fix correct version

README.md

@@ -1,3 +1,3 @@
 ## challenging-america-word-gap-prediction
 ### using simple trigram nn
-calculated perplexity: 653.89
+calculated perplexity: 349.16

run.py

@@ -17,12 +17,12 @@ import torch
 
 from tqdm.notebook import tqdm
 
-embed_size = 30
-vocab_size = 10_000
-num_epochs = 2
+embed_size = 300
+vocab_size = 30_000
+num_epochs = 1
 device = 'cuda'
 batch_size = 8192
-train_file_path = 'train/nano.txt'
+train_file_path = 'train/train.txt'
 
 with open(train_file_path, 'r', encoding='utf-8') as file:
     total = len(file.readlines())
@@ -177,8 +177,13 @@ def predictor(prefix):
 
 
 def generate_result(input_path, output_path='out.tsv'):
+    lines = []
     with open(input_path, encoding='utf-8') as f:
-        lines = f.readlines()
+        for line in f:
+            columns = line.split('\t')
+            prefix = columns[6]
+            suffix = columns[7]
+            lines.append(prefix)
 
     with open(output_path, 'w', encoding='utf-8') as output_file:
         for line in lines:

trigram.ipynb

@@ -35,12 +35,12 @@
     "\n",
     "from tqdm.notebook import tqdm\n",
     "\n",
-    "embed_size = 30\n",
-    "vocab_size = 10_000\n",
-    "num_epochs = 2\n",
+    "embed_size = 300\n",
+    "vocab_size = 30_000\n",
+    "num_epochs = 1\n",
     "device = 'cuda'\n",
     "batch_size = 8192\n",
-    "train_file_path = 'train/nano.txt'\n",
+    "train_file_path = 'train/train.txt'\n",
     "\n",
     "with open(train_file_path, 'r', encoding='utf-8') as file:\n",
     "    total = len(file.readlines())"
@@ -147,7 +147,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "5e4b6ce6edf94b90a70d415d75be7eb6",
+       "model_id": "c3d8f9d5b178490899934860a55c2508",
        "version_major": 2,
        "version_minor": 0
       },
@@ -162,37 +162,19 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "0 tensor(9.2450, device='cuda:0', grad_fn=<NllLossBackward0>)\n"
-     ]
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "044c2ea05e344306881002e34d89bd54",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Train loop: 0it [00:00, ?it/s]"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "0 tensor(6.2669, device='cuda:0', grad_fn=<NllLossBackward0>)\n"
+      "0 tensor(10.3631, device='cuda:0', grad_fn=<NllLossBackward0>)\n",
+      "5000 tensor(5.7081, device='cuda:0', grad_fn=<NllLossBackward0>)\n",
+      "10000 tensor(5.5925, device='cuda:0', grad_fn=<NllLossBackward0>)\n",
+      "15000 tensor(5.5097, device='cuda:0', grad_fn=<NllLossBackward0>)\n"
      ]
     },
     {
      "data": {
       "text/plain": [
        "SimpleTrigramNeuralLanguageModel(\n",
-       "  (embedding): Embedding(10000, 30)\n",
-       "  (linear1): Linear(in_features=60, out_features=30, bias=True)\n",
-       "  (linear2): Linear(in_features=30, out_features=10000, bias=True)\n",
+       "  (embedding): Embedding(30000, 300)\n",
+       "  (linear1): Linear(in_features=600, out_features=300, bias=True)\n",
+       "  (linear2): Linear(in_features=300, out_features=30000, bias=True)\n",
        "  (softmax): Softmax(dim=1)\n",
        ")"
       ]
@@ -281,8 +263,13 @@
    "outputs": [],
    "source": [
     "def generate_result(input_path, output_path='out.tsv'):\n",
+    "    lines = []\n",
     "    with open(input_path, encoding='utf-8') as f:\n",
-    "        lines = f.readlines()\n",
+    "        for line in f:\n",
+    "            columns = line.split('\\t')\n",
+    "            prefix = columns[6]\n",
+    "            suffix = columns[7]\n",
+    "            lines.append(prefix)\n",
     "\n",
     "    with open(output_path, 'w', encoding='utf-8') as output_file:\n",
     "        for line in lines:\n",