diff --git a/notebooks/Predict.ipynb b/notebooks/Predict.ipynb
index f479b3e92a836387e0e59adc5e671e6e587344be..76e7e0ac071aed40627043e8e26de73460c8d9b4 100644
--- a/notebooks/Predict.ipynb
+++ b/notebooks/Predict.ipynb
@@ -139,7 +139,7 @@
},
{
"cell_type": "code",
- "execution_count": 23,
+ "execution_count": 2,
"metadata": {
"id": "SkErnwgMMbRj"
},
@@ -330,7 +330,7 @@
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
@@ -341,7 +341,7 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
@@ -445,7 +445,7 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 16,
"metadata": {},
"outputs": [
{
@@ -467,7 +467,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 17,
"metadata": {},
"outputs": [
{
@@ -494,22 +494,9 @@
},
{
"cell_type": "code",
- "execution_count": 26,
+ "execution_count": 18,
"metadata": {},
- "outputs": [
- {
- "ename": "TypeError",
- "evalue": "Expected state_dict to be dict-like, got <class 'transformers.models.bert.modeling_bert.BertForSequenceClassification'>.",
- "output_type": "error",
- "traceback": [
- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)",
- "Cell \u001b[0;32mIn [26], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[39m#model = torch.load(model_path, map_location=torch.device('mps'))\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m model\u001b[39m.\u001b[39;49mload_state_dict(torch\u001b[39m.\u001b[39;49mload(model_path, map_location\u001b[39m=\u001b[39;49mtorch\u001b[39m.\u001b[39;49mdevice(\u001b[39m'\u001b[39;49m\u001b[39mmps\u001b[39;49m\u001b[39m'\u001b[39;49m)))\n",
- "File \u001b[0;32m/opt/homebrew/Caskroom/miniforge/base/envs/geode-classification-py39/lib/python3.9/site-packages/torch/nn/modules/module.py:1620\u001b[0m, in \u001b[0;36mModule.load_state_dict\u001b[0;34m(self, state_dict, strict)\u001b[0m\n\u001b[1;32m 1597\u001b[0m \u001b[39mr\u001b[39m\u001b[39m\"\"\"Copies parameters and buffers from :attr:`state_dict` into\u001b[39;00m\n\u001b[1;32m 1598\u001b[0m \u001b[39mthis module and its descendants. If :attr:`strict` is ``True``, then\u001b[39;00m\n\u001b[1;32m 1599\u001b[0m \u001b[39mthe keys of :attr:`state_dict` must exactly match the keys returned\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1617\u001b[0m \u001b[39m ``RuntimeError``.\u001b[39;00m\n\u001b[1;32m 1618\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m 1619\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39misinstance\u001b[39m(state_dict, Mapping):\n\u001b[0;32m-> 1620\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mTypeError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39mExpected state_dict to be dict-like, got \u001b[39m\u001b[39m{}\u001b[39;00m\u001b[39m.\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39mformat(\u001b[39mtype\u001b[39m(state_dict)))\n\u001b[1;32m 1622\u001b[0m missing_keys: List[\u001b[39mstr\u001b[39m] \u001b[39m=\u001b[39m []\n\u001b[1;32m 1623\u001b[0m unexpected_keys: List[\u001b[39mstr\u001b[39m] \u001b[39m=\u001b[39m []\n",
- "\u001b[0;31mTypeError\u001b[0m: Expected state_dict to be dict-like, got <class 'transformers.models.bert.modeling_bert.BertForSequenceClassification'>."
- ]
- }
- ],
+ "outputs": [],
"source": [
"#model = torch.load(model_path, map_location=torch.device('mps'))\n",
"#model.load_state_dict(torch.load(model_path, map_location=torch.device('mps')))\n",
@@ -519,7 +506,7 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 19,
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
@@ -527,65 +514,493 @@
"id": "_fzgS5USJeAF",
"outputId": "be4a5506-76ed-4eef-bb3c-fe2bb77c6e4d"
},
+ "outputs": [],
+ "source": [
+ "pred = predict(model, data_loader, device)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "metadata": {},
"outputs": [
{
- "ename": "AttributeError",
- "evalue": "'BertEncoder' object has no attribute 'gradient_checkpointing'",
- "output_type": "error",
- "traceback": [
- "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
- "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
- "Cell \u001b[0;32mIn [14], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m pred \u001b[39m=\u001b[39m predict(model, data_loader, device)\n",
- "Cell \u001b[0;32mIn [8], line 68\u001b[0m, in \u001b[0;36mpredict\u001b[0;34m(model, dataloader, device)\u001b[0m\n\u001b[1;32m 64\u001b[0m \u001b[39m# Telling the model not to compute or store gradients, saving memory and\u001b[39;00m\n\u001b[1;32m 65\u001b[0m \u001b[39m# speeding up prediction\u001b[39;00m\n\u001b[1;32m 66\u001b[0m \u001b[39mwith\u001b[39;00m torch\u001b[39m.\u001b[39mno_grad():\n\u001b[1;32m 67\u001b[0m \u001b[39m# Forward pass, calculate logit predictions\u001b[39;00m\n\u001b[0;32m---> 68\u001b[0m outputs \u001b[39m=\u001b[39m model(b_input_ids, token_type_ids\u001b[39m=\u001b[39;49m\u001b[39mNone\u001b[39;49;00m,\n\u001b[1;32m 69\u001b[0m attention_mask\u001b[39m=\u001b[39;49mb_input_mask)\n\u001b[1;32m 71\u001b[0m logits \u001b[39m=\u001b[39m outputs[\u001b[39m0\u001b[39m]\n\u001b[1;32m 72\u001b[0m \u001b[39m#print(logits)\u001b[39;00m\n\u001b[1;32m 73\u001b[0m \n\u001b[1;32m 74\u001b[0m \u001b[39m# Move logits and labels to CPU ???\u001b[39;00m\n",
- "File \u001b[0;32m/opt/homebrew/Caskroom/miniforge/base/envs/geode-classification-py39/lib/python3.9/site-packages/torch/nn/modules/module.py:1190\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m 1186\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1187\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1188\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1189\u001b[0m \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1190\u001b[0m \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m 1191\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m 1192\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
- "File \u001b[0;32m/opt/homebrew/Caskroom/miniforge/base/envs/geode-classification-py39/lib/python3.9/site-packages/transformers/models/bert/modeling_bert.py:1552\u001b[0m, in \u001b[0;36mBertForSequenceClassification.forward\u001b[0;34m(self, input_ids, attention_mask, token_type_ids, position_ids, head_mask, inputs_embeds, labels, output_attentions, output_hidden_states, return_dict)\u001b[0m\n\u001b[1;32m 1544\u001b[0m \u001b[39mr\u001b[39m\u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m 1545\u001b[0m \u001b[39mlabels (`torch.LongTensor` of shape `(batch_size,)`, *optional*):\u001b[39;00m\n\u001b[1;32m 1546\u001b[0m \u001b[39m Labels for computing the sequence classification/regression loss. Indices should be in `[0, ...,\u001b[39;00m\n\u001b[1;32m 1547\u001b[0m \u001b[39m config.num_labels - 1]`. If `config.num_labels == 1` a regression loss is computed (Mean-Square loss), If\u001b[39;00m\n\u001b[1;32m 1548\u001b[0m \u001b[39m `config.num_labels > 1` a classification loss is computed (Cross-Entropy).\u001b[39;00m\n\u001b[1;32m 1549\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m 1550\u001b[0m return_dict \u001b[39m=\u001b[39m return_dict \u001b[39mif\u001b[39;00m return_dict \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mconfig\u001b[39m.\u001b[39muse_return_dict\n\u001b[0;32m-> 1552\u001b[0m outputs \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mbert(\n\u001b[1;32m 1553\u001b[0m input_ids,\n\u001b[1;32m 1554\u001b[0m attention_mask\u001b[39m=\u001b[39;49mattention_mask,\n\u001b[1;32m 1555\u001b[0m token_type_ids\u001b[39m=\u001b[39;49mtoken_type_ids,\n\u001b[1;32m 1556\u001b[0m position_ids\u001b[39m=\u001b[39;49mposition_ids,\n\u001b[1;32m 1557\u001b[0m head_mask\u001b[39m=\u001b[39;49mhead_mask,\n\u001b[1;32m 1558\u001b[0m inputs_embeds\u001b[39m=\u001b[39;49minputs_embeds,\n\u001b[1;32m 1559\u001b[0m output_attentions\u001b[39m=\u001b[39;49moutput_attentions,\n\u001b[1;32m 1560\u001b[0m output_hidden_states\u001b[39m=\u001b[39;49moutput_hidden_states,\n\u001b[1;32m 1561\u001b[0m return_dict\u001b[39m=\u001b[39;49mreturn_dict,\n\u001b[1;32m 1562\u001b[0m )\n\u001b[1;32m 1564\u001b[0m pooled_output \u001b[39m=\u001b[39m outputs[\u001b[39m1\u001b[39m]\n\u001b[1;32m 1566\u001b[0m pooled_output \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mdropout(pooled_output)\n",
- "File \u001b[0;32m/opt/homebrew/Caskroom/miniforge/base/envs/geode-classification-py39/lib/python3.9/site-packages/torch/nn/modules/module.py:1190\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m 1186\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1187\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1188\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1189\u001b[0m \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1190\u001b[0m \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m 1191\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m 1192\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
- "File \u001b[0;32m/opt/homebrew/Caskroom/miniforge/base/envs/geode-classification-py39/lib/python3.9/site-packages/transformers/models/bert/modeling_bert.py:1014\u001b[0m, in \u001b[0;36mBertModel.forward\u001b[0;34m(self, input_ids, attention_mask, token_type_ids, position_ids, head_mask, inputs_embeds, encoder_hidden_states, encoder_attention_mask, past_key_values, use_cache, output_attentions, output_hidden_states, return_dict)\u001b[0m\n\u001b[1;32m 1005\u001b[0m head_mask \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mget_head_mask(head_mask, \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mconfig\u001b[39m.\u001b[39mnum_hidden_layers)\n\u001b[1;32m 1007\u001b[0m embedding_output \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39membeddings(\n\u001b[1;32m 1008\u001b[0m input_ids\u001b[39m=\u001b[39minput_ids,\n\u001b[1;32m 1009\u001b[0m position_ids\u001b[39m=\u001b[39mposition_ids,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1012\u001b[0m past_key_values_length\u001b[39m=\u001b[39mpast_key_values_length,\n\u001b[1;32m 1013\u001b[0m )\n\u001b[0;32m-> 1014\u001b[0m encoder_outputs \u001b[39m=\u001b[39m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mencoder(\n\u001b[1;32m 1015\u001b[0m embedding_output,\n\u001b[1;32m 1016\u001b[0m attention_mask\u001b[39m=\u001b[39;49mextended_attention_mask,\n\u001b[1;32m 1017\u001b[0m head_mask\u001b[39m=\u001b[39;49mhead_mask,\n\u001b[1;32m 1018\u001b[0m encoder_hidden_states\u001b[39m=\u001b[39;49mencoder_hidden_states,\n\u001b[1;32m 1019\u001b[0m encoder_attention_mask\u001b[39m=\u001b[39;49mencoder_extended_attention_mask,\n\u001b[1;32m 1020\u001b[0m past_key_values\u001b[39m=\u001b[39;49mpast_key_values,\n\u001b[1;32m 1021\u001b[0m use_cache\u001b[39m=\u001b[39;49muse_cache,\n\u001b[1;32m 1022\u001b[0m output_attentions\u001b[39m=\u001b[39;49moutput_attentions,\n\u001b[1;32m 1023\u001b[0m output_hidden_states\u001b[39m=\u001b[39;49moutput_hidden_states,\n\u001b[1;32m 1024\u001b[0m return_dict\u001b[39m=\u001b[39;49mreturn_dict,\n\u001b[1;32m 1025\u001b[0m )\n\u001b[1;32m 1026\u001b[0m sequence_output \u001b[39m=\u001b[39m encoder_outputs[\u001b[39m0\u001b[39m]\n\u001b[1;32m 1027\u001b[0m pooled_output \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpooler(sequence_output) \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mpooler \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m \u001b[39mNone\u001b[39;00m\n",
- "File \u001b[0;32m/opt/homebrew/Caskroom/miniforge/base/envs/geode-classification-py39/lib/python3.9/site-packages/torch/nn/modules/module.py:1190\u001b[0m, in \u001b[0;36mModule._call_impl\u001b[0;34m(self, *input, **kwargs)\u001b[0m\n\u001b[1;32m 1186\u001b[0m \u001b[39m# If we don't have any hooks, we want to skip the rest of the logic in\u001b[39;00m\n\u001b[1;32m 1187\u001b[0m \u001b[39m# this function, and just call forward.\u001b[39;00m\n\u001b[1;32m 1188\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m (\u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_backward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_hooks \u001b[39mor\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_forward_pre_hooks \u001b[39mor\u001b[39;00m _global_backward_hooks\n\u001b[1;32m 1189\u001b[0m \u001b[39mor\u001b[39;00m _global_forward_hooks \u001b[39mor\u001b[39;00m _global_forward_pre_hooks):\n\u001b[0;32m-> 1190\u001b[0m \u001b[39mreturn\u001b[39;00m forward_call(\u001b[39m*\u001b[39;49m\u001b[39minput\u001b[39;49m, \u001b[39m*\u001b[39;49m\u001b[39m*\u001b[39;49mkwargs)\n\u001b[1;32m 1191\u001b[0m \u001b[39m# Do not call functions when jit is used\u001b[39;00m\n\u001b[1;32m 1192\u001b[0m full_backward_hooks, non_full_backward_hooks \u001b[39m=\u001b[39m [], []\n",
- "File \u001b[0;32m/opt/homebrew/Caskroom/miniforge/base/envs/geode-classification-py39/lib/python3.9/site-packages/transformers/models/bert/modeling_bert.py:580\u001b[0m, in \u001b[0;36mBertEncoder.forward\u001b[0;34m(self, hidden_states, attention_mask, head_mask, encoder_hidden_states, encoder_attention_mask, past_key_values, use_cache, output_attentions, output_hidden_states, return_dict)\u001b[0m\n\u001b[1;32m 577\u001b[0m layer_head_mask \u001b[39m=\u001b[39m head_mask[i] \u001b[39mif\u001b[39;00m head_mask \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m \u001b[39mNone\u001b[39;00m\n\u001b[1;32m 578\u001b[0m past_key_value \u001b[39m=\u001b[39m past_key_values[i] \u001b[39mif\u001b[39;00m past_key_values \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39melse\u001b[39;00m \u001b[39mNone\u001b[39;00m\n\u001b[0;32m--> 580\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mself\u001b[39;49m\u001b[39m.\u001b[39;49mgradient_checkpointing \u001b[39mand\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mtraining:\n\u001b[1;32m 582\u001b[0m \u001b[39mif\u001b[39;00m use_cache:\n\u001b[1;32m 583\u001b[0m logger\u001b[39m.\u001b[39mwarning(\n\u001b[1;32m 584\u001b[0m \u001b[39m\"\u001b[39m\u001b[39m`use_cache=True` is incompatible with gradient checkpointing. Setting `use_cache=False`...\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m 585\u001b[0m )\n",
- "File \u001b[0;32m/opt/homebrew/Caskroom/miniforge/base/envs/geode-classification-py39/lib/python3.9/site-packages/torch/nn/modules/module.py:1265\u001b[0m, in \u001b[0;36mModule.__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 1263\u001b[0m \u001b[39mif\u001b[39;00m name \u001b[39min\u001b[39;00m modules:\n\u001b[1;32m 1264\u001b[0m \u001b[39mreturn\u001b[39;00m modules[name]\n\u001b[0;32m-> 1265\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mAttributeError\u001b[39;00m(\u001b[39m\"\u001b[39m\u001b[39m'\u001b[39m\u001b[39m{}\u001b[39;00m\u001b[39m'\u001b[39m\u001b[39m object has no attribute \u001b[39m\u001b[39m'\u001b[39m\u001b[39m{}\u001b[39;00m\u001b[39m'\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39mformat(\n\u001b[1;32m 1266\u001b[0m \u001b[39mtype\u001b[39m(\u001b[39mself\u001b[39m)\u001b[39m.\u001b[39m\u001b[39m__name__\u001b[39m, name))\n",
- "\u001b[0;31mAttributeError\u001b[0m: 'BertEncoder' object has no attribute 'gradient_checkpointing'"
- ]
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+ "metadata": {},
+ "output_type": "execute_result"
}
],
"source": [
- "pred = predict(model, data_loader, device)"
+ "pred"
]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 22,
"metadata": {},
"outputs": [],
- "source": []
+ "source": [
+ "import pickle \n",
+ "encoder_filename = \"models/label_encoder.pkl\"\n",
+ "with open(path+encoder_filename, 'rb') as file:\n",
+ " encoder = pickle.load(file)"
+ ]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 23,
"metadata": {},
"outputs": [],
- "source": []
+ "source": [
+ "p2 = list(encoder.inverse_transform(pred))"
+ ]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 24,
"metadata": {},
"outputs": [],
- "source": []
+ "source": [
+ "df_LGE['class_bert'] = p2"
+ ]
},
{
"cell_type": "code",
- "execution_count": null,
+ "execution_count": 25,
"metadata": {},
- "outputs": [],
- "source": []
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
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+ "<table border=\"1\" class=\"dataframe\">\n",
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+ " <th></th>\n",
+ " <th>id</th>\n",
+ " <th>tome</th>\n",
+ " <th>rank</th>\n",
+ " <th>domain</th>\n",
+ " <th>remark</th>\n",
+ " <th>content</th>\n",
+ " <th>class_bert</th>\n",
+ " </tr>\n",
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+ " <td>ABRABESES. Village d’Espagne de la prov. de Za...</td>\n",
+ " <td>Géographie</td>\n",
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+ " <td>ACCIUS, L. ou L. ATTIUS (170-94 av. J.-C.), po...</td>\n",
+ " <td>Belles-lettres - Poésie</td>\n",
+ " </tr>\n",
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+ " <td>NaN</td>\n",
+ " <td>ACHENBACH(Henri), administrateur prussien, né ...</td>\n",
+ " <td>Histoire</td>\n",
+ " </tr>\n",
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+ " <th>3</th>\n",
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+ " <td>1513</td>\n",
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+ " <td>NaN</td>\n",
+ " <td>ACIREALE. Yille de Sicile, de la province et d...</td>\n",
+ " <td>Géographie</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
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+ " <td>ACTÉE(Actœa L.). Genre de plantes de la famill...</td>\n",
+ " <td>Histoire naturelle</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " id tome rank domain remark \\\n",
+ "0 abrabeses-0 1 623 geography NaN \n",
+ "1 accius-0 1 1076 biography NaN \n",
+ "2 achenbach-2 1 1357 biography NaN \n",
+ "3 acireale-0 1 1513 geography NaN \n",
+ "4 actée-0 1 1731 botany NaN \n",
+ "\n",
+ " content class_bert \n",
+ "0 ABRABESES. Village d’Espagne de la prov. de Za... Géographie \n",
+ "1 ACCIUS, L. ou L. ATTIUS (170-94 av. J.-C.), po... Belles-lettres - Poésie \n",
+ "2 ACHENBACH(Henri), administrateur prussien, né ... Histoire \n",
+ "3 ACIREALE. Yille de Sicile, de la province et d... Géographie \n",
+ "4 ACTÉE(Actœa L.). Genre de plantes de la famill... Histoire naturelle "
+ ]
+ },
+ "execution_count": 25,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df_LGE.head()"
+ ]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
- "source": []
+ "source": [
+ "df_LGE.to_csv(path + \"reports/classification_LGE.tsv\", sep=\"\\t\")"
+ ]
}
],
"metadata": {