
            "2021-02-16 10:46:01,968 - allennlp.common.params - INFO - validation_metric = +f1-measure-overall\n",
            "2021-02-16 10:46:01,972 - allennlp.common.params - INFO - num_epochs = 8\n",
            "2021-02-16 10:46:01,973 - allennlp.common.params - INFO - cuda_device = None\n",
            "2021-02-16 10:46:01,975 - allennlp.common.params - INFO - grad_norm = None\n",
            "2021-02-16 10:46:01,977 - allennlp.common.params - INFO - grad_clipping = None\n",
            "2021-02-16 10:46:01,979 - allennlp.common.params - INFO - distributed = False\n",
            "2021-02-16 10:46:01,981 - allennlp.common.params - INFO - world_size = 1\n",
            "2021-02-16 10:46:01,982 - allennlp.common.params - INFO - num_gradient_accumulation_steps = 1\n",
            "2021-02-16 10:46:01,984 - allennlp.common.params - INFO - use_amp = False\n",
            "2021-02-16 10:46:01,986 - allennlp.common.params - INFO - no_grad = None\n",
            "2021-02-16 10:46:01,992 - allennlp.common.params - INFO - momentum_scheduler = None\n",
            "2021-02-16 10:46:01,995 - allennlp.common.params - INFO - moving_average = None\n",
            "2021-02-16 10:46:01,996 - allennlp.common.params - INFO - batch_callbacks = None\n",
            "2021-02-16 10:46:01,997 - allennlp.common.params - INFO - end_callbacks = None\n",
            "2021-02-16 10:46:02,000 - allennlp.common.params - INFO - trainer_callbacks = None\n",
            "2021-02-16 10:46:02,005 - allennlp.common.params - INFO - optimizer.type = adamw\n",
            "2021-02-16 10:46:02,007 - allennlp.common.params - INFO - optimizer.parameter_groups = None\n",
            "2021-02-16 10:46:02,008 - allennlp.common.params - INFO - optimizer.lr = 3e-05\n",
            "2021-02-16 10:46:02,009 - allennlp.common.params - INFO - optimizer.betas = (0.9, 0.999)\n",
            "2021-02-16 10:46:02,010 - allennlp.common.params - INFO - optimizer.eps = 1e-08\n",
            "2021-02-16 10:46:02,012 - allennlp.common.params - INFO - optimizer.weight_decay = 0.01\n",
            "2021-02-16 10:46:02,013 - allennlp.common.params - INFO - optimizer.amsgrad = False\n",
            "2021-02-16 10:46:02,014 - allennlp.training.optimizers - INFO - Number of trainable parameters: 109854760\n",
            "2021-02-16 10:46:02,020 - allennlp.common.util - INFO - The following parameters are Frozen (without gradient):\n",
            "2021-02-16 10:46:02,026 - allennlp.common.util - INFO - _head._crf._constraint_mask\n",
            "2021-02-16 10:46:02,033 - allennlp.common.util - INFO - The following parameters are Tunable (with gradient):\n",
            "2021-02-16 10:46:02,034 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.embeddings.word_embeddings.weight\n",
            "2021-02-16 10:46:02,035 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.embeddings.position_embeddings.weight\n",
            "2021-02-16 10:46:02,036 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.embeddings.token_type_embeddings.weight\n",
            "2021-02-16 10:46:02,037 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.embeddings.LayerNorm.weight\n",
            "2021-02-16 10:46:02,038 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.embeddings.LayerNorm.bias\n",
            "2021-02-16 10:46:02,040 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.attention.self.query.weight\n",
            "2021-02-16 10:46:02,041 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.attention.self.query.bias\n",
            "2021-02-16 10:46:02,042 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.attention.self.key.weight\n",
            "2021-02-16 10:46:02,043 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.attention.self.key.bias\n",
            "2021-02-16 10:46:02,044 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.attention.self.value.weight\n",
            "2021-02-16 10:46:02,045 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.attention.self.value.bias\n",
            "2021-02-16 10:46:02,046 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.attention.output.dense.weight\n",
            "2021-02-16 10:46:02,047 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.attention.output.dense.bias\n",
            "2021-02-16 10:46:02,048 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.attention.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,049 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.attention.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,050 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.intermediate.dense.weight\n",
            "2021-02-16 10:46:02,051 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.intermediate.dense.bias\n",
            "2021-02-16 10:46:02,054 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.output.dense.weight\n",
            "2021-02-16 10:46:02,054 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.output.dense.bias\n",
            "2021-02-16 10:46:02,055 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,056 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.0.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,057 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.attention.self.query.weight\n",
            "2021-02-16 10:46:02,058 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.attention.self.query.bias\n",
            "2021-02-16 10:46:02,059 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.attention.self.key.weight\n",
            "2021-02-16 10:46:02,060 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.attention.self.key.bias\n",
            "2021-02-16 10:46:02,061 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.attention.self.value.weight\n",
            "2021-02-16 10:46:02,062 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.attention.self.value.bias\n",
            "2021-02-16 10:46:02,063 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.attention.output.dense.weight\n",
            "2021-02-16 10:46:02,063 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.attention.output.dense.bias\n",
            "2021-02-16 10:46:02,064 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.attention.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,065 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.attention.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,066 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.intermediate.dense.weight\n",
            "2021-02-16 10:46:02,067 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.intermediate.dense.bias\n",
            "2021-02-16 10:46:02,068 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.output.dense.weight\n",
            "2021-02-16 10:46:02,069 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.output.dense.bias\n",
            "2021-02-16 10:46:02,070 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,071 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.1.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,072 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.attention.self.query.weight\n",
            "2021-02-16 10:46:02,073 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.attention.self.query.bias\n",
            "2021-02-16 10:46:02,074 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.attention.self.key.weight\n",
            "2021-02-16 10:46:02,075 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.attention.self.key.bias\n",
            "2021-02-16 10:46:02,075 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.attention.self.value.weight\n",
            "2021-02-16 10:46:02,076 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.attention.self.value.bias\n",
            "2021-02-16 10:46:02,078 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.attention.output.dense.weight\n",
            "2021-02-16 10:46:02,078 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.attention.output.dense.bias\n",
            "2021-02-16 10:46:02,079 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.attention.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,080 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.attention.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,081 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.intermediate.dense.weight\n",
            "2021-02-16 10:46:02,082 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.intermediate.dense.bias\n",
            "2021-02-16 10:46:02,083 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.output.dense.weight\n",
            "2021-02-16 10:46:02,084 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.output.dense.bias\n",
            "2021-02-16 10:46:02,085 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,086 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.2.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,087 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.attention.self.query.weight\n",
            "2021-02-16 10:46:02,088 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.attention.self.query.bias\n",
            "2021-02-16 10:46:02,089 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.attention.self.key.weight\n",
            "2021-02-16 10:46:02,089 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.attention.self.key.bias\n",
            "2021-02-16 10:46:02,090 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.attention.self.value.weight\n",
            "2021-02-16 10:46:02,091 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.attention.self.value.bias\n",
            "2021-02-16 10:46:02,092 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.attention.output.dense.weight\n",
            "2021-02-16 10:46:02,093 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.attention.output.dense.bias\n",
            "2021-02-16 10:46:02,093 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.attention.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,094 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.attention.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,095 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.intermediate.dense.weight\n",
            "2021-02-16 10:46:02,096 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.intermediate.dense.bias\n",
            "2021-02-16 10:46:02,096 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.output.dense.weight\n",
            "2021-02-16 10:46:02,097 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.output.dense.bias\n",
            "2021-02-16 10:46:02,098 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,099 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.3.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,100 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.attention.self.query.weight\n",
            "2021-02-16 10:46:02,101 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.attention.self.query.bias\n",
            "2021-02-16 10:46:02,102 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.attention.self.key.weight\n",
            "2021-02-16 10:46:02,103 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.attention.self.key.bias\n",
            "2021-02-16 10:46:02,104 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.attention.self.value.weight\n",
            "2021-02-16 10:46:02,105 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.attention.self.value.bias\n",
            "2021-02-16 10:46:02,106 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.attention.output.dense.weight\n",
            "2021-02-16 10:46:02,106 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.attention.output.dense.bias\n",
            "2021-02-16 10:46:02,107 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.attention.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,108 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.attention.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,109 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.intermediate.dense.weight\n",
            "2021-02-16 10:46:02,110 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.intermediate.dense.bias\n",
            "2021-02-16 10:46:02,111 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.output.dense.weight\n",
            "2021-02-16 10:46:02,112 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.output.dense.bias\n",
            "2021-02-16 10:46:02,113 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,114 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.4.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,115 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.attention.self.query.weight\n",
            "2021-02-16 10:46:02,116 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.attention.self.query.bias\n",
            "2021-02-16 10:46:02,117 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.attention.self.key.weight\n",
            "2021-02-16 10:46:02,118 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.attention.self.key.bias\n",
            "2021-02-16 10:46:02,119 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.attention.self.value.weight\n",
            "2021-02-16 10:46:02,120 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.attention.self.value.bias\n",
            "2021-02-16 10:46:02,120 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.attention.output.dense.weight\n",
            "2021-02-16 10:46:02,121 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.attention.output.dense.bias\n",
            "2021-02-16 10:46:02,122 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.attention.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,123 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.attention.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,124 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.intermediate.dense.weight\n",
            "2021-02-16 10:46:02,125 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.intermediate.dense.bias\n",
            "2021-02-16 10:46:02,126 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.output.dense.weight\n",
            "2021-02-16 10:46:02,127 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.output.dense.bias\n",
            "2021-02-16 10:46:02,128 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,129 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.5.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,130 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.attention.self.query.weight\n",
            "2021-02-16 10:46:02,131 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.attention.self.query.bias\n",
            "2021-02-16 10:46:02,132 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.attention.self.key.weight\n",
            "2021-02-16 10:46:02,133 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.attention.self.key.bias\n",
            "2021-02-16 10:46:02,133 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.attention.self.value.weight\n",
            "2021-02-16 10:46:02,135 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.attention.self.value.bias\n",
            "2021-02-16 10:46:02,135 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.attention.output.dense.weight\n",
            "2021-02-16 10:46:02,136 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.attention.output.dense.bias\n",
            "2021-02-16 10:46:02,137 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.attention.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,138 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.attention.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,139 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.intermediate.dense.weight\n",
            "2021-02-16 10:46:02,140 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.intermediate.dense.bias\n",
            "2021-02-16 10:46:02,141 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.output.dense.weight\n",
            "2021-02-16 10:46:02,142 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.output.dense.bias\n",
            "2021-02-16 10:46:02,143 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,144 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.6.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,145 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.attention.self.query.weight\n",
            "2021-02-16 10:46:02,146 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.attention.self.query.bias\n",
            "2021-02-16 10:46:02,147 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.attention.self.key.weight\n",
            "2021-02-16 10:46:02,147 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.attention.self.key.bias\n",
            "2021-02-16 10:46:02,148 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.attention.self.value.weight\n",
            "2021-02-16 10:46:02,149 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.attention.self.value.bias\n",
            "2021-02-16 10:46:02,150 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.attention.output.dense.weight\n",
            "2021-02-16 10:46:02,151 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.attention.output.dense.bias\n",
            "2021-02-16 10:46:02,152 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.attention.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,153 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.attention.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,154 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.intermediate.dense.weight\n",
            "2021-02-16 10:46:02,155 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.intermediate.dense.bias\n",
            "2021-02-16 10:46:02,156 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.output.dense.weight\n",
            "2021-02-16 10:46:02,157 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.output.dense.bias\n",
            "2021-02-16 10:46:02,158 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,159 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.7.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,160 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.attention.self.query.weight\n",
            "2021-02-16 10:46:02,160 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.attention.self.query.bias\n",
            "2021-02-16 10:46:02,161 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.attention.self.key.weight\n",
            "2021-02-16 10:46:02,162 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.attention.self.key.bias\n",
            "2021-02-16 10:46:02,163 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.attention.self.value.weight\n",
            "2021-02-16 10:46:02,164 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.attention.self.value.bias\n",
            "2021-02-16 10:46:02,165 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.attention.output.dense.weight\n",
            "2021-02-16 10:46:02,166 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.attention.output.dense.bias\n",
            "2021-02-16 10:46:02,167 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.attention.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,168 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.attention.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,169 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.intermediate.dense.weight\n",
            "2021-02-16 10:46:02,170 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.intermediate.dense.bias\n",
            "2021-02-16 10:46:02,171 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.output.dense.weight\n",
            "2021-02-16 10:46:02,172 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.output.dense.bias\n",
            "2021-02-16 10:46:02,173 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,174 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.8.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,175 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.attention.self.query.weight\n",
            "2021-02-16 10:46:02,175 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.attention.self.query.bias\n",
            "2021-02-16 10:46:02,176 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.attention.self.key.weight\n",
            "2021-02-16 10:46:02,177 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.attention.self.key.bias\n",
            "2021-02-16 10:46:02,178 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.attention.self.value.weight\n",
            "2021-02-16 10:46:02,179 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.attention.self.value.bias\n",
            "2021-02-16 10:46:02,180 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.attention.output.dense.weight\n",
            "2021-02-16 10:46:02,181 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.attention.output.dense.bias\n",
            "2021-02-16 10:46:02,182 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.attention.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,183 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.attention.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,184 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.intermediate.dense.weight\n",
            "2021-02-16 10:46:02,185 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.intermediate.dense.bias\n",
            "2021-02-16 10:46:02,186 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.output.dense.weight\n",
            "2021-02-16 10:46:02,187 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.output.dense.bias\n",
            "2021-02-16 10:46:02,188 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,189 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.9.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,190 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.attention.self.query.weight\n",
            "2021-02-16 10:46:02,190 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.attention.self.query.bias\n",
            "2021-02-16 10:46:02,191 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.attention.self.key.weight\n",
            "2021-02-16 10:46:02,199 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.attention.self.key.bias\n",
            "2021-02-16 10:46:02,200 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.attention.self.value.weight\n",
            "2021-02-16 10:46:02,201 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.attention.self.value.bias\n",
            "2021-02-16 10:46:02,202 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.attention.output.dense.weight\n",
            "2021-02-16 10:46:02,203 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.attention.output.dense.bias\n",
            "2021-02-16 10:46:02,203 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.attention.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,204 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.attention.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,209 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.intermediate.dense.weight\n",
            "2021-02-16 10:46:02,210 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.intermediate.dense.bias\n",
            "2021-02-16 10:46:02,211 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.output.dense.weight\n",
            "2021-02-16 10:46:02,212 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.output.dense.bias\n",
            "2021-02-16 10:46:02,213 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,214 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.10.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,214 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.attention.self.query.weight\n",
            "2021-02-16 10:46:02,215 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.attention.self.query.bias\n",
            "2021-02-16 10:46:02,216 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.attention.self.key.weight\n",
            "2021-02-16 10:46:02,217 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.attention.self.key.bias\n",
            "2021-02-16 10:46:02,218 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.attention.self.value.weight\n",
            "2021-02-16 10:46:02,219 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.attention.self.value.bias\n",
            "2021-02-16 10:46:02,220 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.attention.output.dense.weight\n",
            "2021-02-16 10:46:02,220 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.attention.output.dense.bias\n",
            "2021-02-16 10:46:02,221 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.attention.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,222 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.attention.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,223 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.intermediate.dense.weight\n",
            "2021-02-16 10:46:02,224 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.intermediate.dense.bias\n",
            "2021-02-16 10:46:02,227 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.output.dense.weight\n",
            "2021-02-16 10:46:02,244 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.output.dense.bias\n",
            "2021-02-16 10:46:02,249 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.output.LayerNorm.weight\n",
            "2021-02-16 10:46:02,257 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.encoder.layer.11.output.LayerNorm.bias\n",
            "2021-02-16 10:46:02,258 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.pooler.dense.weight\n",
            "2021-02-16 10:46:02,259 - allennlp.common.util - INFO - _head.backbone.embedder.token_embedder_transformers._matched_embedder.transformer_model.pooler.dense.bias\n",
            "2021-02-16 10:46:02,261 - allennlp.common.util - INFO - _head._label_projection_layer._module.weight\n",
            "2021-02-16 10:46:02,262 - allennlp.common.util - INFO - _head._label_projection_layer._module.bias\n",
            "2021-02-16 10:46:02,263 - allennlp.common.util - INFO - _head._crf.transitions\n",
            "2021-02-16 10:46:02,265 - allennlp.common.util - INFO - _head._crf.start_transitions\n",
            "2021-02-16 10:46:02,267 - allennlp.common.util - INFO - _head._crf.end_transitions\n",
            "2021-02-16 10:46:02,271 - allennlp.common.params - INFO - learning_rate_scheduler.type = linear_with_warmup\n",
            "2021-02-16 10:46:02,274 - allennlp.common.from_params - WARNING - Parameter num_epochs for class LinearWithWarmup was found in both **extras and in params. Using the specification found in params, but you probably put a key in a config file that you didn't need, and if it is different from what we get from **extras, you might get unexpected behavior.\n",
            "2021-02-16 10:46:02,277 - allennlp.common.params - INFO - learning_rate_scheduler.num_epochs = 8\n",
            "2021-02-16 10:46:02,281 - allennlp.common.from_params - WARNING - Parameter num_steps_per_epoch for class LinearWithWarmup was found in both **extras and in params. Using the specification found in params, but you probably put a key in a config file that you didn't need, and if it is different from what we get from **extras, you might get unexpected behavior.\n",
            "2021-02-16 10:46:02,286 - allennlp.common.params - INFO - learning_rate_scheduler.num_steps_per_epoch = 4485\n",
            "2021-02-16 10:46:02,289 - allennlp.common.params - INFO - learning_rate_scheduler.warmup_steps = 100\n",
            "2021-02-16 10:46:02,290 - allennlp.common.params - INFO - learning_rate_scheduler.last_epoch = -1\n",
            "2021-02-16 10:46:02,292 - allennlp.common.params - INFO - checkpointer.type = default\n",
            "2021-02-16 10:46:02,293 - allennlp.common.params - INFO - checkpointer.keep_serialized_model_every_num_seconds = None\n",
            "2021-02-16 10:46:02,308 - allennlp.common.params - INFO - checkpointer.num_serialized_models_to_keep = 1\n",
            "2021-02-16 10:46:02,311 - allennlp.common.params - INFO - checkpointer.model_save_interval = None\n",
            "2021-02-16 10:46:02,316 - allennlp.common.params - INFO - tensorboard_writer.summary_interval = 100\n",
            "2021-02-16 10:46:02,319 - allennlp.common.params - INFO - tensorboard_writer.histogram_interval = None\n",
            "2021-02-16 10:46:02,320 - allennlp.common.params - INFO - tensorboard_writer.batch_size_interval = None\n",
            "2021-02-16 10:46:02,323 - allennlp.common.params - INFO - tensorboard_writer.should_log_parameter_statistics = True\n",
            "2021-02-16 10:46:02,325 - allennlp.common.params - INFO - tensorboard_writer.should_log_learning_rate = True\n",
            "2021-02-16 10:46:02,326 - allennlp.common.params - INFO - tensorboard_writer.get_batch_num_total = None\n",
            "2021-02-16 10:46:02,357 - allennlp.training.trainer - INFO - Beginning training.\n",
            "2021-02-16 10:46:02,359 - allennlp.training.trainer - INFO - Epoch 0/7\n",
            "2021-02-16 10:46:02,360 - allennlp.training.trainer - INFO - Worker 0 memory usage: 2.5G\n",
            "2021-02-16 10:46:02,364 - allennlp.training.trainer - INFO - Training\n",
            "accuracy: 0.3825, precision-MORFOLOGIA_NEOPLASIA: 0.0036, recall-MORFOLOGIA_NEOPLASIA: 0.0889, f1-measure-MORFOLOGIA_NEOPLASIA: 0.0069, precision-overall: 0.0036, recall-overall: 0.0889, f1-measure-overall: 0.0069, batch_loss: 71.4499, loss: 285.6324 ||:   0%|          | 13/4485 [01:58<11:16:35,  9.08s/it]\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "error",
          "ename": "KeyboardInterrupt",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-11-16d2a5c02b4f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      3\u001b[0m     \u001b[0mtraining\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtrain_ds\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0mtest\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtest_ds\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m     \u001b[0mtrainer\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtrainer\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      6\u001b[0m )\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/biome/text/pipeline.py\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(self, output, training, trainer, validation, test, vocab_config, loggers, lazy, restore, quiet)\u001b[0m\n\u001b[1;32m    347\u001b[0m                     )\n\u001b[1;32m    348\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 349\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_model\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfile_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmetrics\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpipeline_trainer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    350\u001b[0m             \u001b[0mtrain_results\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTrainingResults\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmodel_path\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmetrics\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    351\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/biome/text/_helpers.py\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    206\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    207\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 208\u001b[0;31m             \u001b[0mmetrics\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_trainer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    209\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mKeyboardInterrupt\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    210\u001b[0m             \u001b[0;31m# if we have completed an epoch, try to create a model archive.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/allennlp/training/trainer.py\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    964\u001b[0m         \"\"\"\n\u001b[1;32m    965\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 966\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_try_train\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    967\u001b[0m         \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    968\u001b[0m             \u001b[0;31m# make sure pending events are flushed to disk and files are closed properly\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/allennlp/training/trainer.py\u001b[0m in \u001b[0;36m_try_train\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    999\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mepoch\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mepoch_counter\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_num_epochs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1000\u001b[0m             \u001b[0mepoch_start_time\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1001\u001b[0;31m             \u001b[0mtrain_metrics\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_train_epoch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mepoch\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1002\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1003\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_master\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_checkpointer\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/allennlp/training/trainer.py\u001b[0m in \u001b[0;36m_train_epoch\u001b[0;34m(self, epoch)\u001b[0m\n\u001b[1;32m    768\u001b[0m                     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_scaler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    769\u001b[0m                 \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 770\u001b[0;31m                     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptimizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    771\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    772\u001b[0m             \u001b[0;31m# Update moving averages\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/autograd/grad_mode.py\u001b[0m in \u001b[0;36mdecorate_context\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     24\u001b[0m         \u001b[0;32mdef\u001b[0m \u001b[0mdecorate_context\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     25\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__class__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 26\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     27\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mcast\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mF\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdecorate_context\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     28\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.6/dist-packages/torch/optim/adamw.py\u001b[0m in \u001b[0;36mstep\u001b[0;34m(self, closure)\u001b[0m\n\u001b[1;32m    114\u001b[0m                 \u001b[0mstep_size\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgroup\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'lr'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m/\u001b[0m \u001b[0mbias_correction1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    115\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 116\u001b[0;31m                 \u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0maddcdiv_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexp_avg\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdenom\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0mstep_size\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    117\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    118\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mloss\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-wT0YoMAch-E"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}