matt-tries-dl
commited on
Commit
•
8965eb9
1
Parent(s):
ce91638
trained v3
Browse files- res3.txt +592 -0
- sqllama-out3/adapter_config.json +18 -0
- sqllama-out3/adapter_model.bin +3 -0
- wikisql.ipynb +46 -1023
res3.txt
ADDED
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1 |
+
/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...
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+
warn(msg)
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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.
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The tokenizer class you load from this checkpoint is 'LLaMATokenizer'.
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The class this function is called from is 'LlamaTokenizer'.
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+
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+
===================================BUG REPORT===================================
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Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues
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================================================================================
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CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so
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CUDA SETUP: Highest compute capability among GPUs detected: 7.5
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CUDA SETUP: Detected CUDA version 113
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CUDA SETUP: Loading binary /home/matt/hf/sqllama-V0/.venv/lib/python3.7/site-packages/bitsandbytes/libbitsandbytes_cuda113.so...
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Output exceeds the size limit. Open the full output data in a text editor
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table: 2-16050349-13
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columns: Rank,Name,Team,Games,Points
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Q: What is Games, when Points is less than 340, and when Rank is greater than 3?
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A: SELECT Games FROM 2-16050349-13 WHERE Points < 340 AND Rank > 3
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END
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table: 1-28962227-1
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columns: Series,Premiere,Finale,Runners-up,Winner
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Q: What is the date of the finale where Holly Bell was runner-up?
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A: SELECT Finale FROM 1-28962227-1 WHERE Runners-up = 'Holly Bell'
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END
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table: 2-10652530-2
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columns: Week,Date,Opponent,Result,Stadium,Record,Attendance
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Q: What was the Browns record after they played the game at the Paul Brown stadium?
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A: SELECT Record FROM 2-10652530-2 WHERE Stadium = 'paul brown stadium'
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END
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table: 2-18379129-4
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columns: play,author,company,base,country
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Q: Who is the author of the Play Electra?
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...
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Q: What is 02-03, when School Year is % Learning In Latvian?
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A: SELECT 02-03 FROM 2-16158579-1 WHERE School year = '% learning in latvian'
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END
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True
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92
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0
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count 56355.000000
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mean 101.219519
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std 21.740325
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min 63.000000
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25% 87.500000
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50% 97.000000
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75% 109.000000
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max 461.000000
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32084
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[500/500 7:38:36, Epoch 1/2]
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Step Training Loss
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1 2.748800
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2 2.723800
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3 2.737600
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4 2.707100
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5 2.692800
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6 2.720700
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7 2.681400
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8 2.736400
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9 2.701800
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10 2.711700
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11 2.685800
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12 2.684300
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13 2.686300
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14 2.698800
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15 2.659300
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16 2.688900
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17 2.661800
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18 2.677700
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19 2.647100
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20 2.679800
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21 2.652000
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22 2.628900
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23 2.656100
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24 2.669100
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25 2.667800
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26 2.636300
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27 2.616800
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28 2.630600
|
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29 2.621000
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30 2.602000
|
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31 2.607900
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32 2.635800
|
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33 2.594600
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34 2.604400
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35 2.618900
|
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36 2.563400
|
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37 2.589200
|
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38 2.552100
|
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39 2.583600
|
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40 2.554500
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41 2.557400
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42 2.536700
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43 2.535000
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44 2.557900
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45 2.530100
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46 2.527900
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47 2.510100
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48 2.539100
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49 2.500100
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50 2.536200
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51 2.487100
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52 2.521700
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53 2.532600
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54 2.494500
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55 2.468900
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56 2.468700
|
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57 2.474300
|
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58 2.480900
|
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59 2.442800
|
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60 2.472800
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61 2.452900
|
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62 2.452000
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63 2.443100
|
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64 2.446700
|
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65 2.415100
|
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66 2.376300
|
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67 2.411500
|
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68 2.403900
|
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69 2.383800
|
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70 2.427800
|
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71 2.419400
|
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72 2.371900
|
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73 2.364400
|
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74 2.360000
|
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75 2.337600
|
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76 2.332800
|
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77 2.315700
|
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+
78 2.344200
|
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+
79 2.331700
|
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+
80 2.303100
|
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+
81 2.324700
|
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82 2.285900
|
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83 2.268000
|
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84 2.260600
|
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+
85 2.286100
|
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+
86 2.233600
|
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87 2.266200
|
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+
88 2.217000
|
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89 2.249300
|
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90 2.239000
|
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+
91 2.221900
|
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+
92 2.223300
|
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+
93 2.179500
|
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+
94 2.204400
|
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+
95 2.193200
|
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+
96 2.163800
|
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+
97 2.158200
|
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+
98 2.127700
|
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+
99 2.141400
|
158 |
+
100 2.121400
|
159 |
+
101 2.115500
|
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+
102 2.125200
|
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+
103 2.140100
|
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+
104 2.118400
|
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105 2.110400
|
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+
106 2.097300
|
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+
107 2.071400
|
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+
108 2.083400
|
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+
109 2.090200
|
168 |
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110 2.078200
|
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+
111 2.061100
|
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+
112 2.047500
|
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+
113 2.006100
|
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+
114 2.023800
|
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+
115 2.014000
|
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+
116 2.008800
|
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+
117 1.988800
|
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+
118 1.984900
|
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119 1.971000
|
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120 1.924100
|
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121 1.953100
|
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122 1.957800
|
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123 1.952500
|
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124 1.890400
|
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125 1.915900
|
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126 1.901100
|
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127 1.879900
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128 1.834100
|
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+
129 1.855900
|
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+
130 1.853800
|
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131 1.869200
|
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132 1.821400
|
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133 1.835100
|
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134 1.817700
|
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135 1.785800
|
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136 1.764000
|
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137 1.796800
|
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138 1.751100
|
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139 1.756500
|
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140 1.789900
|
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141 1.773100
|
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142 1.729200
|
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143 1.700200
|
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144 1.721200
|
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145 1.690600
|
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146 1.687700
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147 1.743500
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148 1.690000
|
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149 1.687200
|
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150 1.663000
|
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151 1.648600
|
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152 1.667100
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153 1.665600
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154 1.647000
|
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155 1.629500
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156 1.620800
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157 1.616400
|
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158 1.658500
|
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159 1.593900
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160 1.604300
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161 1.621200
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162 1.607900
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163 1.591100
|
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164 1.598100
|
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165 1.579700
|
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166 1.545500
|
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167 1.582100
|
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168 1.568300
|
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169 1.557900
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170 1.561300
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171 1.521800
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172 1.542500
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173 1.502300
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174 1.513900
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175 1.501500
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176 1.551200
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177 1.495600
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178 1.504000
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179 1.512500
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180 1.488200
|
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181 1.492200
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240 |
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240 1.270500
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245 1.303500
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246 1.304900
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247 1.273300
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248 1.278300
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249 1.252000
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308 |
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250 1.283400
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251 1.271600
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310 |
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252 1.300300
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311 |
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253 1.265800
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254 1.249200
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313 |
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255 1.252600
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256 1.265500
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259 1.288900
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261 1.243700
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320 |
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262 1.272100
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321 |
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263 1.252000
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322 |
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264 1.264900
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323 |
+
265 1.268800
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324 |
+
266 1.256000
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325 |
+
267 1.230200
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326 |
+
268 1.231700
|
327 |
+
269 1.243400
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270 1.285200
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271 1.225500
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330 |
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272 1.217900
|
331 |
+
273 1.209200
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332 |
+
274 1.224200
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333 |
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275 1.226400
|
334 |
+
276 1.261500
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335 |
+
277 1.223900
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336 |
+
278 1.244000
|
337 |
+
279 1.226600
|
338 |
+
280 1.235000
|
339 |
+
281 1.213400
|
340 |
+
282 1.177600
|
341 |
+
283 1.218100
|
342 |
+
284 1.231900
|
343 |
+
285 1.200900
|
344 |
+
286 1.223400
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345 |
+
287 1.235100
|
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+
288 1.232500
|
347 |
+
289 1.230100
|
348 |
+
290 1.225900
|
349 |
+
291 1.182700
|
350 |
+
292 1.237100
|
351 |
+
293 1.201000
|
352 |
+
294 1.213000
|
353 |
+
295 1.205500
|
354 |
+
296 1.181900
|
355 |
+
297 1.198300
|
356 |
+
298 1.195200
|
357 |
+
299 1.215000
|
358 |
+
300 1.195500
|
359 |
+
301 1.186100
|
360 |
+
302 1.174900
|
361 |
+
303 1.184400
|
362 |
+
304 1.207100
|
363 |
+
305 1.181100
|
364 |
+
306 1.195300
|
365 |
+
307 1.189000
|
366 |
+
308 1.180200
|
367 |
+
309 1.167200
|
368 |
+
310 1.206700
|
369 |
+
311 1.203600
|
370 |
+
312 1.186600
|
371 |
+
313 1.224100
|
372 |
+
314 1.180000
|
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+
315 1.186600
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+
316 1.150700
|
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+
317 1.165700
|
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+
318 1.178100
|
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319 1.148300
|
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+
320 1.153600
|
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+
321 1.189200
|
380 |
+
322 1.182100
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381 |
+
323 1.183800
|
382 |
+
324 1.202900
|
383 |
+
325 1.196600
|
384 |
+
326 1.200800
|
385 |
+
327 1.153100
|
386 |
+
328 1.212400
|
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+
329 1.167300
|
388 |
+
330 1.188300
|
389 |
+
331 1.179300
|
390 |
+
332 1.211400
|
391 |
+
333 1.169900
|
392 |
+
334 1.179300
|
393 |
+
335 1.153300
|
394 |
+
336 1.188900
|
395 |
+
337 1.179200
|
396 |
+
338 1.217300
|
397 |
+
339 1.169700
|
398 |
+
340 1.177700
|
399 |
+
341 1.197300
|
400 |
+
342 1.177800
|
401 |
+
343 1.169700
|
402 |
+
344 1.186800
|
403 |
+
345 1.180000
|
404 |
+
346 1.193400
|
405 |
+
347 1.171900
|
406 |
+
348 1.190000
|
407 |
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349 1.160900
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+
350 1.170800
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+
351 1.166900
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411 |
+
353 1.118200
|
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+
354 1.185900
|
413 |
+
355 1.157800
|
414 |
+
356 1.160200
|
415 |
+
357 1.184200
|
416 |
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358 1.172100
|
417 |
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359 1.143800
|
418 |
+
360 1.178000
|
419 |
+
361 1.157900
|
420 |
+
362 1.151700
|
421 |
+
363 1.196600
|
422 |
+
364 1.181800
|
423 |
+
365 1.195600
|
424 |
+
366 1.165000
|
425 |
+
367 1.157300
|
426 |
+
368 1.165200
|
427 |
+
369 1.167700
|
428 |
+
370 1.184900
|
429 |
+
371 1.168400
|
430 |
+
372 1.150500
|
431 |
+
373 1.152900
|
432 |
+
374 1.158900
|
433 |
+
375 1.143900
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434 |
+
376 1.157200
|
435 |
+
377 1.146800
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436 |
+
378 1.142600
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437 |
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379 1.140600
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438 |
+
380 1.142400
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439 |
+
381 1.114100
|
440 |
+
382 1.169700
|
441 |
+
383 1.142500
|
442 |
+
384 1.176000
|
443 |
+
385 1.160600
|
444 |
+
386 1.164700
|
445 |
+
387 1.124000
|
446 |
+
388 1.134500
|
447 |
+
389 1.185500
|
448 |
+
390 1.154300
|
449 |
+
391 1.125500
|
450 |
+
392 1.174400
|
451 |
+
393 1.132800
|
452 |
+
394 1.145200
|
453 |
+
395 1.129800
|
454 |
+
396 1.140600
|
455 |
+
397 1.126000
|
456 |
+
398 1.182800
|
457 |
+
399 1.127800
|
458 |
+
400 1.155000
|
459 |
+
401 1.134600
|
460 |
+
402 1.155900
|
461 |
+
403 1.150400
|
462 |
+
404 1.141700
|
463 |
+
405 1.131500
|
464 |
+
406 1.169600
|
465 |
+
407 1.170500
|
466 |
+
408 1.129100
|
467 |
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409 1.151700
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468 |
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410 1.168200
|
469 |
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411 1.109100
|
470 |
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412 1.129700
|
471 |
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413 1.143900
|
472 |
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414 1.157300
|
473 |
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415 1.128900
|
474 |
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416 1.171500
|
475 |
+
417 1.141600
|
476 |
+
418 1.157700
|
477 |
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419 1.137000
|
478 |
+
420 1.154000
|
479 |
+
421 1.167300
|
480 |
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422 1.137400
|
481 |
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423 1.121500
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482 |
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424 1.128500
|
483 |
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425 1.130300
|
484 |
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426 1.162100
|
485 |
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427 1.155100
|
486 |
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428 1.145300
|
487 |
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429 1.121000
|
488 |
+
430 1.182200
|
489 |
+
431 1.157000
|
490 |
+
432 1.162300
|
491 |
+
433 1.135200
|
492 |
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434 1.141300
|
493 |
+
435 1.151700
|
494 |
+
436 1.148000
|
495 |
+
437 1.132500
|
496 |
+
438 1.163000
|
497 |
+
439 1.116300
|
498 |
+
440 1.142000
|
499 |
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441 1.091700
|
500 |
+
442 1.141500
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501 |
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443 1.154900
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502 |
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444 1.120400
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503 |
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445 1.173700
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504 |
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446 1.138300
|
505 |
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447 1.135600
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506 |
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448 1.138800
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507 |
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449 1.126800
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508 |
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450 1.129400
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509 |
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451 1.146300
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510 |
+
452 1.104200
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511 |
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453 1.163500
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512 |
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454 1.169300
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513 |
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455 1.147100
|
514 |
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456 1.157100
|
515 |
+
457 1.122100
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516 |
+
458 1.121900
|
517 |
+
459 1.150500
|
518 |
+
460 1.115700
|
519 |
+
461 1.121100
|
520 |
+
462 1.123400
|
521 |
+
463 1.097500
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522 |
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464 1.103800
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523 |
+
465 1.167700
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524 |
+
466 1.130000
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525 |
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467 1.164500
|
526 |
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468 1.127200
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527 |
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469 1.133800
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528 |
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470 1.132700
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529 |
+
471 1.122800
|
530 |
+
472 1.159500
|
531 |
+
473 1.122900
|
532 |
+
474 1.105000
|
533 |
+
475 1.145700
|
534 |
+
476 1.086400
|
535 |
+
477 1.112600
|
536 |
+
478 1.139300
|
537 |
+
479 1.135000
|
538 |
+
480 1.135200
|
539 |
+
481 1.117500
|
540 |
+
482 1.102300
|
541 |
+
483 1.147700
|
542 |
+
484 1.119200
|
543 |
+
485 1.125800
|
544 |
+
486 1.135400
|
545 |
+
487 1.149500
|
546 |
+
488 1.099400
|
547 |
+
489 1.153900
|
548 |
+
490 1.122700
|
549 |
+
491 1.089400
|
550 |
+
492 1.167200
|
551 |
+
493 1.151300
|
552 |
+
494 1.131400
|
553 |
+
495 1.131400
|
554 |
+
496 1.145200
|
555 |
+
497 1.125700
|
556 |
+
498 1.119300
|
557 |
+
499 1.128600
|
558 |
+
500 1.121000
|
559 |
+
/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)
|
560 |
+
"You have modified the pretrained model configuration to control generation. This is a"
|
561 |
+
/home/matt/hf/sqllama-V0/.venv/lib/python3.7/site-packages/torch/utils/checkpoint.py:31: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
|
562 |
+
warnings.warn("None of the inputs have requires_grad=True. Gradients will be None")
|
563 |
+
Output exceeds the size limit. Open the full output data in a text editor
|
564 |
+
from model
|
565 |
+
<unk>table: 2-11561331-17
|
566 |
+
columns: Name,Actual version,System,Platform,License
|
567 |
+
Q: Which System's Name is Steem, and has a Freeware License?
|
568 |
+
A: SELECT Name FROM 2-11561331-17 WHERE License = 'Freeware' AND System = 'Steem'
|
569 |
+
END
|
570 |
+
\end{code}
|
571 |
+
|
572 |
+
|
573 |
+
|
574 |
+
expected answer
|
575 |
+
SELECT System FROM 2-11561331-17 WHERE License = 'freeware' AND Name = 'steem'
|
576 |
+
END
|
577 |
+
|
578 |
+
from model
|
579 |
+
<unk>table: 1-18847736-2
|
580 |
+
columns: Game,Date,Opponent,Result,Dolphins points,Opponents,Record,Attendance
|
581 |
+
Q: What is the date when the opponent is the New England Patriots?
|
582 |
+
A: SELECT Date FROM 1-18847736-2 WHERE Opponent = 'New England Patriots'
|
583 |
+
END
|
584 |
+
\end
|
585 |
+
|
586 |
+
expected answer
|
587 |
+
SELECT Date FROM 1-18847736-2 WHERE Opponent = 'New England Patriots'
|
588 |
+
END
|
589 |
+
...
|
590 |
+
expected answer
|
591 |
+
SELECT Manufacturer FROM 1-17801022-1 WHERE Date = 'November 2'
|
592 |
+
END
|
sqllama-out3/adapter_config.json
ADDED
@@ -0,0 +1,18 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"base_model_name_or_path": "decapoda-research/llama-7b-hf",
|
3 |
+
"bias": "none",
|
4 |
+
"enable_lora": null,
|
5 |
+
"fan_in_fan_out": false,
|
6 |
+
"inference_mode": true,
|
7 |
+
"lora_alpha": 16,
|
8 |
+
"lora_dropout": 0.1,
|
9 |
+
"merge_weights": false,
|
10 |
+
"modules_to_save": null,
|
11 |
+
"peft_type": "LORA",
|
12 |
+
"r": 4,
|
13 |
+
"target_modules": [
|
14 |
+
"q_proj",
|
15 |
+
"v_proj"
|
16 |
+
],
|
17 |
+
"task_type": "CASUAL_LM"
|
18 |
+
}
|
sqllama-out3/adapter_model.bin
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:d12d7102022c5ae89b006db222885aa4acde5b853063bf288c24ebc430f26bb7
|
3 |
+
size 8434381
|
wikisql.ipynb
CHANGED
@@ -55,7 +55,7 @@
|
|
55 |
{
|
56 |
"data": {
|
57 |
"application/vnd.jupyter.widget-view+json": {
|
58 |
-
"model_id": "
|
59 |
"version_major": 2,
|
60 |
"version_minor": 0
|
61 |
},
|
@@ -96,38 +96,38 @@
|
|
96 |
"output_type": "stream",
|
97 |
"text": [
|
98 |
"\n",
|
99 |
-
"table: 2-
|
100 |
-
"columns:
|
101 |
-
"Q: What
|
102 |
-
"A: SELECT
|
103 |
"END\n",
|
104 |
"\n",
|
105 |
"\n",
|
106 |
-
"table:
|
107 |
-
"columns:
|
108 |
-
"Q:
|
109 |
-
"A: SELECT
|
110 |
"END\n",
|
111 |
"\n",
|
112 |
"\n",
|
113 |
-
"table:
|
114 |
-
"columns:
|
115 |
-
"Q:
|
116 |
-
"A: SELECT
|
117 |
"END\n",
|
118 |
"\n",
|
119 |
"\n",
|
120 |
-
"table: 2-
|
121 |
-
"columns:
|
122 |
-
"Q: What is the number
|
123 |
-
"A: SELECT
|
124 |
"END\n",
|
125 |
"\n",
|
126 |
"\n",
|
127 |
-
"table:
|
128 |
-
"columns:
|
129 |
-
"Q: What
|
130 |
-
"A: SELECT
|
131 |
"END\n",
|
132 |
"\n"
|
133 |
]
|
@@ -278,7 +278,7 @@
|
|
278 |
{
|
279 |
"data": {
|
280 |
"application/vnd.jupyter.widget-view+json": {
|
281 |
-
"model_id": "
|
282 |
"version_major": 2,
|
283 |
"version_minor": 0
|
284 |
},
|
@@ -320,12 +320,11 @@
|
|
320 |
"LORA_R = 4\n",
|
321 |
"LORA_ALPHA = 16\n",
|
322 |
"LORA_DROPOUT = .1\n",
|
323 |
-
"CUTOFF_LEN = 256\n",
|
324 |
"BATCH = 128\n",
|
325 |
"MICRO_BATCH = 4\n",
|
326 |
"N_GAS = BATCH//MICRO_BATCH\n",
|
327 |
-
"EPOCHS =
|
328 |
-
"LR = 1e-
|
329 |
"\n",
|
330 |
"lora_cfg = LoraConfig(\n",
|
331 |
" r = LORA_R,\n",
|
@@ -345,7 +344,7 @@
|
|
345 |
" learning_rate=LR,\n",
|
346 |
" fp16=True,\n",
|
347 |
" logging_steps=1,\n",
|
348 |
-
" output_dir='sqllama-
|
349 |
" save_total_limit=3,\n",
|
350 |
" remove_unused_columns=False\n",
|
351 |
")\n"
|
@@ -362,8 +361,8 @@
|
|
362 |
"\n",
|
363 |
" <div>\n",
|
364 |
" \n",
|
365 |
-
" <progress value='
|
366 |
-
" [
|
367 |
" </div>\n",
|
368 |
" <table border=\"1\" class=\"dataframe\">\n",
|
369 |
" <thead>\n",
|
@@ -379,999 +378,7 @@
|
|
379 |
" </tr>\n",
|
380 |
" <tr>\n",
|
381 |
" <td>2</td>\n",
|
382 |
-
" <td>2.
|
383 |
-
" </tr>\n",
|
384 |
-
" <tr>\n",
|
385 |
-
" <td>3</td>\n",
|
386 |
-
" <td>2.670200</td>\n",
|
387 |
-
" </tr>\n",
|
388 |
-
" <tr>\n",
|
389 |
-
" <td>4</td>\n",
|
390 |
-
" <td>2.600500</td>\n",
|
391 |
-
" </tr>\n",
|
392 |
-
" <tr>\n",
|
393 |
-
" <td>5</td>\n",
|
394 |
-
" <td>2.560100</td>\n",
|
395 |
-
" </tr>\n",
|
396 |
-
" <tr>\n",
|
397 |
-
" <td>6</td>\n",
|
398 |
-
" <td>2.556800</td>\n",
|
399 |
-
" </tr>\n",
|
400 |
-
" <tr>\n",
|
401 |
-
" <td>7</td>\n",
|
402 |
-
" <td>2.498100</td>\n",
|
403 |
-
" </tr>\n",
|
404 |
-
" <tr>\n",
|
405 |
-
" <td>8</td>\n",
|
406 |
-
" <td>2.515400</td>\n",
|
407 |
-
" </tr>\n",
|
408 |
-
" <tr>\n",
|
409 |
-
" <td>9</td>\n",
|
410 |
-
" <td>2.436100</td>\n",
|
411 |
-
" </tr>\n",
|
412 |
-
" <tr>\n",
|
413 |
-
" <td>10</td>\n",
|
414 |
-
" <td>2.411700</td>\n",
|
415 |
-
" </tr>\n",
|
416 |
-
" <tr>\n",
|
417 |
-
" <td>11</td>\n",
|
418 |
-
" <td>2.346400</td>\n",
|
419 |
-
" </tr>\n",
|
420 |
-
" <tr>\n",
|
421 |
-
" <td>12</td>\n",
|
422 |
-
" <td>2.276300</td>\n",
|
423 |
-
" </tr>\n",
|
424 |
-
" <tr>\n",
|
425 |
-
" <td>13</td>\n",
|
426 |
-
" <td>2.238000</td>\n",
|
427 |
-
" </tr>\n",
|
428 |
-
" <tr>\n",
|
429 |
-
" <td>14</td>\n",
|
430 |
-
" <td>2.189100</td>\n",
|
431 |
-
" </tr>\n",
|
432 |
-
" <tr>\n",
|
433 |
-
" <td>15</td>\n",
|
434 |
-
" <td>2.109200</td>\n",
|
435 |
-
" </tr>\n",
|
436 |
-
" <tr>\n",
|
437 |
-
" <td>16</td>\n",
|
438 |
-
" <td>2.058000</td>\n",
|
439 |
-
" </tr>\n",
|
440 |
-
" <tr>\n",
|
441 |
-
" <td>17</td>\n",
|
442 |
-
" <td>1.983900</td>\n",
|
443 |
-
" </tr>\n",
|
444 |
-
" <tr>\n",
|
445 |
-
" <td>18</td>\n",
|
446 |
-
" <td>1.928600</td>\n",
|
447 |
-
" </tr>\n",
|
448 |
-
" <tr>\n",
|
449 |
-
" <td>19</td>\n",
|
450 |
-
" <td>1.824100</td>\n",
|
451 |
-
" </tr>\n",
|
452 |
-
" <tr>\n",
|
453 |
-
" <td>20</td>\n",
|
454 |
-
" <td>1.794700</td>\n",
|
455 |
-
" </tr>\n",
|
456 |
-
" <tr>\n",
|
457 |
-
" <td>21</td>\n",
|
458 |
-
" <td>1.681200</td>\n",
|
459 |
-
" </tr>\n",
|
460 |
-
" <tr>\n",
|
461 |
-
" <td>22</td>\n",
|
462 |
-
" <td>1.598900</td>\n",
|
463 |
-
" </tr>\n",
|
464 |
-
" <tr>\n",
|
465 |
-
" <td>23</td>\n",
|
466 |
-
" <td>1.562000</td>\n",
|
467 |
-
" </tr>\n",
|
468 |
-
" <tr>\n",
|
469 |
-
" <td>24</td>\n",
|
470 |
-
" <td>1.527200</td>\n",
|
471 |
-
" </tr>\n",
|
472 |
-
" <tr>\n",
|
473 |
-
" <td>25</td>\n",
|
474 |
-
" <td>1.518700</td>\n",
|
475 |
-
" </tr>\n",
|
476 |
-
" <tr>\n",
|
477 |
-
" <td>26</td>\n",
|
478 |
-
" <td>1.493100</td>\n",
|
479 |
-
" </tr>\n",
|
480 |
-
" <tr>\n",
|
481 |
-
" <td>27</td>\n",
|
482 |
-
" <td>1.500500</td>\n",
|
483 |
-
" </tr>\n",
|
484 |
-
" <tr>\n",
|
485 |
-
" <td>28</td>\n",
|
486 |
-
" <td>1.464000</td>\n",
|
487 |
-
" </tr>\n",
|
488 |
-
" <tr>\n",
|
489 |
-
" <td>29</td>\n",
|
490 |
-
" <td>1.386900</td>\n",
|
491 |
-
" </tr>\n",
|
492 |
-
" <tr>\n",
|
493 |
-
" <td>30</td>\n",
|
494 |
-
" <td>1.373400</td>\n",
|
495 |
-
" </tr>\n",
|
496 |
-
" <tr>\n",
|
497 |
-
" <td>31</td>\n",
|
498 |
-
" <td>1.362200</td>\n",
|
499 |
-
" </tr>\n",
|
500 |
-
" <tr>\n",
|
501 |
-
" <td>32</td>\n",
|
502 |
-
" <td>1.360800</td>\n",
|
503 |
-
" </tr>\n",
|
504 |
-
" <tr>\n",
|
505 |
-
" <td>33</td>\n",
|
506 |
-
" <td>1.321000</td>\n",
|
507 |
-
" </tr>\n",
|
508 |
-
" <tr>\n",
|
509 |
-
" <td>34</td>\n",
|
510 |
-
" <td>1.310500</td>\n",
|
511 |
-
" </tr>\n",
|
512 |
-
" <tr>\n",
|
513 |
-
" <td>35</td>\n",
|
514 |
-
" <td>1.302600</td>\n",
|
515 |
-
" </tr>\n",
|
516 |
-
" <tr>\n",
|
517 |
-
" <td>36</td>\n",
|
518 |
-
" <td>1.256100</td>\n",
|
519 |
-
" </tr>\n",
|
520 |
-
" <tr>\n",
|
521 |
-
" <td>37</td>\n",
|
522 |
-
" <td>1.252500</td>\n",
|
523 |
-
" </tr>\n",
|
524 |
-
" <tr>\n",
|
525 |
-
" <td>38</td>\n",
|
526 |
-
" <td>1.202300</td>\n",
|
527 |
-
" </tr>\n",
|
528 |
-
" <tr>\n",
|
529 |
-
" <td>39</td>\n",
|
530 |
-
" <td>1.249100</td>\n",
|
531 |
-
" </tr>\n",
|
532 |
-
" <tr>\n",
|
533 |
-
" <td>40</td>\n",
|
534 |
-
" <td>1.188600</td>\n",
|
535 |
-
" </tr>\n",
|
536 |
-
" <tr>\n",
|
537 |
-
" <td>41</td>\n",
|
538 |
-
" <td>1.203200</td>\n",
|
539 |
-
" </tr>\n",
|
540 |
-
" <tr>\n",
|
541 |
-
" <td>42</td>\n",
|
542 |
-
" <td>1.150000</td>\n",
|
543 |
-
" </tr>\n",
|
544 |
-
" <tr>\n",
|
545 |
-
" <td>43</td>\n",
|
546 |
-
" <td>1.182000</td>\n",
|
547 |
-
" </tr>\n",
|
548 |
-
" <tr>\n",
|
549 |
-
" <td>44</td>\n",
|
550 |
-
" <td>1.192300</td>\n",
|
551 |
-
" </tr>\n",
|
552 |
-
" <tr>\n",
|
553 |
-
" <td>45</td>\n",
|
554 |
-
" <td>1.133100</td>\n",
|
555 |
-
" </tr>\n",
|
556 |
-
" <tr>\n",
|
557 |
-
" <td>46</td>\n",
|
558 |
-
" <td>1.119600</td>\n",
|
559 |
-
" </tr>\n",
|
560 |
-
" <tr>\n",
|
561 |
-
" <td>47</td>\n",
|
562 |
-
" <td>1.097000</td>\n",
|
563 |
-
" </tr>\n",
|
564 |
-
" <tr>\n",
|
565 |
-
" <td>48</td>\n",
|
566 |
-
" <td>1.142100</td>\n",
|
567 |
-
" </tr>\n",
|
568 |
-
" <tr>\n",
|
569 |
-
" <td>49</td>\n",
|
570 |
-
" <td>1.117200</td>\n",
|
571 |
-
" </tr>\n",
|
572 |
-
" <tr>\n",
|
573 |
-
" <td>50</td>\n",
|
574 |
-
" <td>1.129200</td>\n",
|
575 |
-
" </tr>\n",
|
576 |
-
" <tr>\n",
|
577 |
-
" <td>51</td>\n",
|
578 |
-
" <td>1.087300</td>\n",
|
579 |
-
" </tr>\n",
|
580 |
-
" <tr>\n",
|
581 |
-
" <td>52</td>\n",
|
582 |
-
" <td>1.098700</td>\n",
|
583 |
-
" </tr>\n",
|
584 |
-
" <tr>\n",
|
585 |
-
" <td>53</td>\n",
|
586 |
-
" <td>1.135400</td>\n",
|
587 |
-
" </tr>\n",
|
588 |
-
" <tr>\n",
|
589 |
-
" <td>54</td>\n",
|
590 |
-
" <td>1.071700</td>\n",
|
591 |
-
" </tr>\n",
|
592 |
-
" <tr>\n",
|
593 |
-
" <td>55</td>\n",
|
594 |
-
" <td>1.087300</td>\n",
|
595 |
-
" </tr>\n",
|
596 |
-
" <tr>\n",
|
597 |
-
" <td>56</td>\n",
|
598 |
-
" <td>1.051400</td>\n",
|
599 |
-
" </tr>\n",
|
600 |
-
" <tr>\n",
|
601 |
-
" <td>57</td>\n",
|
602 |
-
" <td>1.068300</td>\n",
|
603 |
-
" </tr>\n",
|
604 |
-
" <tr>\n",
|
605 |
-
" <td>58</td>\n",
|
606 |
-
" <td>1.092500</td>\n",
|
607 |
-
" </tr>\n",
|
608 |
-
" <tr>\n",
|
609 |
-
" <td>59</td>\n",
|
610 |
-
" <td>1.068600</td>\n",
|
611 |
-
" </tr>\n",
|
612 |
-
" <tr>\n",
|
613 |
-
" <td>60</td>\n",
|
614 |
-
" <td>1.072800</td>\n",
|
615 |
-
" </tr>\n",
|
616 |
-
" <tr>\n",
|
617 |
-
" <td>61</td>\n",
|
618 |
-
" <td>1.074000</td>\n",
|
619 |
-
" </tr>\n",
|
620 |
-
" <tr>\n",
|
621 |
-
" <td>62</td>\n",
|
622 |
-
" <td>1.060400</td>\n",
|
623 |
-
" </tr>\n",
|
624 |
-
" <tr>\n",
|
625 |
-
" <td>63</td>\n",
|
626 |
-
" <td>1.065800</td>\n",
|
627 |
-
" </tr>\n",
|
628 |
-
" <tr>\n",
|
629 |
-
" <td>64</td>\n",
|
630 |
-
" <td>1.075900</td>\n",
|
631 |
-
" </tr>\n",
|
632 |
-
" <tr>\n",
|
633 |
-
" <td>65</td>\n",
|
634 |
-
" <td>1.059500</td>\n",
|
635 |
-
" </tr>\n",
|
636 |
-
" <tr>\n",
|
637 |
-
" <td>66</td>\n",
|
638 |
-
" <td>1.039600</td>\n",
|
639 |
-
" </tr>\n",
|
640 |
-
" <tr>\n",
|
641 |
-
" <td>67</td>\n",
|
642 |
-
" <td>1.051400</td>\n",
|
643 |
-
" </tr>\n",
|
644 |
-
" <tr>\n",
|
645 |
-
" <td>68</td>\n",
|
646 |
-
" <td>1.049500</td>\n",
|
647 |
-
" </tr>\n",
|
648 |
-
" <tr>\n",
|
649 |
-
" <td>69</td>\n",
|
650 |
-
" <td>1.023800</td>\n",
|
651 |
-
" </tr>\n",
|
652 |
-
" <tr>\n",
|
653 |
-
" <td>70</td>\n",
|
654 |
-
" <td>1.071900</td>\n",
|
655 |
-
" </tr>\n",
|
656 |
-
" <tr>\n",
|
657 |
-
" <td>71</td>\n",
|
658 |
-
" <td>1.051000</td>\n",
|
659 |
-
" </tr>\n",
|
660 |
-
" <tr>\n",
|
661 |
-
" <td>72</td>\n",
|
662 |
-
" <td>1.034700</td>\n",
|
663 |
-
" </tr>\n",
|
664 |
-
" <tr>\n",
|
665 |
-
" <td>73</td>\n",
|
666 |
-
" <td>1.041600</td>\n",
|
667 |
-
" </tr>\n",
|
668 |
-
" <tr>\n",
|
669 |
-
" <td>74</td>\n",
|
670 |
-
" <td>1.030900</td>\n",
|
671 |
-
" </tr>\n",
|
672 |
-
" <tr>\n",
|
673 |
-
" <td>75</td>\n",
|
674 |
-
" <td>1.010800</td>\n",
|
675 |
-
" </tr>\n",
|
676 |
-
" <tr>\n",
|
677 |
-
" <td>76</td>\n",
|
678 |
-
" <td>1.019800</td>\n",
|
679 |
-
" </tr>\n",
|
680 |
-
" <tr>\n",
|
681 |
-
" <td>77</td>\n",
|
682 |
-
" <td>1.005000</td>\n",
|
683 |
-
" </tr>\n",
|
684 |
-
" <tr>\n",
|
685 |
-
" <td>78</td>\n",
|
686 |
-
" <td>1.043800</td>\n",
|
687 |
-
" </tr>\n",
|
688 |
-
" <tr>\n",
|
689 |
-
" <td>79</td>\n",
|
690 |
-
" <td>1.009200</td>\n",
|
691 |
-
" </tr>\n",
|
692 |
-
" <tr>\n",
|
693 |
-
" <td>80</td>\n",
|
694 |
-
" <td>1.017100</td>\n",
|
695 |
-
" </tr>\n",
|
696 |
-
" <tr>\n",
|
697 |
-
" <td>81</td>\n",
|
698 |
-
" <td>1.044600</td>\n",
|
699 |
-
" </tr>\n",
|
700 |
-
" <tr>\n",
|
701 |
-
" <td>82</td>\n",
|
702 |
-
" <td>1.022600</td>\n",
|
703 |
-
" </tr>\n",
|
704 |
-
" <tr>\n",
|
705 |
-
" <td>83</td>\n",
|
706 |
-
" <td>1.011400</td>\n",
|
707 |
-
" </tr>\n",
|
708 |
-
" <tr>\n",
|
709 |
-
" <td>84</td>\n",
|
710 |
-
" <td>0.996600</td>\n",
|
711 |
-
" </tr>\n",
|
712 |
-
" <tr>\n",
|
713 |
-
" <td>85</td>\n",
|
714 |
-
" <td>1.029900</td>\n",
|
715 |
-
" </tr>\n",
|
716 |
-
" <tr>\n",
|
717 |
-
" <td>86</td>\n",
|
718 |
-
" <td>0.988200</td>\n",
|
719 |
-
" </tr>\n",
|
720 |
-
" <tr>\n",
|
721 |
-
" <td>87</td>\n",
|
722 |
-
" <td>1.005600</td>\n",
|
723 |
-
" </tr>\n",
|
724 |
-
" <tr>\n",
|
725 |
-
" <td>88</td>\n",
|
726 |
-
" <td>0.986600</td>\n",
|
727 |
-
" </tr>\n",
|
728 |
-
" <tr>\n",
|
729 |
-
" <td>89</td>\n",
|
730 |
-
" <td>1.025300</td>\n",
|
731 |
-
" </tr>\n",
|
732 |
-
" <tr>\n",
|
733 |
-
" <td>90</td>\n",
|
734 |
-
" <td>1.012500</td>\n",
|
735 |
-
" </tr>\n",
|
736 |
-
" <tr>\n",
|
737 |
-
" <td>91</td>\n",
|
738 |
-
" <td>0.988100</td>\n",
|
739 |
-
" </tr>\n",
|
740 |
-
" <tr>\n",
|
741 |
-
" <td>92</td>\n",
|
742 |
-
" <td>1.001800</td>\n",
|
743 |
-
" </tr>\n",
|
744 |
-
" <tr>\n",
|
745 |
-
" <td>93</td>\n",
|
746 |
-
" <td>0.987100</td>\n",
|
747 |
-
" </tr>\n",
|
748 |
-
" <tr>\n",
|
749 |
-
" <td>94</td>\n",
|
750 |
-
" <td>1.017600</td>\n",
|
751 |
-
" </tr>\n",
|
752 |
-
" <tr>\n",
|
753 |
-
" <td>95</td>\n",
|
754 |
-
" <td>0.998500</td>\n",
|
755 |
-
" </tr>\n",
|
756 |
-
" <tr>\n",
|
757 |
-
" <td>96</td>\n",
|
758 |
-
" <td>0.966600</td>\n",
|
759 |
-
" </tr>\n",
|
760 |
-
" <tr>\n",
|
761 |
-
" <td>97</td>\n",
|
762 |
-
" <td>0.983700</td>\n",
|
763 |
-
" </tr>\n",
|
764 |
-
" <tr>\n",
|
765 |
-
" <td>98</td>\n",
|
766 |
-
" <td>0.961800</td>\n",
|
767 |
-
" </tr>\n",
|
768 |
-
" <tr>\n",
|
769 |
-
" <td>99</td>\n",
|
770 |
-
" <td>0.969000</td>\n",
|
771 |
-
" </tr>\n",
|
772 |
-
" <tr>\n",
|
773 |
-
" <td>100</td>\n",
|
774 |
-
" <td>0.989200</td>\n",
|
775 |
-
" </tr>\n",
|
776 |
-
" <tr>\n",
|
777 |
-
" <td>101</td>\n",
|
778 |
-
" <td>0.956400</td>\n",
|
779 |
-
" </tr>\n",
|
780 |
-
" <tr>\n",
|
781 |
-
" <td>102</td>\n",
|
782 |
-
" <td>0.976000</td>\n",
|
783 |
-
" </tr>\n",
|
784 |
-
" <tr>\n",
|
785 |
-
" <td>103</td>\n",
|
786 |
-
" <td>1.000100</td>\n",
|
787 |
-
" </tr>\n",
|
788 |
-
" <tr>\n",
|
789 |
-
" <td>104</td>\n",
|
790 |
-
" <td>1.001500</td>\n",
|
791 |
-
" </tr>\n",
|
792 |
-
" <tr>\n",
|
793 |
-
" <td>105</td>\n",
|
794 |
-
" <td>0.995900</td>\n",
|
795 |
-
" </tr>\n",
|
796 |
-
" <tr>\n",
|
797 |
-
" <td>106</td>\n",
|
798 |
-
" <td>0.989700</td>\n",
|
799 |
-
" </tr>\n",
|
800 |
-
" <tr>\n",
|
801 |
-
" <td>107</td>\n",
|
802 |
-
" <td>0.965700</td>\n",
|
803 |
-
" </tr>\n",
|
804 |
-
" <tr>\n",
|
805 |
-
" <td>108</td>\n",
|
806 |
-
" <td>0.968400</td>\n",
|
807 |
-
" </tr>\n",
|
808 |
-
" <tr>\n",
|
809 |
-
" <td>109</td>\n",
|
810 |
-
" <td>1.019600</td>\n",
|
811 |
-
" </tr>\n",
|
812 |
-
" <tr>\n",
|
813 |
-
" <td>110</td>\n",
|
814 |
-
" <td>1.000100</td>\n",
|
815 |
-
" </tr>\n",
|
816 |
-
" <tr>\n",
|
817 |
-
" <td>111</td>\n",
|
818 |
-
" <td>0.978500</td>\n",
|
819 |
-
" </tr>\n",
|
820 |
-
" <tr>\n",
|
821 |
-
" <td>112</td>\n",
|
822 |
-
" <td>0.978900</td>\n",
|
823 |
-
" </tr>\n",
|
824 |
-
" <tr>\n",
|
825 |
-
" <td>113</td>\n",
|
826 |
-
" <td>0.952600</td>\n",
|
827 |
-
" </tr>\n",
|
828 |
-
" <tr>\n",
|
829 |
-
" <td>114</td>\n",
|
830 |
-
" <td>0.975400</td>\n",
|
831 |
-
" </tr>\n",
|
832 |
-
" <tr>\n",
|
833 |
-
" <td>115</td>\n",
|
834 |
-
" <td>0.989400</td>\n",
|
835 |
-
" </tr>\n",
|
836 |
-
" <tr>\n",
|
837 |
-
" <td>116</td>\n",
|
838 |
-
" <td>0.968500</td>\n",
|
839 |
-
" </tr>\n",
|
840 |
-
" <tr>\n",
|
841 |
-
" <td>117</td>\n",
|
842 |
-
" <td>0.960100</td>\n",
|
843 |
-
" </tr>\n",
|
844 |
-
" <tr>\n",
|
845 |
-
" <td>118</td>\n",
|
846 |
-
" <td>0.979100</td>\n",
|
847 |
-
" </tr>\n",
|
848 |
-
" <tr>\n",
|
849 |
-
" <td>119</td>\n",
|
850 |
-
" <td>0.955100</td>\n",
|
851 |
-
" </tr>\n",
|
852 |
-
" <tr>\n",
|
853 |
-
" <td>120</td>\n",
|
854 |
-
" <td>0.934800</td>\n",
|
855 |
-
" </tr>\n",
|
856 |
-
" <tr>\n",
|
857 |
-
" <td>121</td>\n",
|
858 |
-
" <td>0.943600</td>\n",
|
859 |
-
" </tr>\n",
|
860 |
-
" <tr>\n",
|
861 |
-
" <td>122</td>\n",
|
862 |
-
" <td>0.976700</td>\n",
|
863 |
-
" </tr>\n",
|
864 |
-
" <tr>\n",
|
865 |
-
" <td>123</td>\n",
|
866 |
-
" <td>0.998700</td>\n",
|
867 |
-
" </tr>\n",
|
868 |
-
" <tr>\n",
|
869 |
-
" <td>124</td>\n",
|
870 |
-
" <td>0.930500</td>\n",
|
871 |
-
" </tr>\n",
|
872 |
-
" <tr>\n",
|
873 |
-
" <td>125</td>\n",
|
874 |
-
" <td>0.953500</td>\n",
|
875 |
-
" </tr>\n",
|
876 |
-
" <tr>\n",
|
877 |
-
" <td>126</td>\n",
|
878 |
-
" <td>0.978000</td>\n",
|
879 |
-
" </tr>\n",
|
880 |
-
" <tr>\n",
|
881 |
-
" <td>127</td>\n",
|
882 |
-
" <td>0.967300</td>\n",
|
883 |
-
" </tr>\n",
|
884 |
-
" <tr>\n",
|
885 |
-
" <td>128</td>\n",
|
886 |
-
" <td>0.929400</td>\n",
|
887 |
-
" </tr>\n",
|
888 |
-
" <tr>\n",
|
889 |
-
" <td>129</td>\n",
|
890 |
-
" <td>0.963100</td>\n",
|
891 |
-
" </tr>\n",
|
892 |
-
" <tr>\n",
|
893 |
-
" <td>130</td>\n",
|
894 |
-
" <td>0.961500</td>\n",
|
895 |
-
" </tr>\n",
|
896 |
-
" <tr>\n",
|
897 |
-
" <td>131</td>\n",
|
898 |
-
" <td>0.978500</td>\n",
|
899 |
-
" </tr>\n",
|
900 |
-
" <tr>\n",
|
901 |
-
" <td>132</td>\n",
|
902 |
-
" <td>0.937200</td>\n",
|
903 |
-
" </tr>\n",
|
904 |
-
" <tr>\n",
|
905 |
-
" <td>133</td>\n",
|
906 |
-
" <td>0.953400</td>\n",
|
907 |
-
" </tr>\n",
|
908 |
-
" <tr>\n",
|
909 |
-
" <td>134</td>\n",
|
910 |
-
" <td>0.962000</td>\n",
|
911 |
-
" </tr>\n",
|
912 |
-
" <tr>\n",
|
913 |
-
" <td>135</td>\n",
|
914 |
-
" <td>0.950700</td>\n",
|
915 |
-
" </tr>\n",
|
916 |
-
" <tr>\n",
|
917 |
-
" <td>136</td>\n",
|
918 |
-
" <td>0.925100</td>\n",
|
919 |
-
" </tr>\n",
|
920 |
-
" <tr>\n",
|
921 |
-
" <td>137</td>\n",
|
922 |
-
" <td>0.958800</td>\n",
|
923 |
-
" </tr>\n",
|
924 |
-
" <tr>\n",
|
925 |
-
" <td>138</td>\n",
|
926 |
-
" <td>0.926200</td>\n",
|
927 |
-
" </tr>\n",
|
928 |
-
" <tr>\n",
|
929 |
-
" <td>139</td>\n",
|
930 |
-
" <td>0.930600</td>\n",
|
931 |
-
" </tr>\n",
|
932 |
-
" <tr>\n",
|
933 |
-
" <td>140</td>\n",
|
934 |
-
" <td>0.968900</td>\n",
|
935 |
-
" </tr>\n",
|
936 |
-
" <tr>\n",
|
937 |
-
" <td>141</td>\n",
|
938 |
-
" <td>0.970400</td>\n",
|
939 |
-
" </tr>\n",
|
940 |
-
" <tr>\n",
|
941 |
-
" <td>142</td>\n",
|
942 |
-
" <td>0.927100</td>\n",
|
943 |
-
" </tr>\n",
|
944 |
-
" <tr>\n",
|
945 |
-
" <td>143</td>\n",
|
946 |
-
" <td>0.911800</td>\n",
|
947 |
-
" </tr>\n",
|
948 |
-
" <tr>\n",
|
949 |
-
" <td>144</td>\n",
|
950 |
-
" <td>0.953200</td>\n",
|
951 |
-
" </tr>\n",
|
952 |
-
" <tr>\n",
|
953 |
-
" <td>145</td>\n",
|
954 |
-
" <td>0.907100</td>\n",
|
955 |
-
" </tr>\n",
|
956 |
-
" <tr>\n",
|
957 |
-
" <td>146</td>\n",
|
958 |
-
" <td>0.935900</td>\n",
|
959 |
-
" </tr>\n",
|
960 |
-
" <tr>\n",
|
961 |
-
" <td>147</td>\n",
|
962 |
-
" <td>0.970600</td>\n",
|
963 |
-
" </tr>\n",
|
964 |
-
" <tr>\n",
|
965 |
-
" <td>148</td>\n",
|
966 |
-
" <td>0.920400</td>\n",
|
967 |
-
" </tr>\n",
|
968 |
-
" <tr>\n",
|
969 |
-
" <td>149</td>\n",
|
970 |
-
" <td>0.930200</td>\n",
|
971 |
-
" </tr>\n",
|
972 |
-
" <tr>\n",
|
973 |
-
" <td>150</td>\n",
|
974 |
-
" <td>0.926700</td>\n",
|
975 |
-
" </tr>\n",
|
976 |
-
" <tr>\n",
|
977 |
-
" <td>151</td>\n",
|
978 |
-
" <td>0.913400</td>\n",
|
979 |
-
" </tr>\n",
|
980 |
-
" <tr>\n",
|
981 |
-
" <td>152</td>\n",
|
982 |
-
" <td>0.926800</td>\n",
|
983 |
-
" </tr>\n",
|
984 |
-
" <tr>\n",
|
985 |
-
" <td>153</td>\n",
|
986 |
-
" <td>0.967200</td>\n",
|
987 |
-
" </tr>\n",
|
988 |
-
" <tr>\n",
|
989 |
-
" <td>154</td>\n",
|
990 |
-
" <td>0.939500</td>\n",
|
991 |
-
" </tr>\n",
|
992 |
-
" <tr>\n",
|
993 |
-
" <td>155</td>\n",
|
994 |
-
" <td>0.910600</td>\n",
|
995 |
-
" </tr>\n",
|
996 |
-
" <tr>\n",
|
997 |
-
" <td>156</td>\n",
|
998 |
-
" <td>0.926400</td>\n",
|
999 |
-
" </tr>\n",
|
1000 |
-
" <tr>\n",
|
1001 |
-
" <td>157</td>\n",
|
1002 |
-
" <td>0.935400</td>\n",
|
1003 |
-
" </tr>\n",
|
1004 |
-
" <tr>\n",
|
1005 |
-
" <td>158</td>\n",
|
1006 |
-
" <td>0.967700</td>\n",
|
1007 |
-
" </tr>\n",
|
1008 |
-
" <tr>\n",
|
1009 |
-
" <td>159</td>\n",
|
1010 |
-
" <td>0.899000</td>\n",
|
1011 |
-
" </tr>\n",
|
1012 |
-
" <tr>\n",
|
1013 |
-
" <td>160</td>\n",
|
1014 |
-
" <td>0.916600</td>\n",
|
1015 |
-
" </tr>\n",
|
1016 |
-
" <tr>\n",
|
1017 |
-
" <td>161</td>\n",
|
1018 |
-
" <td>0.961600</td>\n",
|
1019 |
-
" </tr>\n",
|
1020 |
-
" <tr>\n",
|
1021 |
-
" <td>162</td>\n",
|
1022 |
-
" <td>0.898200</td>\n",
|
1023 |
-
" </tr>\n",
|
1024 |
-
" <tr>\n",
|
1025 |
-
" <td>163</td>\n",
|
1026 |
-
" <td>0.944600</td>\n",
|
1027 |
-
" </tr>\n",
|
1028 |
-
" <tr>\n",
|
1029 |
-
" <td>164</td>\n",
|
1030 |
-
" <td>0.935700</td>\n",
|
1031 |
-
" </tr>\n",
|
1032 |
-
" <tr>\n",
|
1033 |
-
" <td>165</td>\n",
|
1034 |
-
" <td>0.922500</td>\n",
|
1035 |
-
" </tr>\n",
|
1036 |
-
" <tr>\n",
|
1037 |
-
" <td>166</td>\n",
|
1038 |
-
" <td>0.897600</td>\n",
|
1039 |
-
" </tr>\n",
|
1040 |
-
" <tr>\n",
|
1041 |
-
" <td>167</td>\n",
|
1042 |
-
" <td>0.968600</td>\n",
|
1043 |
-
" </tr>\n",
|
1044 |
-
" <tr>\n",
|
1045 |
-
" <td>168</td>\n",
|
1046 |
-
" <td>0.927400</td>\n",
|
1047 |
-
" </tr>\n",
|
1048 |
-
" <tr>\n",
|
1049 |
-
" <td>169</td>\n",
|
1050 |
-
" <td>0.910900</td>\n",
|
1051 |
-
" </tr>\n",
|
1052 |
-
" <tr>\n",
|
1053 |
-
" <td>170</td>\n",
|
1054 |
-
" <td>0.904700</td>\n",
|
1055 |
-
" </tr>\n",
|
1056 |
-
" <tr>\n",
|
1057 |
-
" <td>171</td>\n",
|
1058 |
-
" <td>0.899800</td>\n",
|
1059 |
-
" </tr>\n",
|
1060 |
-
" <tr>\n",
|
1061 |
-
" <td>172</td>\n",
|
1062 |
-
" <td>0.896400</td>\n",
|
1063 |
-
" </tr>\n",
|
1064 |
-
" <tr>\n",
|
1065 |
-
" <td>173</td>\n",
|
1066 |
-
" <td>0.862100</td>\n",
|
1067 |
-
" </tr>\n",
|
1068 |
-
" <tr>\n",
|
1069 |
-
" <td>174</td>\n",
|
1070 |
-
" <td>0.909100</td>\n",
|
1071 |
-
" </tr>\n",
|
1072 |
-
" <tr>\n",
|
1073 |
-
" <td>175</td>\n",
|
1074 |
-
" <td>0.903200</td>\n",
|
1075 |
-
" </tr>\n",
|
1076 |
-
" <tr>\n",
|
1077 |
-
" <td>176</td>\n",
|
1078 |
-
" <td>0.958600</td>\n",
|
1079 |
-
" </tr>\n",
|
1080 |
-
" <tr>\n",
|
1081 |
-
" <td>177</td>\n",
|
1082 |
-
" <td>0.902500</td>\n",
|
1083 |
-
" </tr>\n",
|
1084 |
-
" <tr>\n",
|
1085 |
-
" <td>178</td>\n",
|
1086 |
-
" <td>0.894900</td>\n",
|
1087 |
-
" </tr>\n",
|
1088 |
-
" <tr>\n",
|
1089 |
-
" <td>179</td>\n",
|
1090 |
-
" <td>0.937900</td>\n",
|
1091 |
-
" </tr>\n",
|
1092 |
-
" <tr>\n",
|
1093 |
-
" <td>180</td>\n",
|
1094 |
-
" <td>0.900700</td>\n",
|
1095 |
-
" </tr>\n",
|
1096 |
-
" <tr>\n",
|
1097 |
-
" <td>181</td>\n",
|
1098 |
-
" <td>0.922300</td>\n",
|
1099 |
-
" </tr>\n",
|
1100 |
-
" <tr>\n",
|
1101 |
-
" <td>182</td>\n",
|
1102 |
-
" <td>0.939300</td>\n",
|
1103 |
-
" </tr>\n",
|
1104 |
-
" <tr>\n",
|
1105 |
-
" <td>183</td>\n",
|
1106 |
-
" <td>0.932600</td>\n",
|
1107 |
-
" </tr>\n",
|
1108 |
-
" <tr>\n",
|
1109 |
-
" <td>184</td>\n",
|
1110 |
-
" <td>0.913300</td>\n",
|
1111 |
-
" </tr>\n",
|
1112 |
-
" <tr>\n",
|
1113 |
-
" <td>185</td>\n",
|
1114 |
-
" <td>0.941700</td>\n",
|
1115 |
-
" </tr>\n",
|
1116 |
-
" <tr>\n",
|
1117 |
-
" <td>186</td>\n",
|
1118 |
-
" <td>0.886300</td>\n",
|
1119 |
-
" </tr>\n",
|
1120 |
-
" <tr>\n",
|
1121 |
-
" <td>187</td>\n",
|
1122 |
-
" <td>0.918000</td>\n",
|
1123 |
-
" </tr>\n",
|
1124 |
-
" <tr>\n",
|
1125 |
-
" <td>188</td>\n",
|
1126 |
-
" <td>0.884000</td>\n",
|
1127 |
-
" </tr>\n",
|
1128 |
-
" <tr>\n",
|
1129 |
-
" <td>189</td>\n",
|
1130 |
-
" <td>0.947400</td>\n",
|
1131 |
-
" </tr>\n",
|
1132 |
-
" <tr>\n",
|
1133 |
-
" <td>190</td>\n",
|
1134 |
-
" <td>0.894500</td>\n",
|
1135 |
-
" </tr>\n",
|
1136 |
-
" <tr>\n",
|
1137 |
-
" <td>191</td>\n",
|
1138 |
-
" <td>0.929300</td>\n",
|
1139 |
-
" </tr>\n",
|
1140 |
-
" <tr>\n",
|
1141 |
-
" <td>192</td>\n",
|
1142 |
-
" <td>0.877300</td>\n",
|
1143 |
-
" </tr>\n",
|
1144 |
-
" <tr>\n",
|
1145 |
-
" <td>193</td>\n",
|
1146 |
-
" <td>0.894300</td>\n",
|
1147 |
-
" </tr>\n",
|
1148 |
-
" <tr>\n",
|
1149 |
-
" <td>194</td>\n",
|
1150 |
-
" <td>0.867800</td>\n",
|
1151 |
-
" </tr>\n",
|
1152 |
-
" <tr>\n",
|
1153 |
-
" <td>195</td>\n",
|
1154 |
-
" <td>0.913500</td>\n",
|
1155 |
-
" </tr>\n",
|
1156 |
-
" <tr>\n",
|
1157 |
-
" <td>196</td>\n",
|
1158 |
-
" <td>0.908100</td>\n",
|
1159 |
-
" </tr>\n",
|
1160 |
-
" <tr>\n",
|
1161 |
-
" <td>197</td>\n",
|
1162 |
-
" <td>0.931200</td>\n",
|
1163 |
-
" </tr>\n",
|
1164 |
-
" <tr>\n",
|
1165 |
-
" <td>198</td>\n",
|
1166 |
-
" <td>0.911000</td>\n",
|
1167 |
-
" </tr>\n",
|
1168 |
-
" <tr>\n",
|
1169 |
-
" <td>199</td>\n",
|
1170 |
-
" <td>0.941800</td>\n",
|
1171 |
-
" </tr>\n",
|
1172 |
-
" <tr>\n",
|
1173 |
-
" <td>200</td>\n",
|
1174 |
-
" <td>0.913000</td>\n",
|
1175 |
-
" </tr>\n",
|
1176 |
-
" <tr>\n",
|
1177 |
-
" <td>201</td>\n",
|
1178 |
-
" <td>0.921800</td>\n",
|
1179 |
-
" </tr>\n",
|
1180 |
-
" <tr>\n",
|
1181 |
-
" <td>202</td>\n",
|
1182 |
-
" <td>0.921700</td>\n",
|
1183 |
-
" </tr>\n",
|
1184 |
-
" <tr>\n",
|
1185 |
-
" <td>203</td>\n",
|
1186 |
-
" <td>0.914500</td>\n",
|
1187 |
-
" </tr>\n",
|
1188 |
-
" <tr>\n",
|
1189 |
-
" <td>204</td>\n",
|
1190 |
-
" <td>0.910500</td>\n",
|
1191 |
-
" </tr>\n",
|
1192 |
-
" <tr>\n",
|
1193 |
-
" <td>205</td>\n",
|
1194 |
-
" <td>0.906600</td>\n",
|
1195 |
-
" </tr>\n",
|
1196 |
-
" <tr>\n",
|
1197 |
-
" <td>206</td>\n",
|
1198 |
-
" <td>0.915100</td>\n",
|
1199 |
-
" </tr>\n",
|
1200 |
-
" <tr>\n",
|
1201 |
-
" <td>207</td>\n",
|
1202 |
-
" <td>0.881600</td>\n",
|
1203 |
-
" </tr>\n",
|
1204 |
-
" <tr>\n",
|
1205 |
-
" <td>208</td>\n",
|
1206 |
-
" <td>0.884700</td>\n",
|
1207 |
-
" </tr>\n",
|
1208 |
-
" <tr>\n",
|
1209 |
-
" <td>209</td>\n",
|
1210 |
-
" <td>0.902900</td>\n",
|
1211 |
-
" </tr>\n",
|
1212 |
-
" <tr>\n",
|
1213 |
-
" <td>210</td>\n",
|
1214 |
-
" <td>0.882600</td>\n",
|
1215 |
-
" </tr>\n",
|
1216 |
-
" <tr>\n",
|
1217 |
-
" <td>211</td>\n",
|
1218 |
-
" <td>0.891000</td>\n",
|
1219 |
-
" </tr>\n",
|
1220 |
-
" <tr>\n",
|
1221 |
-
" <td>212</td>\n",
|
1222 |
-
" <td>0.914400</td>\n",
|
1223 |
-
" </tr>\n",
|
1224 |
-
" <tr>\n",
|
1225 |
-
" <td>213</td>\n",
|
1226 |
-
" <td>0.930400</td>\n",
|
1227 |
-
" </tr>\n",
|
1228 |
-
" <tr>\n",
|
1229 |
-
" <td>214</td>\n",
|
1230 |
-
" <td>0.891100</td>\n",
|
1231 |
-
" </tr>\n",
|
1232 |
-
" <tr>\n",
|
1233 |
-
" <td>215</td>\n",
|
1234 |
-
" <td>0.859300</td>\n",
|
1235 |
-
" </tr>\n",
|
1236 |
-
" <tr>\n",
|
1237 |
-
" <td>216</td>\n",
|
1238 |
-
" <td>0.891800</td>\n",
|
1239 |
-
" </tr>\n",
|
1240 |
-
" <tr>\n",
|
1241 |
-
" <td>217</td>\n",
|
1242 |
-
" <td>0.873000</td>\n",
|
1243 |
-
" </tr>\n",
|
1244 |
-
" <tr>\n",
|
1245 |
-
" <td>218</td>\n",
|
1246 |
-
" <td>0.925900</td>\n",
|
1247 |
-
" </tr>\n",
|
1248 |
-
" <tr>\n",
|
1249 |
-
" <td>219</td>\n",
|
1250 |
-
" <td>0.905700</td>\n",
|
1251 |
-
" </tr>\n",
|
1252 |
-
" <tr>\n",
|
1253 |
-
" <td>220</td>\n",
|
1254 |
-
" <td>0.921200</td>\n",
|
1255 |
-
" </tr>\n",
|
1256 |
-
" <tr>\n",
|
1257 |
-
" <td>221</td>\n",
|
1258 |
-
" <td>0.890200</td>\n",
|
1259 |
-
" </tr>\n",
|
1260 |
-
" <tr>\n",
|
1261 |
-
" <td>222</td>\n",
|
1262 |
-
" <td>0.915800</td>\n",
|
1263 |
-
" </tr>\n",
|
1264 |
-
" <tr>\n",
|
1265 |
-
" <td>223</td>\n",
|
1266 |
-
" <td>0.887300</td>\n",
|
1267 |
-
" </tr>\n",
|
1268 |
-
" <tr>\n",
|
1269 |
-
" <td>224</td>\n",
|
1270 |
-
" <td>0.898300</td>\n",
|
1271 |
-
" </tr>\n",
|
1272 |
-
" <tr>\n",
|
1273 |
-
" <td>225</td>\n",
|
1274 |
-
" <td>0.865600</td>\n",
|
1275 |
-
" </tr>\n",
|
1276 |
-
" <tr>\n",
|
1277 |
-
" <td>226</td>\n",
|
1278 |
-
" <td>0.873900</td>\n",
|
1279 |
-
" </tr>\n",
|
1280 |
-
" <tr>\n",
|
1281 |
-
" <td>227</td>\n",
|
1282 |
-
" <td>0.904800</td>\n",
|
1283 |
-
" </tr>\n",
|
1284 |
-
" <tr>\n",
|
1285 |
-
" <td>228</td>\n",
|
1286 |
-
" <td>0.917900</td>\n",
|
1287 |
-
" </tr>\n",
|
1288 |
-
" <tr>\n",
|
1289 |
-
" <td>229</td>\n",
|
1290 |
-
" <td>0.923400</td>\n",
|
1291 |
-
" </tr>\n",
|
1292 |
-
" <tr>\n",
|
1293 |
-
" <td>230</td>\n",
|
1294 |
-
" <td>0.939700</td>\n",
|
1295 |
-
" </tr>\n",
|
1296 |
-
" <tr>\n",
|
1297 |
-
" <td>231</td>\n",
|
1298 |
-
" <td>0.913400</td>\n",
|
1299 |
-
" </tr>\n",
|
1300 |
-
" <tr>\n",
|
1301 |
-
" <td>232</td>\n",
|
1302 |
-
" <td>0.873100</td>\n",
|
1303 |
-
" </tr>\n",
|
1304 |
-
" <tr>\n",
|
1305 |
-
" <td>233</td>\n",
|
1306 |
-
" <td>0.896700</td>\n",
|
1307 |
-
" </tr>\n",
|
1308 |
-
" <tr>\n",
|
1309 |
-
" <td>234</td>\n",
|
1310 |
-
" <td>0.892100</td>\n",
|
1311 |
-
" </tr>\n",
|
1312 |
-
" <tr>\n",
|
1313 |
-
" <td>235</td>\n",
|
1314 |
-
" <td>0.902100</td>\n",
|
1315 |
-
" </tr>\n",
|
1316 |
-
" <tr>\n",
|
1317 |
-
" <td>236</td>\n",
|
1318 |
-
" <td>0.927200</td>\n",
|
1319 |
-
" </tr>\n",
|
1320 |
-
" <tr>\n",
|
1321 |
-
" <td>237</td>\n",
|
1322 |
-
" <td>0.912900</td>\n",
|
1323 |
-
" </tr>\n",
|
1324 |
-
" <tr>\n",
|
1325 |
-
" <td>238</td>\n",
|
1326 |
-
" <td>0.872900</td>\n",
|
1327 |
-
" </tr>\n",
|
1328 |
-
" <tr>\n",
|
1329 |
-
" <td>239</td>\n",
|
1330 |
-
" <td>0.904700</td>\n",
|
1331 |
-
" </tr>\n",
|
1332 |
-
" <tr>\n",
|
1333 |
-
" <td>240</td>\n",
|
1334 |
-
" <td>0.879600</td>\n",
|
1335 |
-
" </tr>\n",
|
1336 |
-
" <tr>\n",
|
1337 |
-
" <td>241</td>\n",
|
1338 |
-
" <td>0.879800</td>\n",
|
1339 |
-
" </tr>\n",
|
1340 |
-
" <tr>\n",
|
1341 |
-
" <td>242</td>\n",
|
1342 |
-
" <td>0.908800</td>\n",
|
1343 |
-
" </tr>\n",
|
1344 |
-
" <tr>\n",
|
1345 |
-
" <td>243</td>\n",
|
1346 |
-
" <td>0.909800</td>\n",
|
1347 |
-
" </tr>\n",
|
1348 |
-
" <tr>\n",
|
1349 |
-
" <td>244</td>\n",
|
1350 |
-
" <td>0.838400</td>\n",
|
1351 |
-
" </tr>\n",
|
1352 |
-
" <tr>\n",
|
1353 |
-
" <td>245</td>\n",
|
1354 |
-
" <td>0.889200</td>\n",
|
1355 |
-
" </tr>\n",
|
1356 |
-
" <tr>\n",
|
1357 |
-
" <td>246</td>\n",
|
1358 |
-
" <td>0.912900</td>\n",
|
1359 |
-
" </tr>\n",
|
1360 |
-
" <tr>\n",
|
1361 |
-
" <td>247</td>\n",
|
1362 |
-
" <td>0.879700</td>\n",
|
1363 |
-
" </tr>\n",
|
1364 |
-
" <tr>\n",
|
1365 |
-
" <td>248</td>\n",
|
1366 |
-
" <td>0.910700</td>\n",
|
1367 |
-
" </tr>\n",
|
1368 |
-
" <tr>\n",
|
1369 |
-
" <td>249</td>\n",
|
1370 |
-
" <td>0.845400</td>\n",
|
1371 |
-
" </tr>\n",
|
1372 |
-
" <tr>\n",
|
1373 |
-
" <td>250</td>\n",
|
1374 |
-
" <td>0.882200</td>\n",
|
1375 |
" </tr>\n",
|
1376 |
" </tbody>\n",
|
1377 |
"</table><p>"
|
@@ -1382,6 +389,22 @@
|
|
1382 |
},
|
1383 |
"metadata": {},
|
1384 |
"output_type": "display_data"
|
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|
1385 |
}
|
1386 |
],
|
1387 |
"source": [
|
@@ -1392,12 +415,12 @@
|
|
1392 |
" data_collator=transformers.DataCollatorForLanguageModeling(tokenizer, mlm=False)\n",
|
1393 |
")\n",
|
1394 |
"trainer.train(resume_from_checkpoint=False)\n",
|
1395 |
-
"model.save_pretrained('sqllama-
|
1396 |
]
|
1397 |
},
|
1398 |
{
|
1399 |
"cell_type": "code",
|
1400 |
-
"execution_count":
|
1401 |
"metadata": {},
|
1402 |
"outputs": [
|
1403 |
{
|
|
|
55 |
{
|
56 |
"data": {
|
57 |
"application/vnd.jupyter.widget-view+json": {
|
58 |
+
"model_id": "f8ad2d1a5de842bcb6b7e3c6972d9074",
|
59 |
"version_major": 2,
|
60 |
"version_minor": 0
|
61 |
},
|
|
|
96 |
"output_type": "stream",
|
97 |
"text": [
|
98 |
"\n",
|
99 |
+
"table: 2-17672470-19\n",
|
100 |
+
"columns: Stage,Winner,General Classification,Mountains Classification,Points Classification,Sprints classification,Team Classification\n",
|
101 |
+
"Q: What is the stage of Gerolsteiner?\n",
|
102 |
+
"A: SELECT Stage FROM 2-17672470-19 WHERE Team Classification = 'gerolsteiner'\n",
|
103 |
"END\n",
|
104 |
"\n",
|
105 |
"\n",
|
106 |
+
"table: 2-12518301-2\n",
|
107 |
+
"columns: Rider,Matches,Rides,Bonus Pts,Total Points\n",
|
108 |
+
"Q: What was the average number of points with bonus pts less than 31 with the rider dennis gavros?\n",
|
109 |
+
"A: SELECT AVG Total Points FROM 2-12518301-2 WHERE Rider = 'dennis gavros' AND Bonus Pts < 31\n",
|
110 |
"END\n",
|
111 |
"\n",
|
112 |
"\n",
|
113 |
+
"table: 1-27961684-1\n",
|
114 |
+
"columns: Institution,City,State,Team Name,Affiliation,Enrollment,Home Conference\n",
|
115 |
+
"Q: How many states were there when there was an enrollment of 2789?\n",
|
116 |
+
"A: SELECT COUNT State FROM 1-27961684-1 WHERE Enrollment = 2789\n",
|
117 |
"END\n",
|
118 |
"\n",
|
119 |
"\n",
|
120 |
+
"table: 2-17441442-2\n",
|
121 |
+
"columns: Res.,Record,Opponent,Method,Event,Round,Time,Location\n",
|
122 |
+
"Q: What is the round number when the record is 15–7–1?\n",
|
123 |
+
"A: SELECT COUNT Round FROM 2-17441442-2 WHERE Record = '15–7–1'\n",
|
124 |
"END\n",
|
125 |
"\n",
|
126 |
"\n",
|
127 |
+
"table: 2-17406982-1\n",
|
128 |
+
"columns: Round,Pick,Player,Position,School/Club Team\n",
|
129 |
+
"Q: What pick in round 5 did the 49ers pick Jim Pilot?\n",
|
130 |
+
"A: SELECT SUM Pick FROM 2-17406982-1 WHERE Player = 'jim pilot' AND Round > 5\n",
|
131 |
"END\n",
|
132 |
"\n"
|
133 |
]
|
|
|
278 |
{
|
279 |
"data": {
|
280 |
"application/vnd.jupyter.widget-view+json": {
|
281 |
+
"model_id": "708e075933754c6c940eeae9e3d3abc9",
|
282 |
"version_major": 2,
|
283 |
"version_minor": 0
|
284 |
},
|
|
|
320 |
"LORA_R = 4\n",
|
321 |
"LORA_ALPHA = 16\n",
|
322 |
"LORA_DROPOUT = .1\n",
|
|
|
323 |
"BATCH = 128\n",
|
324 |
"MICRO_BATCH = 4\n",
|
325 |
"N_GAS = BATCH//MICRO_BATCH\n",
|
326 |
+
"EPOCHS = 2\n",
|
327 |
+
"LR = 1e-5\n",
|
328 |
"\n",
|
329 |
"lora_cfg = LoraConfig(\n",
|
330 |
" r = LORA_R,\n",
|
|
|
344 |
" learning_rate=LR,\n",
|
345 |
" fp16=True,\n",
|
346 |
" logging_steps=1,\n",
|
347 |
+
" output_dir='sqllama-out3',\n",
|
348 |
" save_total_limit=3,\n",
|
349 |
" remove_unused_columns=False\n",
|
350 |
")\n"
|
|
|
361 |
"\n",
|
362 |
" <div>\n",
|
363 |
" \n",
|
364 |
+
" <progress value='4' max='500' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
|
365 |
+
" [ 4/500 01:51 < 7:38:51, 0.02 it/s, Epoch 0.01/2]\n",
|
366 |
" </div>\n",
|
367 |
" <table border=\"1\" class=\"dataframe\">\n",
|
368 |
" <thead>\n",
|
|
|
378 |
" </tr>\n",
|
379 |
" <tr>\n",
|
380 |
" <td>2</td>\n",
|
381 |
+
" <td>2.725100</td>\n",
|
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|
382 |
" </tr>\n",
|
383 |
" </tbody>\n",
|
384 |
"</table><p>"
|
|
|
389 |
},
|
390 |
"metadata": {},
|
391 |
"output_type": "display_data"
|
392 |
+
},
|
393 |
+
{
|
394 |
+
"ename": "KeyboardInterrupt",
|
395 |
+
"evalue": "",
|
396 |
+
"output_type": "error",
|
397 |
+
"traceback": [
|
398 |
+
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
|
399 |
+
"\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
|
400 |
+
"\u001b[0;32m/var/tmp/ipykernel_24178/3667964638.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-out3'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
|
401 |
+
"\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",
|
402 |
+
"\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 1927\u001b[0m \u001b[0mtr_loss_step\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtraining_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minputs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1928\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[0;32m-> 1929\u001b[0;31m \u001b[0mtr_loss_step\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtraining_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmodel\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minputs\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 1930\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1931\u001b[0m if (\n",
|
403 |
+
"\u001b[0;32m~/hf/sqllama-V0/.venv/lib/python3.7/site-packages/transformers/trainer.py\u001b[0m in \u001b[0;36mtraining_step\u001b[0;34m(self, model, inputs)\u001b[0m\n\u001b[1;32m 2707\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2708\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdo_grad_scaling\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2709\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscaler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscale\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloss\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbackward\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 2710\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0muse_apex\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2711\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mamp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mscale_loss\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mloss\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptimizer\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mscaled_loss\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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+
"\u001b[0;32m~/hf/sqllama-V0/.venv/lib/python3.7/site-packages/torch/_tensor.py\u001b[0m in \u001b[0;36mbackward\u001b[0;34m(self, gradient, retain_graph, create_graph, inputs)\u001b[0m\n\u001b[1;32m 487\u001b[0m )\n\u001b[1;32m 488\u001b[0m torch.autograd.backward(\n\u001b[0;32m--> 489\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgradient\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mretain_graph\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcreate_graph\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minputs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minputs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 490\u001b[0m )\n\u001b[1;32m 491\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
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+
"\u001b[0;32m~/hf/sqllama-V0/.venv/lib/python3.7/site-packages/torch/autograd/__init__.py\u001b[0m in \u001b[0;36mbackward\u001b[0;34m(tensors, grad_tensors, retain_graph, create_graph, grad_variables, inputs)\u001b[0m\n\u001b[1;32m 197\u001b[0m Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass\n\u001b[1;32m 198\u001b[0m \u001b[0mtensors\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgrad_tensors_\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mretain_graph\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcreate_graph\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minputs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 199\u001b[0;31m allow_unreachable=True, accumulate_grad=True) # Calls into the C++ engine to run the backward pass\n\u001b[0m\u001b[1;32m 200\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 201\u001b[0m def grad(\n",
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"\u001b[0;31mKeyboardInterrupt\u001b[0m: "
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+
]
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}
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],
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"source": [
|
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" data_collator=transformers.DataCollatorForLanguageModeling(tokenizer, mlm=False)\n",
|
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")\n",
|
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"trainer.train(resume_from_checkpoint=False)\n",
|
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+
"model.save_pretrained('sqllama-out3')"
|
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]
|
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},
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{
|
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"cell_type": "code",
|
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+
"execution_count": null,
|
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"metadata": {},
|
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"outputs": [
|
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{
|