diff --git "a/deepl_ner.ipynb" "b/deepl_ner.ipynb"
--- "a/deepl_ner.ipynb"
+++ "b/deepl_ner.ipynb"
@@ -30,7 +30,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 42,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "os.environ[\"TF_USE_LEGACY_KERAS\"] = \"0\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -53,7 +64,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -64,7 +75,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -75,7 +86,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -85,7 +96,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -129,7 +140,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -140,7 +151,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [
     {
@@ -165,7 +176,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -186,18 +197,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-12-29 19:18:12 INFO: Checking for updates to resources.json in case models have been updated.  Note: this behavior can be turned off with download_method=None or download_method=DownloadMethod.REUSE_RESOURCES\n",
-      "Downloading https://raw.githubusercontent.com/stanfordnlp/stanza-resources/main/resources_1.9.0.json: 392kB [00:00, 172MB/s]                     \n",
-      "2024-12-29 19:18:12 INFO: Downloaded file to /Users/az-r-ow/stanza_resources/resources.json\n",
-      "2024-12-29 19:18:12 WARNING: Language fr package default expects mwt, which has been added\n",
-      "2024-12-29 19:18:12 INFO: Loading these models for language: fr (French):\n",
+      "/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning:\n",
+      "\n",
+      "IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "\n",
+      "2025-01-05 14:29:26 INFO: Checking for updates to resources.json in case models have been updated.  Note: this behavior can be turned off with download_method=None or download_method=DownloadMethod.REUSE_RESOURCES\n",
+      "Downloading https://raw.githubusercontent.com/stanfordnlp/stanza-resources/main/resources_1.9.0.json: 392kB [00:00, 103MB/s]                     \n",
+      "2025-01-05 14:29:26 INFO: Downloaded file to /Users/az-r-ow/stanza_resources/resources.json\n",
+      "2025-01-05 14:29:26 WARNING: Language fr package default expects mwt, which has been added\n",
+      "2025-01-05 14:29:27 INFO: Loading these models for language: fr (French):\n",
       "===============================\n",
       "| Processor | Package         |\n",
       "-------------------------------\n",
@@ -206,22 +221,32 @@
       "| pos       | combined_charlm |\n",
       "===============================\n",
       "\n",
-      "2024-12-29 19:18:12 WARNING: GPU requested, but is not available!\n",
-      "2024-12-29 19:18:12 INFO: Using device: cpu\n",
-      "2024-12-29 19:18:12 INFO: Loading: tokenize\n",
-      "/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/stanza/models/tokenization/trainer.py:82: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
-      "  checkpoint = torch.load(filename, lambda storage, loc: storage)\n",
-      "2024-12-29 19:18:12 INFO: Loading: mwt\n",
-      "/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/stanza/models/mwt/trainer.py:201: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
-      "  checkpoint = torch.load(filename, lambda storage, loc: storage)\n",
-      "2024-12-29 19:18:12 INFO: Loading: pos\n",
-      "/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/stanza/models/pos/trainer.py:139: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
-      "  checkpoint = torch.load(filename, lambda storage, loc: storage)\n",
-      "/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/stanza/models/common/pretrain.py:56: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
-      "  data = torch.load(self.filename, lambda storage, loc: storage)\n",
-      "/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/stanza/models/common/char_model.py:271: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
-      "  state = torch.load(filename, lambda storage, loc: storage)\n",
-      "2024-12-29 19:18:13 INFO: Done loading processors!\n"
+      "2025-01-05 14:29:27 WARNING: GPU requested, but is not available!\n",
+      "2025-01-05 14:29:27 INFO: Using device: cpu\n",
+      "2025-01-05 14:29:27 INFO: Loading: tokenize\n",
+      "/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/stanza/models/tokenization/trainer.py:82: FutureWarning:\n",
+      "\n",
+      "You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
+      "\n",
+      "2025-01-05 14:29:27 INFO: Loading: mwt\n",
+      "/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/stanza/models/mwt/trainer.py:201: FutureWarning:\n",
+      "\n",
+      "You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
+      "\n",
+      "2025-01-05 14:29:27 INFO: Loading: pos\n",
+      "/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/stanza/models/pos/trainer.py:139: FutureWarning:\n",
+      "\n",
+      "You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
+      "\n",
+      "/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/stanza/models/common/pretrain.py:56: FutureWarning:\n",
+      "\n",
+      "You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
+      "\n",
+      "/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/stanza/models/common/char_model.py:271: FutureWarning:\n",
+      "\n",
+      "You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
+      "\n",
+      "2025-01-05 14:29:28 INFO: Done loading processors!\n"
      ]
     }
    ],
@@ -235,7 +260,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -246,7 +271,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -272,7 +297,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -284,7 +309,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -297,7 +322,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -321,7 +346,7 @@
        " 'X']"
       ]
      },
-     "execution_count": 19,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -341,7 +366,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -371,7 +396,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -397,7 +422,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 21,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -408,7 +433,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 27,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -417,7 +442,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 28,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -428,7 +453,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -439,7 +464,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -450,14 +475,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 61,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-12-29 19:19:50.647172: I tensorflow/core/framework/local_rendezvous.cc:405] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+      "2025-01-05 14:33:50.868923: I tensorflow/core/framework/local_rendezvous.cc:405] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
      ]
     }
    ],
@@ -472,14 +497,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-12-29 19:19:51.603887: I tensorflow/core/framework/local_rendezvous.cc:405] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
+      "2025-01-05 14:31:08.581526: I tensorflow/core/framework/local_rendezvous.cc:405] Local rendezvous is aborting with status: OUT_OF_RANGE: End of sequence\n"
      ]
     }
    ],
@@ -524,7 +549,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 154,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -577,7 +602,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 155,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -625,7 +650,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 156,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -668,7 +693,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -697,7 +722,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -708,7 +733,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 30,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -730,7 +755,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -776,7 +801,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 157,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -872,7 +897,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 243,
+   "execution_count": 54,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -971,7 +996,7 @@
     "        entity_acc = entity_accuracy(sampled_labels, predictions).numpy()\n",
     "\n",
     "        positive_labels = np.unique(sampled_labels.numpy().flatten())\n",
-    "        positive_labels = positive_labels[positive_labels >= 0]\n",
+    "        positive_labels = positive_labels[positive_labels > 0]\n",
     "\n",
     "        predictions = tf.math.argmax(predictions, axis=-1)\n",
     "\n",
@@ -1023,17 +1048,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 161,
+   "execution_count": 43,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "WARNING:absl:At this time, the v2.11+ optimizer `tf.keras.optimizers.Adam` runs slowly on M1/M2 Macs, please use the legacy TF-Keras optimizer instead, located at `tf.keras.optimizers.legacy.Adam`.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "word_input = tf.keras.layers.Input(shape=(MAX_LEN,), name=\"word_input\")\n",
     "pos_input = tf.keras.layers.Input(shape=(MAX_LEN,), name=\"pos_input\")\n",
@@ -1077,28 +1094,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 162,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Epoch 1/10\n"
+      "Epoch 1/10\n",
+      "\u001b[1m297/297\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m8s\u001b[0m 22ms/step - entity_accuracy: 0.7112 - loss: 0.1691 - val_entity_accuracy: 0.9696 - val_loss: 0.0141\n",
+      "Epoch 2/10\n",
+      "\u001b[1m297/297\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m6s\u001b[0m 21ms/step - entity_accuracy: 0.9678 - loss: 0.0168 - val_entity_accuracy: 0.9814 - val_loss: 0.0090\n"
      ]
     },
     {
-     "ename": "ValueError",
-     "evalue": "in user code:\n\n    File \"/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/tf_keras/src/engine/training.py\", line 1398, in train_function  *\n        return step_function(self, iterator)\n    File \"/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/tf_keras/src/engine/training.py\", line 1381, in step_function  **\n        outputs = model.distribute_strategy.run(run_step, args=(data,))\n    File \"/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/tf_keras/src/engine/training.py\", line 1370, in run_step  **\n        outputs = model.train_step(data)\n    File \"/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/tf_keras/src/engine/training.py\", line 1147, in train_step\n        y_pred = self(x, training=True)\n    File \"/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/tf_keras/src/utils/traceback_utils.py\", line 70, in error_handler\n        raise e.with_traceback(filtered_tb) from None\n    File \"/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/tf_keras/src/engine/input_spec.py\", line 219, in assert_input_compatibility\n        raise ValueError(\n\n    ValueError: Layer \"model_1\" expects 2 input(s), but it received 1 input tensors. Inputs received: [<tf.Tensor 'IteratorGetNext:0' shape=(None, 2, 100) dtype=int32>]\n",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[162], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mlstm_with_pos\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      2\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpos_train_dataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbatch\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m32\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      3\u001b[0m \u001b[43m    \u001b[49m\u001b[43mvalidation_data\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpos_test_dataset\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbatch\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m32\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      4\u001b[0m \u001b[43m    \u001b[49m\u001b[43mepochs\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m10\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m      5\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\n\u001b[1;32m      6\u001b[0m \u001b[43m        \u001b[49m\u001b[43mtf\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mkeras\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mEarlyStopping\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      7\u001b[0m \u001b[43m            \u001b[49m\u001b[43mmonitor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mval_loss\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmin_delta\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m0.01\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrestore_best_weights\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\n\u001b[1;32m      8\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      9\u001b[0m \u001b[43m    \u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     10\u001b[0m \u001b[43m)\u001b[49m\n",
-      "File \u001b[0;32m~/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/tf_keras/src/utils/traceback_utils.py:70\u001b[0m, in \u001b[0;36mfilter_traceback.<locals>.error_handler\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     67\u001b[0m     filtered_tb \u001b[38;5;241m=\u001b[39m _process_traceback_frames(e\u001b[38;5;241m.\u001b[39m__traceback__)\n\u001b[1;32m     68\u001b[0m     \u001b[38;5;66;03m# To get the full stack trace, call:\u001b[39;00m\n\u001b[1;32m     69\u001b[0m     \u001b[38;5;66;03m# `tf.debugging.disable_traceback_filtering()`\u001b[39;00m\n\u001b[0;32m---> 70\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m e\u001b[38;5;241m.\u001b[39mwith_traceback(filtered_tb) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m     71\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[1;32m     72\u001b[0m     \u001b[38;5;28;01mdel\u001b[39;00m filtered_tb\n",
-      "File \u001b[0;32m/var/folders/3h/5n6s9rcj3sx0gpncsxbq_99m0000gn/T/__autograph_generated_filengd_sbb1.py:15\u001b[0m, in \u001b[0;36mouter_factory.<locals>.inner_factory.<locals>.tf__train_function\u001b[0;34m(iterator)\u001b[0m\n\u001b[1;32m     13\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m     14\u001b[0m     do_return \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[0;32m---> 15\u001b[0m     retval_ \u001b[38;5;241m=\u001b[39m ag__\u001b[38;5;241m.\u001b[39mconverted_call(ag__\u001b[38;5;241m.\u001b[39mld(step_function), (ag__\u001b[38;5;241m.\u001b[39mld(\u001b[38;5;28mself\u001b[39m), ag__\u001b[38;5;241m.\u001b[39mld(iterator)), \u001b[38;5;28;01mNone\u001b[39;00m, fscope)\n\u001b[1;32m     16\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[1;32m     17\u001b[0m     do_return \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n",
-      "\u001b[0;31mValueError\u001b[0m: in user code:\n\n    File \"/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/tf_keras/src/engine/training.py\", line 1398, in train_function  *\n        return step_function(self, iterator)\n    File \"/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/tf_keras/src/engine/training.py\", line 1381, in step_function  **\n        outputs = model.distribute_strategy.run(run_step, args=(data,))\n    File \"/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/tf_keras/src/engine/training.py\", line 1370, in run_step  **\n        outputs = model.train_step(data)\n    File \"/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/tf_keras/src/engine/training.py\", line 1147, in train_step\n        y_pred = self(x, training=True)\n    File \"/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/tf_keras/src/utils/traceback_utils.py\", line 70, in error_handler\n        raise e.with_traceback(filtered_tb) from None\n    File \"/Users/az-r-ow/Developer/TravelOrderResolver/venv/lib/python3.12/site-packages/tf_keras/src/engine/input_spec.py\", line 219, in assert_input_compatibility\n        raise ValueError(\n\n    ValueError: Layer \"model_1\" expects 2 input(s), but it received 1 input tensors. Inputs received: [<tf.Tensor 'IteratorGetNext:0' shape=(None, 2, 100) dtype=int32>]\n"
-     ]
+     "data": {
+      "text/plain": [
+       "<keras.src.callbacks.history.History at 0x2dc3c53d0>"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
     }
    ],
    "source": [
@@ -1116,7 +1133,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 106,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1125,20 +1142,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 107,
+   "execution_count": 46,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[1m24/24\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 8ms/step\n",
+      "\u001b[1m24/24\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 11ms/step\n",
       "(758, 100)\n"
      ]
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1162,7 +1179,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 47,
    "metadata": {},
    "outputs": [
     {
@@ -1175,7 +1192,7 @@
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1203,20 +1220,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 108,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 11ms/step\n",
+      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 9ms/step \n",
       "(96, 100)\n"
      ]
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -1242,14 +1259,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 55,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 30/30 [00:05<00:00,  5.39it/s]\n"
+      "100%|██████████| 30/30 [00:05<00:00,  5.64it/s]\n"
      ]
     }
    ],
@@ -1261,7 +1278,56 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 56,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[0.8164736164736165,\n",
+       " 0.7985812009120852,\n",
+       " 0.784516765285996,\n",
+       " 0.8030188679245283,\n",
+       " 0.8226950354609929,\n",
+       " 0.8065573770491803,\n",
+       " 0.8091872791519434,\n",
+       " 0.8013398608606029,\n",
+       " 0.7972406996797241,\n",
+       " 0.801345059493016,\n",
+       " 0.8103008669046405,\n",
+       " 0.820815175596001,\n",
+       " 0.802,\n",
+       " 0.8129829984544049,\n",
+       " 0.8045859872611465,\n",
+       " 0.8225765628954695,\n",
+       " 0.8179299924452279,\n",
+       " 0.8139656070870245,\n",
+       " 0.8120261437908497,\n",
+       " 0.8071500503524672,\n",
+       " 0.8032786885245902,\n",
+       " 0.8046324269889225,\n",
+       " 0.8132375577219086,\n",
+       " 0.8171772978402813,\n",
+       " 0.8084672277480235,\n",
+       " 0.8151873271310033,\n",
+       " 0.8107396683337721,\n",
+       " 0.8050568900126422,\n",
+       " 0.8066098631551769,\n",
+       " 0.8025316455696202]"
+      ]
+     },
+     "execution_count": 56,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lstm_with_pos_results[\"f1_scores\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 114,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1280,7 +1346,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 134,
+   "execution_count": 58,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1296,7 +1362,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 137,
+   "execution_count": 59,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1309,7 +1375,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 138,
+   "execution_count": 62,
    "metadata": {},
    "outputs": [
     {
@@ -1317,20 +1383,18 @@
      "output_type": "stream",
      "text": [
       "Epoch 1/10\n",
-      "\u001b[1m149/149\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 65ms/step - entity_accuracy: 0.9696 - loss: 0.0147 - val_entity_accuracy: 0.9146 - val_loss: 0.0274\n",
+      "\u001b[1m149/149\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m11s\u001b[0m 67ms/step - entity_accuracy: 0.7096 - loss: 0.1811 - val_entity_accuracy: 0.9831 - val_loss: 0.0105\n",
       "Epoch 2/10\n",
-      "\u001b[1m149/149\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 68ms/step - entity_accuracy: 0.9857 - loss: 0.0062 - val_entity_accuracy: 0.9782 - val_loss: 0.0099\n",
-      "Epoch 3/10\n",
-      "\u001b[1m149/149\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 67ms/step - entity_accuracy: 0.9940 - loss: 0.0023 - val_entity_accuracy: 0.9816 - val_loss: 0.0120\n"
+      "\u001b[1m149/149\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m10s\u001b[0m 66ms/step - entity_accuracy: 0.9802 - loss: 0.0090 - val_entity_accuracy: 0.9864 - val_loss: 0.0084\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<keras.src.callbacks.history.History at 0x30f2a1b20>"
+       "<keras.src.callbacks.history.History at 0x2dc58f200>"
       ]
      },
-     "execution_count": 138,
+     "execution_count": 62,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1351,7 +1415,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 139,
+   "execution_count": 63,
    "metadata": {},
    "outputs": [
     {
@@ -1368,7 +1432,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 140,
+   "execution_count": 64,
    "metadata": {},
    "outputs": [
     {
@@ -1389,16 +1453,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 141,
+   "execution_count": 65,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Eval short sentences accuracy:  0.93448687\n",
-      "Eval unlabeled sentences accuracy:  0.99549145\n",
-      "Eval large sentences accuracy:  0.9792176\n"
+      "Eval short sentences accuracy:  0.9421664\n",
+      "Eval unlabeled sentences accuracy:  0.9981966\n",
+      "Eval large sentences accuracy:  0.97053784\n"
      ]
     }
    ],
@@ -1426,15 +1490,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 142,
+   "execution_count": 66,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Eval short sentences tag accuracy:  0.7413793\n",
-      "Eval large sentences tag accuracy:  0.7351598\n"
+      "Eval short sentences tag accuracy:  0.738223\n",
+      "Eval large sentences tag accuracy:  0.6543779\n"
      ]
     }
    ],
@@ -1451,13 +1515,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 144,
+   "execution_count": 67,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<tf.Tensor: shape=(757, 100), dtype=int64, numpy=\n",
+       "<tf.Tensor: shape=(758, 100), dtype=int64, numpy=\n",
        "array([[0, 0, 0, ..., 0, 0, 0],\n",
        "       [0, 0, 0, ..., 0, 0, 0],\n",
        "       [0, 0, 0, ..., 0, 0, 0],\n",
@@ -1467,7 +1531,7 @@
        "       [0, 0, 0, ..., 0, 0, 0]])>"
       ]
      },
-     "execution_count": 144,
+     "execution_count": 67,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1498,16 +1562,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 146,
+   "execution_count": 68,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "0.7738132174992243"
+       "0.7795969773299748"
       ]
      },
-     "execution_count": 146,
+     "execution_count": 68,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1525,21 +1589,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 147,
+   "execution_count": 69,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "(757, 100)\n",
+      "(758, 100)\n",
       "(100, 100)\n",
-      "(95, 100)\n"
+      "(96, 100)\n"
      ]
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 1000x3000 with 6 Axes>"
       ]
@@ -1583,7 +1647,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 24,
+   "execution_count": 70,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1627,7 +1691,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 148,
+   "execution_count": 71,
    "metadata": {},
    "outputs": [
     {
@@ -1644,7 +1708,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 72,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1656,21 +1720,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 153,
+   "execution_count": 73,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 25ms/step\n",
+      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 24ms/step\n",
       "J'ai: O\n",
       "passé: O\n",
       "de: O\n",
       "belles: O\n",
       "vacances: O\n",
       "à: O\n",
-      "Paris: O\n",
+      "Paris: LOC-ARR\n",
       ".: O\n",
       "C'est: O\n",
       "l'heure: O\n",
@@ -1699,7 +1763,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 307,
+   "execution_count": 74,
    "metadata": {},
    "outputs": [
     {
@@ -1718,36 +1782,36 @@
          "name": "LSTM",
          "type": "box",
          "y": [
-          0.7699706118087096,
-          0.7702230583176566,
-          0.7715792395226201,
-          0.7691474966170501,
-          0.7716707683893902,
-          0.7598393574297189,
-          0.7640142193054417,
-          0.7393939393939394,
-          0.7947761194029851,
-          0.7657266811279827,
-          0.7728375101050929,
-          0.7657430730478589,
-          0.7752992383025027,
-          0.7929708951125755,
-          0.7639531717941737,
-          0.7607133351077988,
-          0.7812326485285952,
-          0.7720348204570185,
-          0.7717303005686433,
-          0.774157923799006,
-          0.7778673113080848,
-          0.7705488621151272,
-          0.7736757624398074,
-          0.76775956284153,
-          0.751145861418172,
-          0.7765900587920898,
-          0.7500676956404008,
-          0.7687002652519894,
-          0.7512967512967513,
-          0.7618543046357615
+          0.7618257261410788,
+          0.7644217107132708,
+          0.7775585001409642,
+          0.774390243902439,
+          0.7608447488584474,
+          0.7607361963190185,
+          0.7933425797503467,
+          0.7749303621169916,
+          0.7679465776293823,
+          0.7556066705002875,
+          0.7724331926863572,
+          0.7743201569946734,
+          0.8006952491309386,
+          0.7796135536264351,
+          0.7630090497737556,
+          0.7779024116657319,
+          0.7739227756015669,
+          0.7729957805907173,
+          0.7790178571428571,
+          0.7672242699177771,
+          0.7670149675232985,
+          0.780650542118432,
+          0.7711670480549199,
+          0.7820829898323716,
+          0.7791563275434243,
+          0.7692307692307693,
+          0.7648757943385326,
+          0.7610810810810811,
+          0.7864849517319704,
+          0.7941501103752759
          ]
         },
         {
@@ -1759,36 +1823,36 @@
          "name": "LSTM with POS",
          "type": "box",
          "y": [
-          0.7799689785065367,
-          0.7794685441744266,
-          0.7705207413945278,
-          0.7703180212014135,
-          0.7760109041344844,
-          0.7829614604462475,
-          0.7701330927137379,
-          0.781941309255079,
-          0.7678328032712404,
-          0.7840651878678135,
-          0.7741364038972542,
-          0.7719221517603324,
-          0.7792732166890982,
-          0.792931581332125,
-          0.785131459655485,
-          0.7834206331131861,
-          0.7802512673572846,
-          0.7633587786259542,
-          0.793194874060981,
-          0.7686583497483038,
-          0.7804655408489274,
-          0.7657555906934719,
-          0.781878453038674,
-          0.7808988764044944,
-          0.7685018050541517,
-          0.7862254025044723,
-          0.7849677562819658,
-          0.771078875793291,
-          0.7803895231699127,
-          0.7849364791288567
+          0.8164736164736165,
+          0.7985812009120852,
+          0.784516765285996,
+          0.8030188679245283,
+          0.8226950354609929,
+          0.8065573770491803,
+          0.8091872791519434,
+          0.8013398608606029,
+          0.7972406996797241,
+          0.801345059493016,
+          0.8103008669046405,
+          0.820815175596001,
+          0.802,
+          0.8129829984544049,
+          0.8045859872611465,
+          0.8225765628954695,
+          0.8179299924452279,
+          0.8139656070870245,
+          0.8120261437908497,
+          0.8071500503524672,
+          0.8032786885245902,
+          0.8046324269889225,
+          0.8132375577219086,
+          0.8171772978402813,
+          0.8084672277480235,
+          0.8151873271310033,
+          0.8107396683337721,
+          0.8050568900126422,
+          0.8066098631551769,
+          0.8025316455696202
          ]
         }
        ],
@@ -2688,7 +2752,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 146,
+   "execution_count": 75,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2706,17 +2770,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 147,
+   "execution_count": 76,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "WARNING:absl:At this time, the v2.11+ optimizer `tf.keras.optimizers.Adam` runs slowly on M1/M2 Macs, please use the legacy TF-Keras optimizer instead, located at `tf.keras.optimizers.legacy.Adam`.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "bilstm.compile(\n",
     "    optimizer=tf.keras.optimizers.Adam(0.01),\n",
@@ -2727,32 +2783,93 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 148,
+   "execution_count": 77,
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Model: \"sequential\"\n",
-      "_________________________________________________________________\n",
-      " Layer (type)                Output Shape              Param #   \n",
-      "=================================================================\n",
-      " embedding (Embedding)       (None, None, 100)         499300    \n",
-      "                                                                 \n",
-      " bidirectional (Bidirection  (None, None, 200)         160800    \n",
-      " al)                                                             \n",
-      "                                                                 \n",
-      " dropout_160 (Dropout)       (None, None, 200)         0         \n",
-      "                                                                 \n",
-      " dense (Dense)               (None, None, 3)           603       \n",
-      "                                                                 \n",
-      "=================================================================\n",
-      "Total params: 660703 (2.52 MB)\n",
-      "Trainable params: 660703 (2.52 MB)\n",
-      "Non-trainable params: 0 (0.00 Byte)\n",
-      "_________________________________________________________________\n"
-     ]
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">Model: \"sequential_1\"</span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1mModel: \"sequential_1\"\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃<span style=\"font-weight: bold\"> Layer (type)                    </span>┃<span style=\"font-weight: bold\"> Output Shape           </span>┃<span style=\"font-weight: bold\">       Param # </span>┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ embedding_1 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Embedding</span>)         │ ?                      │   <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (unbuilt) │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ bidirectional (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Bidirectional</span>)   │ ?                      │   <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (unbuilt) │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dropout_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dropout</span>)             │ ?                      │             <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_3 (<span style=\"color: #0087ff; text-decoration-color: #0087ff\">Dense</span>)                 │ ?                      │   <span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (unbuilt) │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃\u001b[1m \u001b[0m\u001b[1mLayer (type)                   \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape          \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m      Param #\u001b[0m\u001b[1m \u001b[0m┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ embedding_1 (\u001b[38;5;33mEmbedding\u001b[0m)         │ ?                      │   \u001b[38;5;34m0\u001b[0m (unbuilt) │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ bidirectional (\u001b[38;5;33mBidirectional\u001b[0m)   │ ?                      │   \u001b[38;5;34m0\u001b[0m (unbuilt) │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dropout_3 (\u001b[38;5;33mDropout\u001b[0m)             │ ?                      │             \u001b[38;5;34m0\u001b[0m │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_3 (\u001b[38;5;33mDense\u001b[0m)                 │ ?                      │   \u001b[38;5;34m0\u001b[0m (unbuilt) │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Total params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\"> Non-trainable params: </span><span style=\"color: #00af00; text-decoration-color: #00af00\">0</span> (0.00 B)\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -2761,7 +2878,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 149,
+   "execution_count": 78,
    "metadata": {},
    "outputs": [
     {
@@ -2769,18 +2886,18 @@
      "output_type": "stream",
      "text": [
       "Epoch 1/10\n",
-      "149/149 [==============================] - 15s 80ms/step - loss: 0.0866 - masked_accuracy: 0.9744 - val_loss: 0.0119 - val_masked_accuracy: 0.9961\n",
+      "\u001b[1m149/149\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m16s\u001b[0m 94ms/step - loss: 0.1662 - masked_accuracy: 0.9349 - val_loss: 0.0034 - val_masked_accuracy: 0.9992\n",
       "Epoch 2/10\n",
-      "149/149 [==============================] - 11s 73ms/step - loss: 0.0023 - masked_accuracy: 0.9994 - val_loss: 0.0023 - val_masked_accuracy: 0.9995\n"
+      "\u001b[1m149/149\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m19s\u001b[0m 128ms/step - loss: 0.0022 - masked_accuracy: 0.9994 - val_loss: 6.5582e-04 - val_masked_accuracy: 0.9998\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<tf_keras.src.callbacks.History at 0x2e143fbf0>"
+       "<keras.src.callbacks.history.History at 0x2dd4068a0>"
       ]
      },
-     "execution_count": 149,
+     "execution_count": 78,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -2801,16 +2918,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 150,
+   "execution_count": 79,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "24/24 [==============================] - 1s 13ms/step\n",
-      "4/4 [==============================] - 0s 10ms/step\n",
-      "3/3 [==============================] - 0s 13ms/step\n"
+      "\u001b[1m24/24\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 19ms/step\n",
+      "\u001b[1m4/4\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 15ms/step\n",
+      "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 20ms/step\n"
      ]
     }
    ],
@@ -2822,14 +2939,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 151,
+   "execution_count": 80,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 30/30 [00:12<00:00,  2.41it/s]\n"
+      "100%|██████████| 30/30 [00:20<00:00,  1.49it/s]\n"
      ]
     }
    ],
@@ -2839,7 +2956,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 161,
+   "execution_count": 81,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -2851,7 +2968,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 168,
+   "execution_count": 82,
    "metadata": {},
    "outputs": [
     {
@@ -2863,7 +2980,7 @@
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -2883,7 +3000,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 169,
+   "execution_count": 83,
    "metadata": {},
    "outputs": [
     {
@@ -2915,7 +3032,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 170,
+   "execution_count": 84,
    "metadata": {},
    "outputs": [
     {
@@ -2927,7 +3044,7 @@
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 2 Axes>"
       ]
@@ -2947,18 +3064,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 85,
    "metadata": {},
    "outputs": [
     {
-     "ename": "NameError",
-     "evalue": "name 'predict' is not defined",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[47], line 4\u001b[0m\n\u001b[1;32m      1\u001b[0m test_sentence \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mJe pensais partir de Bangkok. Mais finalement, je vais devoir trouver un voyage de Tokyo vers Osaka.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m----> 4\u001b[0m p \u001b[38;5;241m=\u001b[39m \u001b[43mpredict\u001b[49m(test_sentence, bilstm)\n",
-      "\u001b[0;31mNameError\u001b[0m: name 'predict' is not defined"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 25ms/step\n",
+      "Je: O\n",
+      "pensais: O\n",
+      "partir: O\n",
+      "de: O\n",
+      "Bangkok: LOC-DEP\n",
+      ".: O\n",
+      "Mais: O\n",
+      "finalement: O\n",
+      ",: O\n",
+      "je: O\n",
+      "vais: O\n",
+      "devoir: O\n",
+      "trouver: O\n",
+      "un: O\n",
+      "voyage: O\n",
+      "de: O\n",
+      "Tokyo: O\n",
+      "vers: O\n",
+      "Osaka: O\n",
+      ".: O\n"
      ]
     }
    ],
@@ -2978,7 +3111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 91,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3026,7 +3159,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 309,
+   "execution_count": 92,
    "metadata": {},
    "outputs": [
     {
@@ -3034,18 +3167,18 @@
      "output_type": "stream",
      "text": [
       "Epoch 1/10\n",
-      "\u001b[1m297/297\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m27s\u001b[0m 85ms/step - entity_accuracy: 0.7609 - loss: 0.1435 - val_entity_accuracy: 0.9983 - val_loss: 0.0027\n",
+      "\u001b[1m297/297\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m27s\u001b[0m 83ms/step - entity_accuracy: 0.7734 - loss: 0.1357 - val_entity_accuracy: 0.9912 - val_loss: 0.0055\n",
       "Epoch 2/10\n",
-      "\u001b[1m297/297\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m29s\u001b[0m 97ms/step - entity_accuracy: 0.9953 - loss: 0.0036 - val_entity_accuracy: 0.9990 - val_loss: 7.3262e-04\n"
+      "\u001b[1m297/297\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m29s\u001b[0m 97ms/step - entity_accuracy: 0.9930 - loss: 0.0052 - val_entity_accuracy: 0.9991 - val_loss: 0.0011\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "<keras.src.callbacks.history.History at 0x2e928c5f0>"
+       "<keras.src.callbacks.history.History at 0x2d9ee9f70>"
       ]
      },
-     "execution_count": 309,
+     "execution_count": 92,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -3065,14 +3198,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 93,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 30/30 [00:23<00:00,  1.25it/s]\n"
+      "100%|██████████| 30/30 [00:24<00:00,  1.22it/s]\n"
      ]
     }
    ],
@@ -3091,7 +3224,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 311,
+   "execution_count": 94,
    "metadata": {},
    "outputs": [
     {
@@ -3110,36 +3243,36 @@
          "name": "BiLSTM",
          "type": "box",
          "y": [
-          0.8619989852866565,
-          0.8681347837622712,
-          0.853715775749674,
-          0.8695187165775401,
-          0.8717029449423815,
-          0.8714934544483035,
-          0.8753206772703951,
-          0.8563927540036755,
-          0.8748035620743845,
-          0.8718487394957983,
-          0.8780860269788751,
-          0.8719262295081968,
-          0.8841447539703202,
-          0.8628571428571429,
-          0.8853388301984024,
-          0.8711751092825919,
-          0.8743589743589744,
-          0.8676699532952776,
-          0.8754977435625166,
-          0.8647551382897741,
-          0.8802456499488229,
-          0.873336881319851,
-          0.8622816032887975,
-          0.8749016522423289,
-          0.8817584638706417,
-          0.8745762711864407,
-          0.8757606490872211,
-          0.88,
-          0.8573635427394438,
-          0.8709338929695698
+          0.7837041007772715,
+          0.7847896440129449,
+          0.783288409703504,
+          0.7917320774463632,
+          0.777387070597782,
+          0.7896145610278372,
+          0.8009721847150959,
+          0.771006711409396,
+          0.782981000802783,
+          0.7776008492569002,
+          0.7727520435967302,
+          0.7713310580204779,
+          0.7712166987091459,
+          0.7819879187259747,
+          0.7635494155154091,
+          0.7698154180238871,
+          0.7941888619854721,
+          0.7898471615720524,
+          0.7717303005686433,
+          0.7771550573792367,
+          0.7904061052057781,
+          0.7846735024284943,
+          0.778675282714055,
+          0.7859838274932615,
+          0.7787222374554428,
+          0.7543668122270742,
+          0.7617787188988883,
+          0.7648316408337787,
+          0.7718264595607928,
+          0.7906602254428341
          ]
         },
         {
@@ -3151,36 +3284,36 @@
          "name": "BiLSTM with POS",
          "type": "box",
          "y": [
-          0.7713580246913581,
-          0.7854109417936548,
-          0.7817781043350478,
-          0.7860196127734473,
-          0.7770114942528735,
-          0.7710017144256675,
-          0.7921138008485151,
-          0.7577332343479337,
-          0.7644444444444445,
-          0.7878938228727363,
-          0.7664641555285541,
-          0.7690058479532164,
-          0.7911596722125652,
-          0.7520235467255335,
-          0.7766220901436355,
-          0.7802224969097652,
-          0.7729374543684595,
-          0.7692693949284459,
-          0.7812812812812813,
-          0.7722532136793597,
-          0.7800529992772826,
-          0.7904737775525715,
-          0.7511901779002756,
-          0.7694180667153641,
-          0.7572339382050024,
-          0.772218073188947,
-          0.7781853753974077,
-          0.7806253203485393,
-          0.7672894928415434,
-          0.7871545929798357
+          0.7505422993492408,
+          0.7371727748691099,
+          0.7534713125491224,
+          0.7374358974358974,
+          0.7519484009674818,
+          0.7457803168008309,
+          0.7453954496208017,
+          0.7434864356701585,
+          0.7594465141032464,
+          0.7537154989384289,
+          0.7647058823529411,
+          0.7359580052493438,
+          0.7411920529801325,
+          0.7587661481676773,
+          0.7640449438202247,
+          0.7588614393125671,
+          0.7492749802267334,
+          0.7354427014091997,
+          0.7323498419388831,
+          0.7607947019867549,
+          0.7554734898443682,
+          0.7655579399141631,
+          0.7630606860158311,
+          0.7455811462238886,
+          0.7641160949868074,
+          0.7471895424836601,
+          0.7432072456046883,
+          0.7355507088331515,
+          0.7689778021375719,
+          0.747867803837953
          ]
         }
        ],
@@ -4066,17 +4199,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": 95,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Some layers from the model checkpoint at ./models/distilcamembert-base-ner-cross-entropy-11 were not used when initializing TFCamembertForTokenClassification: ['dropout_39']\n",
+      "Transformers is only compatible with Keras 2, but you have explicitly set `TF_USE_LEGACY_KERAS` to `0`. This may result in unexpected behaviour or errors if Keras 3 objects are passed to Transformers models.\n",
+      "Some layers from the model checkpoint at Az-r-ow/CamemBERT-NER-Travel were not used when initializing TFCamembertForTokenClassification: ['dropout_39']\n",
       "- This IS expected if you are initializing TFCamembertForTokenClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
       "- This IS NOT expected if you are initializing TFCamembertForTokenClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
-      "All the layers of TFCamembertForTokenClassification were initialized from the model checkpoint at ./models/distilcamembert-base-ner-cross-entropy-11.\n",
+      "All the layers of TFCamembertForTokenClassification were initialized from the model checkpoint at Az-r-ow/CamemBERT-NER-Travel.\n",
       "If your task is similar to the task the model of the checkpoint was trained on, you can already use TFCamembertForTokenClassification for predictions without further training.\n"
      ]
     }
@@ -4089,13 +4223,13 @@
     "tokenizer = CamembertTokenizerFast.from_pretrained(\"cmarkea/distilcamembert-base\")\n",
     "\n",
     "camembert = TFCamembertForTokenClassification.from_pretrained(\n",
-    "    \"./models/distilcamembert-base-ner-cross-entropy-11\", num_labels=len(unique_labels)\n",
+    "    \"Az-r-ow/CamemBERT-NER-Travel\", num_labels=len(unique_labels)\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 121,
+   "execution_count": 96,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4121,7 +4255,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 99,
+   "execution_count": 97,
    "metadata": {},
    "outputs": [
     {
@@ -4140,7 +4274,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 100,
+   "execution_count": 98,
    "metadata": {},
    "outputs": [
     {
@@ -4156,7 +4290,7 @@
        "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])>"
       ]
      },
-     "execution_count": 100,
+     "execution_count": 98,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4167,14 +4301,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 95,
+   "execution_count": 99,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "1/1 [==============================] - 0s 51ms/step\n"
+      "1/1 [==============================] - 1s 631ms/step\n"
      ]
     },
     {
@@ -4188,7 +4322,7 @@
        "        1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]])>"
       ]
      },
-     "execution_count": 95,
+     "execution_count": 99,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4207,7 +4341,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 59,
+   "execution_count": 100,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4264,7 +4398,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 119,
+   "execution_count": 102,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4275,25 +4409,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "type(tokenized_eval_large_sentences)\n",
-    "\n",
-    "num_sentences = tokenized_eval_short_sentences[\"input_ids\"].shape[0]\n",
-    "\n",
-    "indicies = tf.random.uniform([num_sentences], maxval=num_sentences, dtype=tf.int32)\n",
-    "\n",
-    "sampled_input_ids = tf.gather(tokenized_eval_short_sentences[\"input_ids\"], indicies)\n",
-    "sampled_attention_mask = tf.gather(\n",
-    "    tokenized_eval_short_sentences[\"attention_mask\"], indicies\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 124,
+   "execution_count": 103,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4304,7 +4420,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 171,
+   "execution_count": 104,
    "metadata": {},
    "outputs": [
     {
@@ -4336,7 +4452,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 117,
+   "execution_count": 105,
    "metadata": {},
    "outputs": [
     {
@@ -4355,7 +4471,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 174,
+   "execution_count": 106,
    "metadata": {},
    "outputs": [
     {
@@ -4387,14 +4503,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 123,
+   "execution_count": 107,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "4/4 [==============================] - 4s 924ms/step\n"
+      "4/4 [==============================] - 5s 1s/step\n"
      ]
     }
    ],
@@ -4406,7 +4522,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 172,
+   "execution_count": 108,
    "metadata": {},
    "outputs": [
     {
@@ -4438,7 +4554,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 188,
+   "execution_count": 109,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4450,7 +4566,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 189,
+   "execution_count": 110,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -4465,7 +4581,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 248,
+   "execution_count": 111,
    "metadata": {},
    "outputs": [
     {
@@ -4474,7 +4590,7 @@
        "954"
       ]
      },
-     "execution_count": 248,
+     "execution_count": 111,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -4485,14 +4601,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 244,
+   "execution_count": 112,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|██████████| 1/1 [00:42<00:00, 42.16s/it]\n"
+      "100%|██████████| 30/30 [18:42<00:00, 37.42s/it]\n"
      ]
     }
    ],
@@ -4502,29 +4618,20 @@
     "    sentences=camembert_eval_sentences_tokenized,\n",
     "    labels=camembert_eval_labels_aligned,\n",
     "    from_logits=True,\n",
-    "    has_mask=True\n",
-    "    num_bootstrap_samples=1,\n",
+    "    has_mask=True,\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 245,
+   "execution_count": 256,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[0.2422770593488873]"
-      ]
-     },
-     "execution_count": 245,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
-    "camembert_results[\"f1_scores\"]"
+    "import pickle\n",
+    "\n",
+    "with open(\"./results/camembert_results.pickle\", \"wb\") as f:\n",
+    "    pickle.dump(camembert_results, f)"
    ]
   },
   {
@@ -4914,9 +5021,44 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Overall Results\n"
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 116,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "hmm_results = pd.read_pickle(\"./results/hmm_f1_results\")\n",
+    "lstm_results = pd.read_pickle(\"./results/lstm_results.pickle\")\n",
+    "lstm_with_pos_results = pd.read_pickle(\"./results/lstm_with_pos_results.pickle\")\n",
+    "bilstm_results = pd.read_pickle(\"./results/bilstm_results.pickle\")\n",
+    "camembert_results = pd.read_pickle(\"./results/camembert_results.pickle\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 117,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "hmm_results_df = pd.DataFrame({\"f1_scores\": hmm_results})\n",
+    "lstm_results_df = pd.DataFrame(lstm_results)\n",
+    "lstm_with_pos_results_df = pd.DataFrame(lstm_with_pos_results)\n",
+    "bilstm_results_df = pd.DataFrame(bilstm_results)\n",
+    "camembert_results_df = pd.DataFrame(camembert_results)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 119,
    "metadata": {},
    "outputs": [
     {
@@ -4932,39 +5074,39 @@
          "marker": {
           "color": "blue"
          },
-         "name": "LSTM",
+         "name": "HMM",
          "type": "box",
          "y": [
-          0.9469351172447205,
-          0.9464889764785767,
-          0.9397405385971069,
-          0.9440984725952148,
-          0.9434906840324402,
-          0.9442935585975647,
-          0.9460118412971497,
-          0.9438055753707886,
-          0.9433724880218506,
-          0.9453536868095398,
-          0.9445471167564392,
-          0.9429071545600891,
-          0.9488546848297119,
-          0.9466729164123535,
-          0.9430928826332092,
-          0.9440149068832397,
-          0.9473151564598083,
-          0.9429548382759094,
-          0.9444136023521423,
-          0.9441613554954529,
-          0.9476276636123657,
-          0.9420250058174133,
-          0.9439191818237305,
-          0.9451029300689697,
-          0.9458432197570801,
-          0.943034827709198,
-          0.9515688419342041,
-          0.9432573914527893,
-          0.9428632855415344,
-          0.9460811018943787
+          0.1787280701754386,
+          0.17358490566037735,
+          0.21916357861302277,
+          0.15047021943573669,
+          0.2246104245029554,
+          0.15633423180592992,
+          0.2132390096008085,
+          0.2222222222222222,
+          0.21583459404942007,
+          0.2234214786832164,
+          0.22330097087378642,
+          0.20961145194274028,
+          0.15492200107584722,
+          0.26423200859291085,
+          0.24883720930232558,
+          0.21973333333333334,
+          0.15724286483575659,
+          0.22066738428417654,
+          0.1799163179916318,
+          0.23738532110091742,
+          0.17857142857142858,
+          0.1553398058252427,
+          0.23135964912280702,
+          0.22306034482758622,
+          0.15951539626451286,
+          0.19616685456595265,
+          0.22860298177802318,
+          0.22660098522167488,
+          0.18969298245614036,
+          0.16020671834625322
          ]
         },
         {
@@ -4973,39 +5115,162 @@
          "marker": {
           "color": "red"
          },
+         "name": "LSTM",
+         "type": "box",
+         "y": [
+          0.7618257261410788,
+          0.7644217107132708,
+          0.7775585001409642,
+          0.774390243902439,
+          0.7608447488584474,
+          0.7607361963190185,
+          0.7933425797503467,
+          0.7749303621169916,
+          0.7679465776293823,
+          0.7556066705002875,
+          0.7724331926863572,
+          0.7743201569946734,
+          0.8006952491309386,
+          0.7796135536264351,
+          0.7630090497737556,
+          0.7779024116657319,
+          0.7739227756015669,
+          0.7729957805907173,
+          0.7790178571428571,
+          0.7672242699177771,
+          0.7670149675232985,
+          0.780650542118432,
+          0.7711670480549199,
+          0.7820829898323716,
+          0.7791563275434243,
+          0.7692307692307693,
+          0.7648757943385326,
+          0.7610810810810811,
+          0.7864849517319704,
+          0.7941501103752759
+         ]
+        },
+        {
+         "boxmean": true,
+         "boxpoints": "all",
+         "marker": {
+          "color": "green"
+         },
+         "name": "LSTM with POS",
+         "type": "box",
+         "y": [
+          0.8164736164736165,
+          0.7985812009120852,
+          0.784516765285996,
+          0.8030188679245283,
+          0.8226950354609929,
+          0.8065573770491803,
+          0.8091872791519434,
+          0.8013398608606029,
+          0.7972406996797241,
+          0.801345059493016,
+          0.8103008669046405,
+          0.820815175596001,
+          0.802,
+          0.8129829984544049,
+          0.8045859872611465,
+          0.8225765628954695,
+          0.8179299924452279,
+          0.8139656070870245,
+          0.8120261437908497,
+          0.8071500503524672,
+          0.8032786885245902,
+          0.8046324269889225,
+          0.8132375577219086,
+          0.8171772978402813,
+          0.8084672277480235,
+          0.8151873271310033,
+          0.8107396683337721,
+          0.8050568900126422,
+          0.8066098631551769,
+          0.8025316455696202
+         ]
+        },
+        {
+         "boxmean": true,
+         "boxpoints": "all",
+         "marker": {
+          "color": "orange"
+         },
          "name": "BiLSTM",
          "type": "box",
          "y": [
-          0.9659291505813599,
-          0.9639419913291931,
-          0.96223384141922,
-          0.9609531164169312,
-          0.9620401859283447,
-          0.9631532430648804,
-          0.964192807674408,
-          0.9613586068153381,
-          0.9650702476501465,
-          0.9583070278167725,
-          0.9621696472167969,
-          0.9652013182640076,
-          0.9626458883285522,
-          0.9639601111412048,
-          0.9645354747772217,
-          0.9598312973976135,
-          0.9629576206207275,
-          0.9647513031959534,
-          0.9635975956916809,
-          0.9635218381881714,
-          0.9613850712776184,
-          0.9632705450057983,
-          0.9639430046081543,
-          0.9621418118476868,
-          0.9620762467384338,
-          0.9619245529174805,
-          0.963487982749939,
-          0.9597393870353699,
-          0.9669444561004639,
-          0.9643984436988831
+          0.8619989852866565,
+          0.8681347837622712,
+          0.853715775749674,
+          0.8695187165775401,
+          0.8717029449423815,
+          0.8714934544483035,
+          0.8753206772703951,
+          0.8563927540036755,
+          0.8748035620743845,
+          0.8718487394957983,
+          0.8780860269788751,
+          0.8719262295081968,
+          0.8841447539703202,
+          0.8628571428571429,
+          0.8853388301984024,
+          0.8711751092825919,
+          0.8743589743589744,
+          0.8676699532952776,
+          0.8754977435625166,
+          0.8647551382897741,
+          0.8802456499488229,
+          0.873336881319851,
+          0.8622816032887975,
+          0.8749016522423289,
+          0.8817584638706417,
+          0.8745762711864407,
+          0.8757606490872211,
+          0.88,
+          0.8573635427394438,
+          0.8709338929695698
+         ]
+        },
+        {
+         "boxmean": true,
+         "boxpoints": "all",
+         "marker": {
+          "color": "purple"
+         },
+         "name": "CamemBERT",
+         "type": "box",
+         "y": [
+          0.9662855179859645,
+          0.9660926509822945,
+          0.963169164882227,
+          0.9690846537771963,
+          0.9700561145510835,
+          0.9691146190803019,
+          0.9700717889018238,
+          0.9696671262556628,
+          0.9682887622387841,
+          0.9667264878498326,
+          0.968851762707065,
+          0.9701566282919116,
+          0.9683338982230184,
+          0.9628297362110312,
+          0.969846833437365,
+          0.9671995723796103,
+          0.9672492219296146,
+          0.9675979262672811,
+          0.9689582936583508,
+          0.9660683320054365,
+          0.9632474477394264,
+          0.970085259474644,
+          0.9646859903381643,
+          0.9734946842388907,
+          0.9673554520760574,
+          0.9648621625482074,
+          0.974221214511041,
+          0.9705854844743733,
+          0.9684483856743913,
+          0.9642486557871899
          ]
         }
        ],
@@ -5826,8 +6091,10 @@
           }
          }
         },
-        "title": {
-         "text": "Accuracy distribution for LSTM and BiLSTM models"
+        "yaxis": {
+         "title": {
+          "text": "F1-scores"
+         }
         }
        }
       }
@@ -5837,18 +6104,14 @@
     }
    ],
    "source": [
-    "import plotly.express as px\n",
     "import plotly.graph_objects as go\n",
     "\n",
-    "df_lstm_results = pd.DataFrame(lstm_results)\n",
-    "df_bilstm_results = pd.DataFrame(bilstm_results)\n",
-    "\n",
     "fig = go.Figure()\n",
     "\n",
     "fig.add_trace(\n",
     "    go.Box(\n",
-    "        y=df_lstm_results[\"accuracies\"],\n",
-    "        name=\"LSTM\",\n",
+    "        y=hmm_results_df[\"f1_scores\"],\n",
+    "        name=\"HMM\",\n",
     "        boxmean=True,\n",
     "        boxpoints=\"all\",\n",
     "        marker=dict(color=\"blue\"),\n",
@@ -5857,22 +6120,52 @@
     "\n",
     "fig.add_trace(\n",
     "    go.Box(\n",
-    "        y=df_bilstm_results[\"accuracies\"],\n",
-    "        name=\"BiLSTM\",\n",
+    "        y=lstm_results_df[\"f1_scores\"],\n",
+    "        name=\"LSTM\",\n",
     "        boxmean=True,\n",
     "        boxpoints=\"all\",\n",
     "        marker=dict(color=\"red\"),\n",
     "    )\n",
     ")\n",
     "\n",
-    "fig.update_layout(title=\"Accuracy distribution for LSTM and BiLSTM models\")\n",
+    "fig.add_trace(\n",
+    "    go.Box(\n",
+    "        y=lstm_with_pos_results_df[\"f1_scores\"],\n",
+    "        name=\"LSTM with POS\",\n",
+    "        boxmean=True,\n",
+    "        boxpoints=\"all\",\n",
+    "        marker=dict(color=\"green\"),\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "fig.add_trace(\n",
+    "    go.Box(\n",
+    "        y=bilstm_results_df[\"f1_scores\"],\n",
+    "        name=\"BiLSTM\",\n",
+    "        boxmean=True,\n",
+    "        boxpoints=\"all\",\n",
+    "        marker=dict(color=\"orange\"),\n",
+    "    )\n",
+    ")\n",
     "\n",
+    "fig.add_trace(\n",
+    "    go.Box(\n",
+    "        y=camembert_results_df[\"f1_scores\"],\n",
+    "        name=\"CamemBERT\",\n",
+    "        boxmean=True,\n",
+    "        boxpoints=\"all\",\n",
+    "        marker=dict(color=\"purple\"),\n",
+    "    )\n",
+    ")\n",
+    "\n",
+    "\n",
+    "fig.update_layout(yaxis_title=\"F1-scores\")\n",
     "fig.show()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -5891,36 +6184,36 @@
          "name": "LSTM",
          "type": "box",
          "y": [
-          0.7231516242027283,
-          0.7317708134651184,
-          0.6930999159812927,
-          0.7374802231788635,
-          0.7027162909507751,
-          0.7167630195617676,
-          0.7222792506217957,
-          0.7263549566268921,
-          0.7193074226379395,
-          0.7052238583564758,
-          0.7057250142097473,
-          0.7114093899726868,
-          0.731312096118927,
-          0.7259989380836487,
-          0.7143614292144775,
-          0.7174025774002075,
-          0.7239392399787903,
-          0.7144340872764587,
-          0.7095744609832764,
-          0.7091675400733948,
-          0.7368143200874329,
-          0.7007337808609009,
-          0.7213114500045776,
-          0.7170808911323547,
-          0.7233351469039917,
-          0.7041800618171692,
-          0.7466948628425598,
-          0.7100977301597595,
-          0.7129676938056946,
-          0.723514199256897
+          0.7389743328094482,
+          0.7424870729446411,
+          0.7421249151229858,
+          0.7397189140319824,
+          0.7368146181106567,
+          0.7379094958305359,
+          0.7438764572143555,
+          0.7052023410797119,
+          0.7781836986541748,
+          0.7354166507720947,
+          0.7414684295654297,
+          0.7362755537033081,
+          0.7496054768562317,
+          0.7684938907623291,
+          0.729968786239624,
+          0.7328205108642578,
+          0.7568585276603699,
+          0.7441006898880005,
+          0.7421875,
+          0.7382833361625671,
+          0.752598762512207,
+          0.7518286108970642,
+          0.7472867965698242,
+          0.7437797784805298,
+          0.7225103974342346,
+          0.7497420310974121,
+          0.7191069722175598,
+          0.7411764860153198,
+          0.7272727489471436,
+          0.7470129728317261
          ]
         },
         {
@@ -5932,36 +6225,77 @@
          "name": "BiLSTM",
          "type": "box",
          "y": [
-          0.8823215961456299,
-          0.8796915411949158,
-          0.8764581084251404,
-          0.8780992031097412,
-          0.8883007168769836,
-          0.8983315825462341,
-          0.8793014883995056,
-          0.869060218334198,
-          0.8871740102767944,
-          0.8628571629524231,
-          0.8813830018043518,
-          0.8891848921775818,
-          0.8874801993370056,
-          0.8908803462982178,
-          0.8858842849731445,
-          0.8752642869949341,
-          0.8787076473236084,
-          0.8981723189353943,
-          0.8866525292396545,
-          0.8860501050949097,
-          0.8811518549919128,
-          0.8869844675064087,
-          0.8945416212081909,
-          0.8833940625190735,
-          0.8759852647781372,
-          0.8911352753639221,
-          0.8823529481887817,
-          0.8695651888847351,
-          0.8959227204322815,
-          0.8817092180252075
+          0.8762248754501343,
+          0.8772118091583252,
+          0.8661375641822815,
+          0.883695662021637,
+          0.8873826861381531,
+          0.8759398460388184,
+          0.8899322152137756,
+          0.8661710023880005,
+          0.8887706398963928,
+          0.890080451965332,
+          0.8878023624420166,
+          0.8869202733039856,
+          0.8927444815635681,
+          0.8793011903762817,
+          0.8975966572761536,
+          0.8786306977272034,
+          0.8880208134651184,
+          0.8827877640724182,
+          0.8932827711105347,
+          0.8824443221092224,
+          0.8986415863037109,
+          0.8784796595573425,
+          0.8780742883682251,
+          0.883474588394165,
+          0.8957905769348145,
+          0.8901273608207703,
+          0.895282506942749,
+          0.8931377530097961,
+          0.869905948638916,
+          0.8778424263000488
+         ]
+        },
+        {
+         "boxmean": true,
+         "boxpoints": "all",
+         "marker": {
+          "color": "green"
+         },
+         "name": "CamemBERT",
+         "type": "box",
+         "y": [
+          0.9495962262153625,
+          0.9493274092674255,
+          0.9514999389648438,
+          0.9535566568374634,
+          0.9554597735404968,
+          0.9603195190429688,
+          0.955078661441803,
+          0.9598649144172668,
+          0.9541693925857544,
+          0.9559488892555237,
+          0.958782970905304,
+          0.9597527384757996,
+          0.9568421244621277,
+          0.949177086353302,
+          0.9561835527420044,
+          0.9508851170539856,
+          0.9558723568916321,
+          0.9551921486854553,
+          0.9567764401435852,
+          0.9546648859977722,
+          0.9534945487976074,
+          0.9541284441947937,
+          0.9559615850448608,
+          0.9591890573501587,
+          0.9482483863830566,
+          0.9509974718093872,
+          0.9585822820663452,
+          0.9563137292861938,
+          0.952602207660675,
+          0.9516522884368896
          ]
         }
        ],
@@ -6797,7 +7131,7 @@
     "\n",
     "fig.add_trace(\n",
     "    go.Box(\n",
-    "        y=df_lstm_results[\"entity_accuracies\"],\n",
+    "        y=lstm_results_df[\"entity_accuracies\"],\n",
     "        name=\"LSTM\",\n",
     "        boxmean=True,\n",
     "        boxpoints=\"all\",\n",
@@ -6807,7 +7141,7 @@
     "\n",
     "fig.add_trace(\n",
     "    go.Box(\n",
-    "        y=df_bilstm_results[\"entity_accuracies\"],\n",
+    "        y=bilstm_results_df[\"entity_accuracies\"],\n",
     "        name=\"BiLSTM\",\n",
     "        boxmean=True,\n",
     "        boxpoints=\"all\",\n",
@@ -6815,6 +7149,16 @@
     "    )\n",
     ")\n",
     "\n",
+    "fig.add_trace(\n",
+    "    go.Box(\n",
+    "        y=camembert_results_df[\"entity_accuracies\"],\n",
+    "        name=\"CamemBERT\",\n",
+    "        boxmean=True,\n",
+    "        boxpoints=\"all\",\n",
+    "        marker=dict(color=\"green\"),\n",
+    "    )\n",
+    ")\n",
+    "\n",
     "fig.update_layout(title=\"Entity accuracy distribution for LSTM and BiLSTM models\")\n",
     "\n",
     "fig.show()"