trained adaptor

llama_test.ipynb

@@ -39,15 +39,31 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
+      "/home/matt/hf/sqllama-V0/.venv/lib/python3.7/site-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: /opt/conda did not contain libcudart.so as expected! Searching further paths...\n",
+      "  warn(msg)\n",
       "The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. \n",
       "The tokenizer class you load from this checkpoint is 'LLaMATokenizer'. \n",
       "The class this function is called from is 'LlamaTokenizer'.\n"
      ]
     },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "===================================BUG REPORT===================================\n",
+      "Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues\n",
+      "================================================================================\n",
+      "CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so\n",
+      "CUDA SETUP: Highest compute capability among GPUs detected: 7.5\n",
+      "CUDA SETUP: Detected CUDA version 113\n",
+      "CUDA SETUP: Loading binary /home/matt/hf/sqllama-V0/.venv/lib/python3.7/site-packages/bitsandbytes/libbitsandbytes_cuda113.so...\n"
+     ]
+    },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3ab80e2a1c0744e0af747ba63429a2af",
+       "model_id": "5616e727844a4f0b9efaff97aa2f9d75",
        "version_major": 2,
        "version_minor": 0
       },
@@ -61,6 +77,7 @@
    ],
    "source": [
     "from transformers import LlamaTokenizer, LlamaForCausalLM\n",
+    "from peft import prepare_model_for_int8_training\n",
     "tokenizer = LlamaTokenizer.from_pretrained(\n",
     "    \"decapoda-research/llama-7b-hf\")\n",
     "   \n",
@@ -68,9 +85,12 @@
     "#tokenizer.padding_side = 'left'\n",
     "model = LlamaForCausalLM.from_pretrained(\n",
     "    \"decapoda-research/llama-7b-hf\",\n",
+    "    load_in_8bit=True,\n",
     "    device_map=\"auto\",\n",
     "    torch_dtype=torch.float16\n",
-    ")\n"
+    ")\n",
+    "\n",
+    "model = prepare_model_for_int8_training(model)\n"
    ]
   },
   {
@@ -168,7 +188,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -232,7 +252,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -241,34 +261,35 @@
      "text": [
       "\n",
       "Below is a question that describes a data request, paired with an input that describes a SQL table.  Write a SQL query that retrieves the data.\n",
-      "### Question: What is the Displacement of the Iveco F1CE3481E Engine?\n",
-      "### Input: Table 2-1415821-6 has columns Model (text),Engine (text),Displacement (text),Valvetrain (text),Fuel system (text),Max. power at rpm (text),Max. torque at rpm (text).  \n",
-      "### Answer: SELECT  Displacement FROM 2-1415821-6 WHERE Engine = 'iveco f1ce3481e'\n",
+      "### Question: How many games does novica veličković have when there's more than 24 rebounds?\n",
+      "### Input: Table 2-16050349-8 has columns Rank (real),Name (text),Team (text),Games (real),Rebounds (real).  \n",
+      "### Answer: SELECT COUNT Games FROM 2-16050349-8 WHERE Name = 'novica veličković' AND Rebounds > 24\n",
       "\n",
       "Below is a question that describes a data request, paired with an input that describes a SQL table.  Write a SQL query that retrieves the data.\n",
-      "### Question: What is the record of team utah?\n",
-      "### Input: Table 2-17355628-9 has columns Game (real),Date (text),Team (text),Score (text),High points (text),High rebounds (text),High assists (text),Location Attendance (text),Record (text).  \n",
-      "### Answer: SELECT  Record FROM 2-17355628-9 WHERE Team = 'utah'\n",
+      "### Question: What is the number of capacity at somerset park?\n",
+      "### Input: Table 1-11206787-5 has columns Team (text),Stadium (text),Capacity (real),Highest (real),Lowest (real),Average (real).  \n",
+      "### Answer: SELECT COUNT Capacity FROM 1-11206787-5 WHERE Stadium = 'Somerset Park'\n",
       "\n",
       "Below is a question that describes a data request, paired with an input that describes a SQL table.  Write a SQL query that retrieves the data.\n",
-      "### Question: What is the home of the team with a 16-8 record?\n",
-      "### Input: Table 2-16188254-4 has columns Date (text),Visitor (text),Score (text),Home (text),Leading scorer (text),Attendance (text),Record (text).  \n",
-      "### Answer: SELECT  Home FROM 2-16188254-4 WHERE Record = '16-8'\n",
+      "### Question: What is the number & name with an Undergoing overhaul, restoration or repairs date?\n",
+      "### Input: Table 2-11913905-6 has columns Number & Name (text),Description (text),Livery (text),Owner(s) (text),Date (text).  \n",
+      "### Answer: SELECT  Number & Name FROM 2-11913905-6 WHERE Date = 'undergoing overhaul, restoration or repairs'\n",
       "\n",
       "Below is a question that describes a data request, paired with an input that describes a SQL table.  Write a SQL query that retrieves the data.\n",
-      "### Question: What week did the Galaxy play the Amsterdam Admirals?\n",
-      "### Input: Table 1-24814477-2 has columns Week (real),Date (text),Kickoff (text),Opponent (text),Final score (text),Team record (text),Game site (text),Attendance (real).  \n",
-      "### Answer: SELECT  Week FROM 1-24814477-2 WHERE Opponent = 'Amsterdam Admirals'\n",
+      "### Question: What year did Orlando have a School/Club team in Clemson?\n",
+      "### Input: Table 2-15621965-7 has columns Player (text),Nationality (text),Position (text),Years in Orlando (text),School/Club Team (text).  \n",
+      "### Answer: SELECT  Years in Orlando FROM 2-15621965-7 WHERE School/Club Team = 'clemson'\n",
       "\n",
       "Below is a question that describes a data request, paired with an input that describes a SQL table.  Write a SQL query that retrieves the data.\n",
-      "### Question: How many caps did Mitchell Duke have overall?\n",
-      "### Input: Table 2-1257177-1 has columns Player (text),Country (text),Caps (real),Goals (text),Years Active (text).  \n",
-      "### Answer: SELECT COUNT Caps FROM 2-1257177-1 WHERE Player = 'mitchell duke'\n"
+      "### Question: How many Deaths have a Fate of damaged, and a Tonnage (GRT) smaller than 4,917?\n",
+      "### Input: Table 2-18914307-1 has columns Date (text),Ship Name (text),Flag (text),Tonnage ( GRT ) (real),Fate (text),Deaths (real).  \n",
+      "### Answer: SELECT COUNT Deaths FROM 2-18914307-1 WHERE Fate = 'damaged' AND Tonnage ( GRT ) < 4,917\n"
      ]
     }
    ],
    "source": [
     "import random\n",
+    "import json\n",
     "\n",
     "# defined by WikiSQL\n",
     "\n",
@@ -366,13 +387,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 26,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "4f44918087484dd58b958a64cabdecb6",
+       "model_id": "431b36f60a3940cf8646e1bea4324745",
        "version_major": 2,
        "version_minor": 0
       },
@@ -407,7 +428,7 @@
     "    target_modules=['q_proj','v_proj']\n",
     ")\n",
     "\n",
-    "modad = get_peft_model(model,lora_cfg)\n",
+    "model = get_peft_model(model,lora_cfg)\n",
     "\n",
     "tokenizer.pad_token_id = 0\n",
     "\n",
@@ -422,7 +443,7 @@
     "        padding=\"max_length\"\n",
     "        ))\n",
     "\n",
-    "#data.remove_columns('prompt')\n",
+    "data = data.remove_columns('prompt')\n",
     "\n",
     "targs = transformers.TrainingArguments(\n",
     "    per_device_train_batch_size=MICRO_BATCH,\n",
@@ -438,7 +459,7 @@
     ")\n",
     "\n",
     "\n",
-    "modad.config.use_cache = False"
+    "model.config.use_cache = False"
    ]
   },
   {
@@ -451,7 +472,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -459,10 +480,10 @@
      "output_type": "stream",
      "text": [
       "Dataset({\n",
-      "    features: ['prompt', 'input_ids', 'attention_mask'],\n",
+      "    features: ['input_ids', 'attention_mask'],\n",
       "    num_rows: 56355\n",
       "})\n",
-      "{'prompt': \"Below is a question that describes a data request, paired with an input that describes a SQL table.  Write a SQL query that retrieves the data.\\n### Question: Tell me what the notes are for South Australia \\n### Input: Table 1-1000181-1 has columns State/territory (text),Text/background colour (text),Format (text),Current slogan (text),Current series (text),Notes (text).  \\n### Answer: SELECT  Notes FROM 1-1000181-1 WHERE Current slogan = 'SOUTH AUSTRALIA'\", 'input_ids': [0, 13866, 338, 263, 1139, 393, 16612, 263, 848, 2009, 29892, 3300, 2859, 411, 385, 1881, 393, 16612, 263, 3758, 1591, 29889, 29871, 14350, 263, 3758, 2346, 393, 5663, 17180, 278, 848, 29889, 13, 2277, 29937, 894, 29901, 24948, 592, 825, 278, 11486, 526, 363, 4275, 8314, 29871, 13, 2277, 29937, 10567, 29901, 6137, 29871, 29896, 29899, 29896, 29900, 29900, 29900, 29896, 29947, 29896, 29899, 29896, 756, 4341, 4306, 29914, 357, 768, 706, 313, 726, 511, 1626, 29914, 7042, 12384, 313, 726, 511, 5809, 313, 726, 511, 7583, 269, 1188, 273, 313, 726, 511, 7583, 3652, 313, 726, 511, 3664, 267, 313, 726, 467, 259, 13, 2277, 29937, 673, 29901, 5097, 29871, 8695, 3895, 29871, 29896, 29899, 29896, 29900, 29900, 29900, 29896, 29947, 29896, 29899, 29896, 5754, 9626, 269, 1188, 273, 353, 525, 6156, 2692, 29950, 319, 29965, 10810, 1964, 10764, 29915, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}\n"
+      "{'input_ids': [0, 13866, 338, 263, 1139, 393, 16612, 263, 848, 2009, 29892, 3300, 2859, 411, 385, 1881, 393, 16612, 263, 3758, 1591, 29889, 29871, 14350, 263, 3758, 2346, 393, 5663, 17180, 278, 848, 29889, 13, 2277, 29937, 894, 29901, 24948, 592, 825, 278, 11486, 526, 363, 4275, 8314, 29871, 13, 2277, 29937, 10567, 29901, 6137, 29871, 29896, 29899, 29896, 29900, 29900, 29900, 29896, 29947, 29896, 29899, 29896, 756, 4341, 4306, 29914, 357, 768, 706, 313, 726, 511, 1626, 29914, 7042, 12384, 313, 726, 511, 5809, 313, 726, 511, 7583, 269, 1188, 273, 313, 726, 511, 7583, 3652, 313, 726, 511, 3664, 267, 313, 726, 467, 259, 13, 2277, 29937, 673, 29901, 5097, 29871, 8695, 3895, 29871, 29896, 29899, 29896, 29900, 29900, 29900, 29896, 29947, 29896, 29899, 29896, 5754, 9626, 269, 1188, 273, 353, 525, 6156, 2692, 29950, 319, 29965, 10810, 1964, 10764, 29915, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}\n"
      ]
     }
    ],
@@ -483,46 +504,1802 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/matt/hf/sqllama-V0/.venv/lib/python3.7/site-packages/transformers/optimization.py:395: FutureWarning: This implementation of AdamW is deprecated and will be removed in a future version. Use the PyTorch implementation torch.optim.AdamW instead, or set `no_deprecation_warning=True` to disable this warning\n",
-      "  FutureWarning,\n"
-     ]
-    },
-    {
-     "ename": "ValueError",
-     "evalue": "Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' 'truncation=True' to have batched tensors with the same length. Perhaps your features (`prompt` in this case) have excessive nesting (inputs type `list` where type `int` is expected).",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m~/hf/sqllama-V0/.venv/lib/python3.7/site-packages/transformers/tokenization_utils_base.py\u001b[0m in \u001b[0;36mconvert_to_tensors\u001b[0;34m(self, tensor_type, prepend_batch_axis)\u001b[0m\n\u001b[1;32m    716\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mis_tensor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 717\u001b[0;31m                     \u001b[0mtensor\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mas_tensor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    718\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mValueError\u001b[0m: too many dimensions 'str'",
-      "\nThe above exception was the direct cause of the following exception:\n",
-      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
-      "\u001b[0;32m/var/tmp/ipykernel_2309/3549391384.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0mdata_collator\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtransformers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataCollatorForLanguageModeling\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtokenizer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmlm\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m )\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mtrainer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresume_from_checkpoint\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      8\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msave_pretrained\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'sqllama-out'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/hf/sqllama-V0/.venv/lib/python3.7/site-packages/transformers/trainer.py\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(self, resume_from_checkpoint, trial, ignore_keys_for_eval, **kwargs)\u001b[0m\n\u001b[1;32m   1664\u001b[0m             \u001b[0mresume_from_checkpoint\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mresume_from_checkpoint\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1665\u001b[0m             \u001b[0mtrial\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtrial\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1666\u001b[0;31m             \u001b[0mignore_keys_for_eval\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mignore_keys_for_eval\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1667\u001b[0m         )\n\u001b[1;32m   1668\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/hf/sqllama-V0/.venv/lib/python3.7/site-packages/transformers/trainer.py\u001b[0m in \u001b[0;36m_inner_training_loop\u001b[0;34m(self, batch_size, args, resume_from_checkpoint, trial, ignore_keys_for_eval)\u001b[0m\n\u001b[1;32m   1897\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1898\u001b[0m             \u001b[0mstep\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1899\u001b[0;31m             \u001b[0;32mfor\u001b[0m \u001b[0mstep\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minputs\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mepoch_iterator\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1900\u001b[0m                 \u001b[0mtotal_batched_samples\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1901\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mrng_to_sync\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/hf/sqllama-V0/.venv/lib/python3.7/site-packages/torch/utils/data/dataloader.py\u001b[0m in \u001b[0;36m__next__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    626\u001b[0m                 \u001b[0;31m# TODO(https://github.com/pytorch/pytorch/issues/76750)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    627\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore[call-arg]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 628\u001b[0;31m             \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_next_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    629\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_num_yielded\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    630\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dataset_kind\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0m_DatasetKind\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mIterable\u001b[0m \u001b[0;32mand\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m\\\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/hf/sqllama-V0/.venv/lib/python3.7/site-packages/torch/utils/data/dataloader.py\u001b[0m in \u001b[0;36m_next_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    669\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_next_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    670\u001b[0m         \u001b[0mindex\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_next_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# may raise StopIteration\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 671\u001b[0;31m         \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_dataset_fetcher\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfetch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# may raise StopIteration\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    672\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_pin_memory\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    673\u001b[0m             \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_utils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpin_memory\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpin_memory\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_pin_memory_device\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/hf/sqllama-V0/.venv/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py\u001b[0m in \u001b[0;36mfetch\u001b[0;34m(self, possibly_batched_index)\u001b[0m\n\u001b[1;32m     59\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     60\u001b[0m             \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdataset\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mpossibly_batched_index\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 61\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcollate_fn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;32m~/hf/sqllama-V0/.venv/lib/python3.7/site-packages/transformers/data/data_collator.py\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, features, return_tensors)\u001b[0m\n\u001b[1;32m     43\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtf_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     44\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mreturn_tensors\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"pt\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 45\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtorch_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     46\u001b[0m         \u001b[0;32melif\u001b[0m \u001b[0mreturn_tensors\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"np\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     47\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnumpy_call\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfeatures\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/hf/sqllama-V0/.venv/lib/python3.7/site-packages/transformers/data/data_collator.py\u001b[0m in \u001b[0;36mtorch_call\u001b[0;34m(self, examples)\u001b[0m\n\u001b[1;32m    727\u001b[0m         \u001b[0;31m# Handle dict or lists with proper padding and conversion to tensor.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    728\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexamples\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mMapping\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 729\u001b[0;31m             \u001b[0mbatch\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtokenizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpad\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexamples\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mreturn_tensors\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"pt\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpad_to_multiple_of\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpad_to_multiple_of\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    730\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    731\u001b[0m             batch = {\n",
-      "\u001b[0;32m~/hf/sqllama-V0/.venv/lib/python3.7/site-packages/transformers/tokenization_utils_base.py\u001b[0m in \u001b[0;36mpad\u001b[0;34m(self, encoded_inputs, padding, max_length, pad_to_multiple_of, return_attention_mask, return_tensors, verbose)\u001b[0m\n\u001b[1;32m   3033\u001b[0m                 \u001b[0mbatch_outputs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3034\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3035\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mBatchEncoding\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbatch_outputs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtensor_type\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mreturn_tensors\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3036\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3037\u001b[0m     def create_token_type_ids_from_sequences(\n",
-      "\u001b[0;32m~/hf/sqllama-V0/.venv/lib/python3.7/site-packages/transformers/tokenization_utils_base.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, data, encoding, tensor_type, prepend_batch_axis, n_sequences)\u001b[0m\n\u001b[1;32m    208\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_n_sequences\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mn_sequences\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    209\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 210\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconvert_to_tensors\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtensor_type\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtensor_type\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprepend_batch_axis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mprepend_batch_axis\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    211\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    212\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/hf/sqllama-V0/.venv/lib/python3.7/site-packages/transformers/tokenization_utils_base.py\u001b[0m in \u001b[0;36mconvert_to_tensors\u001b[0;34m(self, tensor_type, prepend_batch_axis)\u001b[0m\n\u001b[1;32m    736\u001b[0m                     \u001b[0;34mf\" features (`{key}` in this case) have excessive nesting (inputs type `list` where type `int` is\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    737\u001b[0m                     \u001b[0;34m\" expected).\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 738\u001b[0;31m                 ) from e\n\u001b[0m\u001b[1;32m    739\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    740\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mValueError\u001b[0m: Unable to create tensor, you should probably activate truncation and/or padding with 'padding=True' 'truncation=True' to have batched tensors with the same length. Perhaps your features (`prompt` in this case) have excessive nesting (inputs type `list` where type `int` is expected)."
-     ]
+     "data": {
+      "text/html": [
+       "\n",
+       "    <div>\n",
+       "      \n",
+       "      <progress value='440' max='440' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
+       "      [440/440 11:19:07, Epoch 0/1]\n",
+       "    </div>\n",
+       "    <table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       " <tr style=\"text-align: left;\">\n",
+       "      <th>Step</th>\n",
+       "      <th>Training Loss</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <td>1</td>\n",
+       "      <td>2.517200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>2</td>\n",
+       "      <td>2.482300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>3</td>\n",
+       "      <td>2.444100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>4</td>\n",
+       "      <td>2.456500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>5</td>\n",
+       "      <td>2.441400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>6</td>\n",
+       "      <td>2.484600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>7</td>\n",
+       "      <td>2.424000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>8</td>\n",
+       "      <td>2.477900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>9</td>\n",
+       "      <td>2.429700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>10</td>\n",
+       "      <td>2.436000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>11</td>\n",
+       "      <td>2.422000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>12</td>\n",
+       "      <td>2.408800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>13</td>\n",
+       "      <td>2.402900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>14</td>\n",
+       "      <td>2.424500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>15</td>\n",
+       "      <td>2.421800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>16</td>\n",
+       "      <td>2.424100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>17</td>\n",
+       "      <td>2.404000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>18</td>\n",
+       "      <td>2.386900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>19</td>\n",
+       "      <td>2.414400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>20</td>\n",
+       "      <td>2.370600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>21</td>\n",
+       "      <td>2.382500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>22</td>\n",
+       "      <td>2.350700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>23</td>\n",
+       "      <td>2.385700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>24</td>\n",
+       "      <td>2.350400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>25</td>\n",
+       "      <td>2.354900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>26</td>\n",
+       "      <td>2.345400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>27</td>\n",
+       "      <td>2.373000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>28</td>\n",
+       "      <td>2.343200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>29</td>\n",
+       "      <td>2.374300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>30</td>\n",
+       "      <td>2.325000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>31</td>\n",
+       "      <td>2.352000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>32</td>\n",
+       "      <td>2.344600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>33</td>\n",
+       "      <td>2.360000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>34</td>\n",
+       "      <td>2.347400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>35</td>\n",
+       "      <td>2.346700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>36</td>\n",
+       "      <td>2.329000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>37</td>\n",
+       "      <td>2.314600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>38</td>\n",
+       "      <td>2.306000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>39</td>\n",
+       "      <td>2.292600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>40</td>\n",
+       "      <td>2.333800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>41</td>\n",
+       "      <td>2.311500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>42</td>\n",
+       "      <td>2.308300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>43</td>\n",
+       "      <td>2.287400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>44</td>\n",
+       "      <td>2.314100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>45</td>\n",
+       "      <td>2.280400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>46</td>\n",
+       "      <td>2.261300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>47</td>\n",
+       "      <td>2.274200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>48</td>\n",
+       "      <td>2.246900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>49</td>\n",
+       "      <td>2.257100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>50</td>\n",
+       "      <td>2.274500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>51</td>\n",
+       "      <td>2.245500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>52</td>\n",
+       "      <td>2.250700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>53</td>\n",
+       "      <td>2.296600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>54</td>\n",
+       "      <td>2.261000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>55</td>\n",
+       "      <td>2.223800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>56</td>\n",
+       "      <td>2.244000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>57</td>\n",
+       "      <td>2.228500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>58</td>\n",
+       "      <td>2.229100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>59</td>\n",
+       "      <td>2.162300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>60</td>\n",
+       "      <td>2.238000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>61</td>\n",
+       "      <td>2.246000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>62</td>\n",
+       "      <td>2.184800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>63</td>\n",
+       "      <td>2.195000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>64</td>\n",
+       "      <td>2.199500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>65</td>\n",
+       "      <td>2.180000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>66</td>\n",
+       "      <td>2.179800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>67</td>\n",
+       "      <td>2.149700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>68</td>\n",
+       "      <td>2.177000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>69</td>\n",
+       "      <td>2.156600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>70</td>\n",
+       "      <td>2.193400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>71</td>\n",
+       "      <td>2.163400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>72</td>\n",
+       "      <td>2.147400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>73</td>\n",
+       "      <td>2.134700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>74</td>\n",
+       "      <td>2.133200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>75</td>\n",
+       "      <td>2.118000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>76</td>\n",
+       "      <td>2.139000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>77</td>\n",
+       "      <td>2.102000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>78</td>\n",
+       "      <td>2.109100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>79</td>\n",
+       "      <td>2.099000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>80</td>\n",
+       "      <td>2.097500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>81</td>\n",
+       "      <td>2.073200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>82</td>\n",
+       "      <td>2.055200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>83</td>\n",
+       "      <td>2.078100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>84</td>\n",
+       "      <td>2.104800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>85</td>\n",
+       "      <td>2.061100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>86</td>\n",
+       "      <td>2.066500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>87</td>\n",
+       "      <td>2.073500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>88</td>\n",
+       "      <td>2.010500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>89</td>\n",
+       "      <td>2.045700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>90</td>\n",
+       "      <td>2.026700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>91</td>\n",
+       "      <td>2.046500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>92</td>\n",
+       "      <td>2.015300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>93</td>\n",
+       "      <td>2.019100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>94</td>\n",
+       "      <td>2.008600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>95</td>\n",
+       "      <td>1.961000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>96</td>\n",
+       "      <td>1.974300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>97</td>\n",
+       "      <td>1.991700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>98</td>\n",
+       "      <td>1.984700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>99</td>\n",
+       "      <td>1.975900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>100</td>\n",
+       "      <td>1.963900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>101</td>\n",
+       "      <td>1.934300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>102</td>\n",
+       "      <td>1.990400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>103</td>\n",
+       "      <td>1.914900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>104</td>\n",
+       "      <td>1.956100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>105</td>\n",
+       "      <td>1.943400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>106</td>\n",
+       "      <td>1.931000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>107</td>\n",
+       "      <td>1.919000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>108</td>\n",
+       "      <td>1.912800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>109</td>\n",
+       "      <td>1.920400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>110</td>\n",
+       "      <td>1.878300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>111</td>\n",
+       "      <td>1.890800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>112</td>\n",
+       "      <td>1.881900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>113</td>\n",
+       "      <td>1.885400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>114</td>\n",
+       "      <td>1.908400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>115</td>\n",
+       "      <td>1.871200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>116</td>\n",
+       "      <td>1.900000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>117</td>\n",
+       "      <td>1.888000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>118</td>\n",
+       "      <td>1.875100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>119</td>\n",
+       "      <td>1.855000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>120</td>\n",
+       "      <td>1.852100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>121</td>\n",
+       "      <td>1.851200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>122</td>\n",
+       "      <td>1.821800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>123</td>\n",
+       "      <td>1.853000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>124</td>\n",
+       "      <td>1.854700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>125</td>\n",
+       "      <td>1.806900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>126</td>\n",
+       "      <td>1.845300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>127</td>\n",
+       "      <td>1.797800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>128</td>\n",
+       "      <td>1.795300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>129</td>\n",
+       "      <td>1.799500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>130</td>\n",
+       "      <td>1.853900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>131</td>\n",
+       "      <td>1.780100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>132</td>\n",
+       "      <td>1.789400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>133</td>\n",
+       "      <td>1.776700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>134</td>\n",
+       "      <td>1.747300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>135</td>\n",
+       "      <td>1.753700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>136</td>\n",
+       "      <td>1.761300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>137</td>\n",
+       "      <td>1.725500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>138</td>\n",
+       "      <td>1.710800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>139</td>\n",
+       "      <td>1.733500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>140</td>\n",
+       "      <td>1.727000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>141</td>\n",
+       "      <td>1.744300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>142</td>\n",
+       "      <td>1.728900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>143</td>\n",
+       "      <td>1.725100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>144</td>\n",
+       "      <td>1.708000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>145</td>\n",
+       "      <td>1.709000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>146</td>\n",
+       "      <td>1.704600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>147</td>\n",
+       "      <td>1.684600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>148</td>\n",
+       "      <td>1.676100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>149</td>\n",
+       "      <td>1.682800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>150</td>\n",
+       "      <td>1.669900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>151</td>\n",
+       "      <td>1.636400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>152</td>\n",
+       "      <td>1.671500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>153</td>\n",
+       "      <td>1.673200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>154</td>\n",
+       "      <td>1.644300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>155</td>\n",
+       "      <td>1.620800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>156</td>\n",
+       "      <td>1.617500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>157</td>\n",
+       "      <td>1.647700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>158</td>\n",
+       "      <td>1.629300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>159</td>\n",
+       "      <td>1.608800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>160</td>\n",
+       "      <td>1.633000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>161</td>\n",
+       "      <td>1.618200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>162</td>\n",
+       "      <td>1.634300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>163</td>\n",
+       "      <td>1.588400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>164</td>\n",
+       "      <td>1.581100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>165</td>\n",
+       "      <td>1.584500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>166</td>\n",
+       "      <td>1.594800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>167</td>\n",
+       "      <td>1.563800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>168</td>\n",
+       "      <td>1.576900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>169</td>\n",
+       "      <td>1.546300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>170</td>\n",
+       "      <td>1.569800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>171</td>\n",
+       "      <td>1.592300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>172</td>\n",
+       "      <td>1.537800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>173</td>\n",
+       "      <td>1.519200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>174</td>\n",
+       "      <td>1.512100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>175</td>\n",
+       "      <td>1.581500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>176</td>\n",
+       "      <td>1.534500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>177</td>\n",
+       "      <td>1.509400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>178</td>\n",
+       "      <td>1.521300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>179</td>\n",
+       "      <td>1.528500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>180</td>\n",
+       "      <td>1.494300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>181</td>\n",
+       "      <td>1.495000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>182</td>\n",
+       "      <td>1.499700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>183</td>\n",
+       "      <td>1.461300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>184</td>\n",
+       "      <td>1.469200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>185</td>\n",
+       "      <td>1.495200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>186</td>\n",
+       "      <td>1.467400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>187</td>\n",
+       "      <td>1.437000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>188</td>\n",
+       "      <td>1.463000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>189</td>\n",
+       "      <td>1.437900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>190</td>\n",
+       "      <td>1.467400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>191</td>\n",
+       "      <td>1.472300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>192</td>\n",
+       "      <td>1.434000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>193</td>\n",
+       "      <td>1.411500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>194</td>\n",
+       "      <td>1.432500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>195</td>\n",
+       "      <td>1.459800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>196</td>\n",
+       "      <td>1.431900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>197</td>\n",
+       "      <td>1.456200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>198</td>\n",
+       "      <td>1.394800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>199</td>\n",
+       "      <td>1.422700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>200</td>\n",
+       "      <td>1.412800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>201</td>\n",
+       "      <td>1.413800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>202</td>\n",
+       "      <td>1.380000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>203</td>\n",
+       "      <td>1.407400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>204</td>\n",
+       "      <td>1.406200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>205</td>\n",
+       "      <td>1.396100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>206</td>\n",
+       "      <td>1.407100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>207</td>\n",
+       "      <td>1.379600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>208</td>\n",
+       "      <td>1.360600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>209</td>\n",
+       "      <td>1.395100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>210</td>\n",
+       "      <td>1.352500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>211</td>\n",
+       "      <td>1.358900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>212</td>\n",
+       "      <td>1.369100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>213</td>\n",
+       "      <td>1.342600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>214</td>\n",
+       "      <td>1.358900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>215</td>\n",
+       "      <td>1.320300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>216</td>\n",
+       "      <td>1.355700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>217</td>\n",
+       "      <td>1.315700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>218</td>\n",
+       "      <td>1.348800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>219</td>\n",
+       "      <td>1.319800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>220</td>\n",
+       "      <td>1.336500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>221</td>\n",
+       "      <td>1.339600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>222</td>\n",
+       "      <td>1.319500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>223</td>\n",
+       "      <td>1.319600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>224</td>\n",
+       "      <td>1.330200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>225</td>\n",
+       "      <td>1.271700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>226</td>\n",
+       "      <td>1.317300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>227</td>\n",
+       "      <td>1.287400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>228</td>\n",
+       "      <td>1.283300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>229</td>\n",
+       "      <td>1.280500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>230</td>\n",
+       "      <td>1.274200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>231</td>\n",
+       "      <td>1.297000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>232</td>\n",
+       "      <td>1.266400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>233</td>\n",
+       "      <td>1.253100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>234</td>\n",
+       "      <td>1.273100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>235</td>\n",
+       "      <td>1.293300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>236</td>\n",
+       "      <td>1.293000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>237</td>\n",
+       "      <td>1.273500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>238</td>\n",
+       "      <td>1.253100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>239</td>\n",
+       "      <td>1.257700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>240</td>\n",
+       "      <td>1.232500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>241</td>\n",
+       "      <td>1.233100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>242</td>\n",
+       "      <td>1.226000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>243</td>\n",
+       "      <td>1.218400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>244</td>\n",
+       "      <td>1.222800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>245</td>\n",
+       "      <td>1.232100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>246</td>\n",
+       "      <td>1.214800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>247</td>\n",
+       "      <td>1.205700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>248</td>\n",
+       "      <td>1.228400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>249</td>\n",
+       "      <td>1.202600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>250</td>\n",
+       "      <td>1.207700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>251</td>\n",
+       "      <td>1.205800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>252</td>\n",
+       "      <td>1.198400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>253</td>\n",
+       "      <td>1.207800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>254</td>\n",
+       "      <td>1.198600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>255</td>\n",
+       "      <td>1.201700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>256</td>\n",
+       "      <td>1.195500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>257</td>\n",
+       "      <td>1.190500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>258</td>\n",
+       "      <td>1.197100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>259</td>\n",
+       "      <td>1.165100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>260</td>\n",
+       "      <td>1.173200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>261</td>\n",
+       "      <td>1.163400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>262</td>\n",
+       "      <td>1.191500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>263</td>\n",
+       "      <td>1.173700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>264</td>\n",
+       "      <td>1.134400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>265</td>\n",
+       "      <td>1.165500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>266</td>\n",
+       "      <td>1.134800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>267</td>\n",
+       "      <td>1.149500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>268</td>\n",
+       "      <td>1.173100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>269</td>\n",
+       "      <td>1.137000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>270</td>\n",
+       "      <td>1.171200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>271</td>\n",
+       "      <td>1.120600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>272</td>\n",
+       "      <td>1.147600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>273</td>\n",
+       "      <td>1.128300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>274</td>\n",
+       "      <td>1.150300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>275</td>\n",
+       "      <td>1.147700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>276</td>\n",
+       "      <td>1.150200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>277</td>\n",
+       "      <td>1.106900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>278</td>\n",
+       "      <td>1.145400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>279</td>\n",
+       "      <td>1.117300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>280</td>\n",
+       "      <td>1.121900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>281</td>\n",
+       "      <td>1.139400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>282</td>\n",
+       "      <td>1.109100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>283</td>\n",
+       "      <td>1.142100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>284</td>\n",
+       "      <td>1.117300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>285</td>\n",
+       "      <td>1.104200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>286</td>\n",
+       "      <td>1.134200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>287</td>\n",
+       "      <td>1.100400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>288</td>\n",
+       "      <td>1.092100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>289</td>\n",
+       "      <td>1.120500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>290</td>\n",
+       "      <td>1.088100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>291</td>\n",
+       "      <td>1.128600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>292</td>\n",
+       "      <td>1.105400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>293</td>\n",
+       "      <td>1.094000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>294</td>\n",
+       "      <td>1.108900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>295</td>\n",
+       "      <td>1.073100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>296</td>\n",
+       "      <td>1.100900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>297</td>\n",
+       "      <td>1.092400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>298</td>\n",
+       "      <td>1.090300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>299</td>\n",
+       "      <td>1.079400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>300</td>\n",
+       "      <td>1.090300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>301</td>\n",
+       "      <td>1.086100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>302</td>\n",
+       "      <td>1.080300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>303</td>\n",
+       "      <td>1.075600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>304</td>\n",
+       "      <td>1.075900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>305</td>\n",
+       "      <td>1.092200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>306</td>\n",
+       "      <td>1.070600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>307</td>\n",
+       "      <td>1.068800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>308</td>\n",
+       "      <td>1.071300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>309</td>\n",
+       "      <td>1.073900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>310</td>\n",
+       "      <td>1.055400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>311</td>\n",
+       "      <td>1.067900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>312</td>\n",
+       "      <td>1.041000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>313</td>\n",
+       "      <td>1.048600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>314</td>\n",
+       "      <td>1.072600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>315</td>\n",
+       "      <td>1.058800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>316</td>\n",
+       "      <td>1.039000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>317</td>\n",
+       "      <td>1.072300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>318</td>\n",
+       "      <td>1.056600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>319</td>\n",
+       "      <td>1.035100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>320</td>\n",
+       "      <td>1.052800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>321</td>\n",
+       "      <td>1.046700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>322</td>\n",
+       "      <td>1.073400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>323</td>\n",
+       "      <td>1.054000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>324</td>\n",
+       "      <td>1.077100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>325</td>\n",
+       "      <td>1.035200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>326</td>\n",
+       "      <td>1.027700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>327</td>\n",
+       "      <td>1.060000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>328</td>\n",
+       "      <td>1.048900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>329</td>\n",
+       "      <td>1.040000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>330</td>\n",
+       "      <td>1.026900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>331</td>\n",
+       "      <td>1.049300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>332</td>\n",
+       "      <td>1.017100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>333</td>\n",
+       "      <td>0.996200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>334</td>\n",
+       "      <td>1.006400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>335</td>\n",
+       "      <td>1.026700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>336</td>\n",
+       "      <td>1.073700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>337</td>\n",
+       "      <td>1.039200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>338</td>\n",
+       "      <td>1.041100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>339</td>\n",
+       "      <td>1.054300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>340</td>\n",
+       "      <td>1.013500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>341</td>\n",
+       "      <td>1.024900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>342</td>\n",
+       "      <td>1.003300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>343</td>\n",
+       "      <td>0.993400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>344</td>\n",
+       "      <td>1.037300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>345</td>\n",
+       "      <td>1.009300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>346</td>\n",
+       "      <td>1.030400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>347</td>\n",
+       "      <td>1.001400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>348</td>\n",
+       "      <td>1.012100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>349</td>\n",
+       "      <td>1.027300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>350</td>\n",
+       "      <td>1.012700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>351</td>\n",
+       "      <td>1.013400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>352</td>\n",
+       "      <td>1.004400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>353</td>\n",
+       "      <td>1.024800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>354</td>\n",
+       "      <td>0.990700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>355</td>\n",
+       "      <td>1.048600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>356</td>\n",
+       "      <td>0.992700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>357</td>\n",
+       "      <td>0.991800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>358</td>\n",
+       "      <td>0.985300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>359</td>\n",
+       "      <td>1.019100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>360</td>\n",
+       "      <td>1.007300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>361</td>\n",
+       "      <td>1.025500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>362</td>\n",
+       "      <td>0.999100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>363</td>\n",
+       "      <td>0.997900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>364</td>\n",
+       "      <td>1.013300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>365</td>\n",
+       "      <td>1.014700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>366</td>\n",
+       "      <td>1.037700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>367</td>\n",
+       "      <td>0.992400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>368</td>\n",
+       "      <td>0.988800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>369</td>\n",
+       "      <td>0.993900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>370</td>\n",
+       "      <td>0.999500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>371</td>\n",
+       "      <td>0.973000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>372</td>\n",
+       "      <td>0.972200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>373</td>\n",
+       "      <td>0.989200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>374</td>\n",
+       "      <td>0.994500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>375</td>\n",
+       "      <td>0.995800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>376</td>\n",
+       "      <td>0.992000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>377</td>\n",
+       "      <td>0.977800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>378</td>\n",
+       "      <td>0.975700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>379</td>\n",
+       "      <td>0.973700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>380</td>\n",
+       "      <td>0.986200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>381</td>\n",
+       "      <td>1.008000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>382</td>\n",
+       "      <td>0.954100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>383</td>\n",
+       "      <td>1.015900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>384</td>\n",
+       "      <td>1.008200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>385</td>\n",
+       "      <td>0.974700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>386</td>\n",
+       "      <td>0.987500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>387</td>\n",
+       "      <td>0.993700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>388</td>\n",
+       "      <td>0.999200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>389</td>\n",
+       "      <td>1.000700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>390</td>\n",
+       "      <td>0.978600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>391</td>\n",
+       "      <td>0.956200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>392</td>\n",
+       "      <td>1.001600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>393</td>\n",
+       "      <td>0.971300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>394</td>\n",
+       "      <td>0.965800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>395</td>\n",
+       "      <td>0.981000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>396</td>\n",
+       "      <td>0.965400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>397</td>\n",
+       "      <td>0.974200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>398</td>\n",
+       "      <td>0.970700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>399</td>\n",
+       "      <td>0.953500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>400</td>\n",
+       "      <td>0.979700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>401</td>\n",
+       "      <td>0.957700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>402</td>\n",
+       "      <td>0.984600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>403</td>\n",
+       "      <td>1.015600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>404</td>\n",
+       "      <td>0.976800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>405</td>\n",
+       "      <td>0.969100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>406</td>\n",
+       "      <td>0.974200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>407</td>\n",
+       "      <td>0.983300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>408</td>\n",
+       "      <td>0.974300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>409</td>\n",
+       "      <td>0.980600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>410</td>\n",
+       "      <td>0.986300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>411</td>\n",
+       "      <td>0.968100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>412</td>\n",
+       "      <td>0.980500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>413</td>\n",
+       "      <td>0.976200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>414</td>\n",
+       "      <td>0.987300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>415</td>\n",
+       "      <td>0.971600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>416</td>\n",
+       "      <td>0.985200</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>417</td>\n",
+       "      <td>0.989800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>418</td>\n",
+       "      <td>0.972000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>419</td>\n",
+       "      <td>0.971100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>420</td>\n",
+       "      <td>0.988800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>421</td>\n",
+       "      <td>0.965600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>422</td>\n",
+       "      <td>1.020400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>423</td>\n",
+       "      <td>0.978000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>424</td>\n",
+       "      <td>0.987800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>425</td>\n",
+       "      <td>0.953700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>426</td>\n",
+       "      <td>0.990400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>427</td>\n",
+       "      <td>0.982900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>428</td>\n",
+       "      <td>0.989100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>429</td>\n",
+       "      <td>0.983800</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>430</td>\n",
+       "      <td>0.981500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>431</td>\n",
+       "      <td>0.966900</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>432</td>\n",
+       "      <td>0.967300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>433</td>\n",
+       "      <td>0.999400</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>434</td>\n",
+       "      <td>0.973100</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>435</td>\n",
+       "      <td>0.980500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>436</td>\n",
+       "      <td>0.995500</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>437</td>\n",
+       "      <td>0.960300</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>438</td>\n",
+       "      <td>0.953700</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>439</td>\n",
+       "      <td>0.993600</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <td>440</td>\n",
+       "      <td>0.965100</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table><p>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
+    "\n",
+    "\n",
     "trainer = transformers.Trainer(\n",
-    "    model = modad,\n",
+    "    model = model,\n",
     "    train_dataset = data,\n",
     "    args = targs,\n",
     "    data_collator=transformers.DataCollatorForLanguageModeling(tokenizer, mlm=False)\n",

res.txt

@@ -0,0 +1,515 @@
+
+Below is a question that describes a data request, paired with an input that describes a SQL table.  Write a SQL query that retrieves the data.
+### Question: How many games does novica veličković have when there's more than 24 rebounds?
+### Input: Table 2-16050349-8 has columns Rank (real),Name (text),Team (text),Games (real),Rebounds (real).  
+### Answer: SELECT COUNT Games FROM 2-16050349-8 WHERE Name = 'novica veličković' AND Rebounds > 24
+
+Below is a question that describes a data request, paired with an input that describes a SQL table.  Write a SQL query that retrieves the data.
+### Question: What is the number of capacity at somerset park?
+### Input: Table 1-11206787-5 has columns Team (text),Stadium (text),Capacity (real),Highest (real),Lowest (real),Average (real).  
+### Answer: SELECT COUNT Capacity FROM 1-11206787-5 WHERE Stadium = 'Somerset Park'
+
+Below is a question that describes a data request, paired with an input that describes a SQL table.  Write a SQL query that retrieves the data.
+### Question: What is the number & name with an Undergoing overhaul, restoration or repairs date?
+### Input: Table 2-11913905-6 has columns Number & Name (text),Description (text),Livery (text),Owner(s) (text),Date (text).  
+### Answer: SELECT  Number & Name FROM 2-11913905-6 WHERE Date = 'undergoing overhaul, restoration or repairs'
+
+Below is a question that describes a data request, paired with an input that describes a SQL table.  Write a SQL query that retrieves the data.
+### Question: What year did Orlando have a School/Club team in Clemson?
+### Input: Table 2-15621965-7 has columns Player (text),Nationality (text),Position (text),Years in Orlando (text),School/Club Team (text).  
+### Answer: SELECT  Years in Orlando FROM 2-15621965-7 WHERE School/Club Team = 'clemson'
+
+Below is a question that describes a data request, paired with an input that describes a SQL table.  Write a SQL query that retrieves the data.
+### Question: How many Deaths have a Fate of damaged, and a Tonnage (GRT) smaller than 4,917?
+### Input: Table 2-18914307-1 has columns Date (text),Ship Name (text),Flag (text),Tonnage ( GRT ) (real),Fate (text),Deaths (real).  
+### Answer: SELECT COUNT Deaths FROM 2-18914307-1 WHERE Fate = 'damaged' AND Tonnage ( GRT ) < 4,917
+
+
+
+
+
+{'phase': 1, 'table_id': '1-1000181-1', 'question': 'Tell me what the notes are for South Australia ', 'sql': {'sel': 5, 'conds': [[3, 0, 'SOUTH AUSTRALIA']], 'agg': 0}}
+
+1-1000181-1
+['State/territory', 'Text/background colour', 'Format', 'Current slogan', 'Current series', 'Notes']
+
+{'id': '1-1000181-1', 'header': ['State/territory', 'Text/background colour', 'Format', 'Current slogan', 'Current series', 'Notes'], 'types': ['text', 'text', 'text', 'text', 'text', 'text'], 'rows': [['Australian Capital Territory', 'blue/white', 'Yaa·nna', 'ACT · CELEBRATION OF A CENTURY 2013', 'YIL·00A', 'Slogan screenprinted on plate'], ['New South Wales', 'black/yellow', 'aa·nn·aa', 'NEW SOUTH WALES', 'BX·99·HI', 'No slogan on current series'], ['New South Wales', 'black/white', 'aaa·nna', 'NSW', 'CPX·12A', 'Optional white slimline series'], ['Northern Territory', 'ochre/white', 'Ca·nn·aa', 'NT · OUTBACK AUSTRALIA', 'CB·06·ZZ', 'New series began in June 2011'], ['Queensland', 'maroon/white', 'nnn·aaa', 'QUEENSLAND · SUNSHINE STATE', '999·TLG', 'Slogan embossed on plate'], ['South Australia', 'black/white', 'Snnn·aaa', 'SOUTH AUSTRALIA', 'S000·AZD', 'No slogan on current series'], ['Victoria', 'blue/white', 'aaa·nnn', 'VICTORIA - THE PLACE TO BE', 'ZZZ·562', 'Current series will be exhausted this year']], 'name': 'table_1000181_1'}
+SELECT  col5 FROM table WHERE col3 = SOUTH AUSTRALIA
+SELECT  Notes FROM table WHERE Current slogan = SOUTH AUSTRALIA
+fatal: destination path 'WikiSQL' already exists and is not an empty directory.
+data/
+data/train.jsonl
+data/test.tables.jsonl
+data/test.db
+data/dev.tables.jsonl
+data/dev.db
+data/test.jsonl
+data/train.tables.jsonl
+data/train.db
+data/dev.jsonl
+/home/matt/hf/sqllama-V0/.venv/lib/python3.7/site-packages/transformers/generation/utils.py:1220: UserWarning: You have modified the pretrained model configuration to control generation. This is a deprecated strategy to control generation and will be removed soon, in a future version. Please use a generation configuration file (see https://huggingface.co/docs/transformers/main_classes/text_generation)
+  "You have modified the pretrained model configuration to control generation. This is a"
+ ⁇  hey dude, talk to me.
+I'm a 20 year old guy from the UK. I'm a bit of a nerd, I like to read, I like to write, I like to play video games, I like to watch movies, I like to listen
+/home/matt/hf/sqllama-V0/.venv/lib/python3.7/site-packages/bitsandbytes/cuda_setup/main.py:136: UserWarning: /opt/conda did not contain libcudart.so as expected! Searching further paths...
+  warn(msg)
+The tokenizer class you load from this checkpoint is not the same type as the class this function is called from. It may result in unexpected tokenization. 
+The tokenizer class you load from this checkpoint is 'LLaMATokenizer'. 
+The class this function is called from is 'LlamaTokenizer'.
+
+===================================BUG REPORT===================================
+Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues
+================================================================================
+CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so
+CUDA SETUP: Highest compute capability among GPUs detected: 7.5
+CUDA SETUP: Detected CUDA version 113
+CUDA SETUP: Loading binary /home/matt/hf/sqllama-V0/.venv/lib/python3.7/site-packages/bitsandbytes/libbitsandbytes_cuda113.so...
+True
+
+ [440/440 11:19:07, Epoch 0/1]
+Step	Training Loss
+1	2.517200
+2	2.482300
+3	2.444100
+4	2.456500
+5	2.441400
+6	2.484600
+7	2.424000
+8	2.477900
+9	2.429700
+10	2.436000
+11	2.422000
+12	2.408800
+13	2.402900
+14	2.424500
+15	2.421800
+16	2.424100
+17	2.404000
+18	2.386900
+19	2.414400
+20	2.370600
+21	2.382500
+22	2.350700
+23	2.385700
+24	2.350400
+25	2.354900
+26	2.345400
+27	2.373000
+28	2.343200
+29	2.374300
+30	2.325000
+31	2.352000
+32	2.344600
+33	2.360000
+34	2.347400
+35	2.346700
+36	2.329000
+37	2.314600
+38	2.306000
+39	2.292600
+40	2.333800
+41	2.311500
+42	2.308300
+43	2.287400
+44	2.314100
+45	2.280400
+46	2.261300
+47	2.274200
+48	2.246900
+49	2.257100
+50	2.274500
+51	2.245500
+52	2.250700
+53	2.296600
+54	2.261000
+55	2.223800
+56	2.244000
+57	2.228500
+58	2.229100
+59	2.162300
+60	2.238000
+61	2.246000
+62	2.184800
+63	2.195000
+64	2.199500
+65	2.180000
+66	2.179800
+67	2.149700
+68	2.177000
+69	2.156600
+70	2.193400
+71	2.163400
+72	2.147400
+73	2.134700
+74	2.133200
+75	2.118000
+76	2.139000
+77	2.102000
+78	2.109100
+79	2.099000
+80	2.097500
+81	2.073200
+82	2.055200
+83	2.078100
+84	2.104800
+85	2.061100
+86	2.066500
+87	2.073500
+88	2.010500
+89	2.045700
+90	2.026700
+91	2.046500
+92	2.015300
+93	2.019100
+94	2.008600
+95	1.961000
+96	1.974300
+97	1.991700
+98	1.984700
+99	1.975900
+100	1.963900
+101	1.934300
+102	1.990400
+103	1.914900
+104	1.956100
+105	1.943400
+106	1.931000
+107	1.919000
+108	1.912800
+109	1.920400
+110	1.878300
+111	1.890800
+112	1.881900
+113	1.885400
+114	1.908400
+115	1.871200
+116	1.900000
+117	1.888000
+118	1.875100
+119	1.855000
+120	1.852100
+121	1.851200
+122	1.821800
+123	1.853000
+124	1.854700
+125	1.806900
+126	1.845300
+127	1.797800
+128	1.795300
+129	1.799500
+130	1.853900
+131	1.780100
+132	1.789400
+133	1.776700
+134	1.747300
+135	1.753700
+136	1.761300
+137	1.725500
+138	1.710800
+139	1.733500
+140	1.727000
+141	1.744300
+142	1.728900
+143	1.725100
+144	1.708000
+145	1.709000
+146	1.704600
+147	1.684600
+148	1.676100
+149	1.682800
+150	1.669900
+151	1.636400
+152	1.671500
+153	1.673200
+154	1.644300
+155	1.620800
+156	1.617500
+157	1.647700
+158	1.629300
+159	1.608800
+160	1.633000
+161	1.618200
+162	1.634300
+163	1.588400
+164	1.581100
+165	1.584500
+166	1.594800
+167	1.563800
+168	1.576900
+169	1.546300
+170	1.569800
+171	1.592300
+172	1.537800
+173	1.519200
+174	1.512100
+175	1.581500
+176	1.534500
+177	1.509400
+178	1.521300
+179	1.528500
+180	1.494300
+181	1.495000
+182	1.499700
+183	1.461300
+184	1.469200
+185	1.495200
+186	1.467400
+187	1.437000
+188	1.463000
+189	1.437900
+190	1.467400
+191	1.472300
+192	1.434000
+193	1.411500
+194	1.432500
+195	1.459800
+196	1.431900
+197	1.456200
+198	1.394800
+199	1.422700
+200	1.412800
+201	1.413800
+202	1.380000
+203	1.407400
+204	1.406200
+205	1.396100
+206	1.407100
+207	1.379600
+208	1.360600
+209	1.395100
+210	1.352500
+211	1.358900
+212	1.369100
+213	1.342600
+214	1.358900
+215	1.320300
+216	1.355700
+217	1.315700
+218	1.348800
+219	1.319800
+220	1.336500
+221	1.339600
+222	1.319500
+223	1.319600
+224	1.330200
+225	1.271700
+226	1.317300
+227	1.287400
+228	1.283300
+229	1.280500
+230	1.274200
+231	1.297000
+232	1.266400
+233	1.253100
+234	1.273100
+235	1.293300
+236	1.293000
+237	1.273500
+238	1.253100
+239	1.257700
+240	1.232500
+241	1.233100
+242	1.226000
+243	1.218400
+244	1.222800
+245	1.232100
+246	1.214800
+247	1.205700
+248	1.228400
+249	1.202600
+250	1.207700
+251	1.205800
+252	1.198400
+253	1.207800
+254	1.198600
+255	1.201700
+256	1.195500
+257	1.190500
+258	1.197100
+259	1.165100
+260	1.173200
+261	1.163400
+262	1.191500
+263	1.173700
+264	1.134400
+265	1.165500
+266	1.134800
+267	1.149500
+268	1.173100
+269	1.137000
+270	1.171200
+271	1.120600
+272	1.147600
+273	1.128300
+274	1.150300
+275	1.147700
+276	1.150200
+277	1.106900
+278	1.145400
+279	1.117300
+280	1.121900
+281	1.139400
+282	1.109100
+283	1.142100
+284	1.117300
+285	1.104200
+286	1.134200
+287	1.100400
+288	1.092100
+289	1.120500
+290	1.088100
+291	1.128600
+292	1.105400
+293	1.094000
+294	1.108900
+295	1.073100
+296	1.100900
+297	1.092400
+298	1.090300
+299	1.079400
+300	1.090300
+301	1.086100
+302	1.080300
+303	1.075600
+304	1.075900
+305	1.092200
+306	1.070600
+307	1.068800
+308	1.071300
+309	1.073900
+310	1.055400
+311	1.067900
+312	1.041000
+313	1.048600
+314	1.072600
+315	1.058800
+316	1.039000
+317	1.072300
+318	1.056600
+319	1.035100
+320	1.052800
+321	1.046700
+322	1.073400
+323	1.054000
+324	1.077100
+325	1.035200
+326	1.027700
+327	1.060000
+328	1.048900
+329	1.040000
+330	1.026900
+331	1.049300
+332	1.017100
+333	0.996200
+334	1.006400
+335	1.026700
+336	1.073700
+337	1.039200
+338	1.041100
+339	1.054300
+340	1.013500
+341	1.024900
+342	1.003300
+343	0.993400
+344	1.037300
+345	1.009300
+346	1.030400
+347	1.001400
+348	1.012100
+349	1.027300
+350	1.012700
+351	1.013400
+352	1.004400
+353	1.024800
+354	0.990700
+355	1.048600
+356	0.992700
+357	0.991800
+358	0.985300
+359	1.019100
+360	1.007300
+361	1.025500
+362	0.999100
+363	0.997900
+364	1.013300
+365	1.014700
+366	1.037700
+367	0.992400
+368	0.988800
+369	0.993900
+370	0.999500
+371	0.973000
+372	0.972200
+373	0.989200
+374	0.994500
+375	0.995800
+376	0.992000
+377	0.977800
+378	0.975700
+379	0.973700
+380	0.986200
+381	1.008000
+382	0.954100
+383	1.015900
+384	1.008200
+385	0.974700
+386	0.987500
+387	0.993700
+388	0.999200
+389	1.000700
+390	0.978600
+391	0.956200
+392	1.001600
+393	0.971300
+394	0.965800
+395	0.981000
+396	0.965400
+397	0.974200
+398	0.970700
+399	0.953500
+400	0.979700
+401	0.957700
+402	0.984600
+403	1.015600
+404	0.976800
+405	0.969100
+406	0.974200
+407	0.983300
+408	0.974300
+409	0.980600
+410	0.986300
+411	0.968100
+412	0.980500
+413	0.976200
+414	0.987300
+415	0.971600
+416	0.985200
+417	0.989800
+418	0.972000
+419	0.971100
+420	0.988800
+421	0.965600
+422	1.020400
+423	0.978000
+424	0.987800
+425	0.953700
+426	0.990400
+427	0.982900
+428	0.989100
+429	0.983800
+430	0.981500
+431	0.966900
+432	0.967300
+433	0.999400
+434	0.973100
+435	0.980500
+436	0.995500
+437	0.960300
+438	0.953700
+439	0.993600
+440	0.965100
+Dataset({
+    features: ['input_ids', 'attention_mask'],
+    num_rows: 56355
+})
+{'input_ids': [0, 13866, 338, 263, 1139, 393, 16612, 263, 848, 2009, 29892, 3300, 2859, 411, 385, 1881, 393, 16612, 263, 3758, 1591, 29889, 29871, 14350, 263, 3758, 2346, 393, 5663, 17180, 278, 848, 29889, 13, 2277, 29937, 894, 29901, 24948, 592, 825, 278, 11486, 526, 363, 4275, 8314, 29871, 13, 2277, 29937, 10567, 29901, 6137, 29871, 29896, 29899, 29896, 29900, 29900, 29900, 29896, 29947, 29896, 29899, 29896, 756, 4341, 4306, 29914, 357, 768, 706, 313, 726, 511, 1626, 29914, 7042, 12384, 313, 726, 511, 5809, 313, 726, 511, 7583, 269, 1188, 273, 313, 726, 511, 7583, 3652, 313, 726, 511, 3664, 267, 313, 726, 467, 259, 13, 2277, 29937, 673, 29901, 5097, 29871, 8695, 3895, 29871, 29896, 29899, 29896, 29900, 29900, 29900, 29896, 29947, 29896, 29899, 29896, 5754, 9626, 269, 1188, 273, 353, 525, 6156, 2692, 29950, 319, 29965, 10810, 1964, 10764, 29915, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}

sqllama-out/adapter_config.json

@@ -0,0 +1,18 @@
+{
+  "base_model_name_or_path": "decapoda-research/llama-7b-hf",
+  "bias": "none",
+  "enable_lora": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "lora_alpha": 16,
+  "lora_dropout": 0.1,
+  "merge_weights": false,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 4,
+  "target_modules": [
+    "q_proj",
+    "v_proj"
+  ],
+  "task_type": "CASUAL_LM"
+}

sqllama-out/adapter_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7b91522cb7c4937b649e402207dcaf5bc5e454af98e8178db2d821b0b5fe5bdd
+size 8434381