Tasknet_multitask_transformer_training.ipynb

{
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      "metadata": {
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      "source": [
        "<a href=\"https://colab.research.google.com/github/sileod/tasknet/blob/main/Tasknet_multitask_transformer_training.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "nBqMVdixWaqC"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "os.system('pip install tasknet')\n",
        "import tasknet as tn\n",
        "from datasets import load_dataset"
      ]
    },
    {
      "cell_type": "code",
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      "outputs": [
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          "text": [
            "***** Running training *****\n",
            "  Num examples = 22680\n",
            "  Num Epochs = 1\n",
            "  Instantaneous batch size per device = 8\n",
            "  Total train batch size (w. parallel, distributed & accumulation) = 8\n",
            "  Gradient Accumulation steps = 1\n",
            "  Total optimization steps = 200\n",
            "  Number of trainable parameters = 125869107\n",
            "You're using a RobertaTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.\n"
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              "      [200/200 02:51, Epoch 0/1]\n",
              "    </div>\n",
              "    <table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              " <tr style=\"text-align: left;\">\n",
              "      <th>Epoch</th>\n",
              "      <th>Training Loss</th>\n",
              "      <th>Validation Loss</th>\n",
              "      <th>Accuracy</th>\n",
              "      <th>F1</th>\n",
              "      <th>Name</th>\n",
              "      <th>Size</th>\n",
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              "      <td>nan</td>\n",
              "      <td>glue/stsb</td>\n",
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              "      <td>3</td>\n",
              "      <td>nan</td>\n",
              "      <td>nan</td>\n",
              "      <td>0.481550</td>\n",
              "      <td>0.466840</td>\n",
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              "  </tbody>\n",
              "</table><p>"
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          "text": [
            "***** Running Evaluation *****\n",
            "  Num examples = 277\n",
            "  Batch size = 8\n"
          ]
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            "Trainer is attempting to log a value of \"\" of type <class 'str'> for key \"eval/name\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n",
            "***** Running Evaluation *****\n",
            "  Num examples = 3250\n",
            "  Batch size = 8\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 22 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 8 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 4 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 16 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 21 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 5 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 6 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 11 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 12 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 38 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 28 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 30 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 35 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 37 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 7 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 24 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 15 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 29 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 23 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 27 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 33 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 34 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 40 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 10 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 46 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 42 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 0 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 41 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 20 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 39 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 43 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 44 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 14 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 31 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 32 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 13 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 18 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 3 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 17 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 45 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 1 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 36 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 26 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 25 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/sequence_labeling.py:171: UserWarning: 19 seems not to be NE tag.\n",
            "  warnings.warn('{} seems not to be NE tag.'.format(chunk))\n",
            "/usr/local/lib/python3.8/dist-packages/seqeval/metrics/v1.py:57: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
            "  _warn_prf(average, modifier, msg_start, len(result))\n",
            "Trainer is attempting to log a value of \"conll_pos\" of type <class 'str'> for key \"eval/name\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n",
            "***** Running Evaluation *****\n",
            "  Num examples = 50\n",
            "  Batch size = 8\n",
            "Trainer is attempting to log a value of \"movie_recommendation\" of type <class 'str'> for key \"eval/name\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n",
            "***** Running Evaluation *****\n",
            "  Num examples = 1500\n",
            "  Batch size = 8\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading builder script:   0%|          | 0.00/5.75k [00:00<?, ?B/s]"
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          "text": [
            "Trainer is attempting to log a value of \"glue/stsb\" of type <class 'str'> for key \"eval/name\" as a scalar. This invocation of Tensorboard's writer.add_scalar() is incorrect so we dropped this attribute.\n",
            "\n",
            "\n",
            "Training completed. Do not forget to share your model on huggingface.co/models =)\n",
            "\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "TrainOutput(global_step=200, training_loss=1.7977635192871093, metrics={'train_runtime': 171.4513, 'train_samples_per_second': 9.332, 'train_steps_per_second': 1.167, 'total_flos': 226301389258752.0, 'train_loss': 1.7977635192871093, 'epoch': 0.07})"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ],
      "source": [
        "import tasknet as tn\n",
        "\n",
        "\n",
        "class args:\n",
        "    mtl_architecture = \"cls_task_embedding\"\n",
        "    model_name = \"roberta-base\"\n",
        "    \n",
        "    # remaining arguments are from https://huggingface.co/docs/transformers/v4.24.0/en/main_classes/trainer#transformers.TrainingArguments\n",
        "    learning_rate = 3e-5\n",
        "    max_steps = 200\n",
        "\n",
        "\n",
        "rte = tn.Classification(\n",
        "    dataset=load_dataset(\"glue\", \"rte\"), s1=\"sentence1\", s2=\"sentence2\", y=\"label\"\n",
        ")\n",
        "\n",
        "conll_pos = tn.TokenClassification(\n",
        "    dataset=\"conll2003\", # A dataset string/tuple can also be passed and loaded internally with datasets.load_dataset\n",
        "    name=\"conll_pos\", tokens=\"tokens\", y=\"pos_tags\"\n",
        ")\n",
        "\n",
        "reco = tn.MultipleChoice(\n",
        "    tn.utils.train_validation_test_split(\n",
        "        tn.load_dataset(\"sileod/movie_recommendation\")[\"test\"]\n",
        "    ),\n",
        "    s1=\"question\",\n",
        "    y=\"label\",\n",
        "    choices=[\"answer_0\", \"answer_1\", \"answer_2\", \"answer_3\"],\n",
        ")\n",
        "\n",
        "stsb = tn.Classification(\n",
        "    dataset=(\"glue\", \"stsb\"), s1=\"sentence1\", s2=\"sentence2\", y=\"label\"\n",
        ")\n",
        "\n",
        "tasks = [rte, conll_pos, reco, stsb]\n",
        "models = tn.Model(tasks, args) # list of models; by default, shared encoder, task-specific CLS token task-specific head \n",
        "trainer = tn.Trainer(models, tasks, args) # tasks are uniformly sampled by default\n",
        "trainer.train()"
      ]
    },
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