simonycl commited on
Commit
0abcf80
1 Parent(s): 536e7f0

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +155 -155
README.md CHANGED
@@ -1,6 +1,6 @@
1
  ---
2
- license: mit
3
- base_model: roberta-base
4
  tags:
5
  - generated_from_trainer
6
  metrics:
@@ -15,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
15
 
16
  # best_model-yelp_polarity-16-21
17
 
18
- This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
19
  It achieves the following results on the evaluation set:
20
- - Loss: 0.5510
21
- - Accuracy: 0.8438
22
 
23
  ## Model description
24
 
@@ -50,156 +50,156 @@ The following hyperparameters were used during training:
50
 
51
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
52
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
53
- | No log | 1.0 | 1 | 0.4875 | 0.7188 |
54
- | No log | 2.0 | 2 | 0.4874 | 0.7188 |
55
- | No log | 3.0 | 3 | 0.4870 | 0.7188 |
56
- | No log | 4.0 | 4 | 0.4866 | 0.7188 |
57
- | No log | 5.0 | 5 | 0.4859 | 0.7188 |
58
- | No log | 6.0 | 6 | 0.4851 | 0.7188 |
59
- | No log | 7.0 | 7 | 0.4841 | 0.7188 |
60
- | No log | 8.0 | 8 | 0.4831 | 0.7188 |
61
- | No log | 9.0 | 9 | 0.4820 | 0.7188 |
62
- | 0.4091 | 10.0 | 10 | 0.4807 | 0.7188 |
63
- | 0.4091 | 11.0 | 11 | 0.4793 | 0.7188 |
64
- | 0.4091 | 12.0 | 12 | 0.4779 | 0.7188 |
65
- | 0.4091 | 13.0 | 13 | 0.4764 | 0.7188 |
66
- | 0.4091 | 14.0 | 14 | 0.4748 | 0.7188 |
67
- | 0.4091 | 15.0 | 15 | 0.4730 | 0.7188 |
68
- | 0.4091 | 16.0 | 16 | 0.4713 | 0.7188 |
69
- | 0.4091 | 17.0 | 17 | 0.4696 | 0.7188 |
70
- | 0.4091 | 18.0 | 18 | 0.4677 | 0.7188 |
71
- | 0.4091 | 19.0 | 19 | 0.4657 | 0.7188 |
72
- | 0.3792 | 20.0 | 20 | 0.4636 | 0.7188 |
73
- | 0.3792 | 21.0 | 21 | 0.4613 | 0.7188 |
74
- | 0.3792 | 22.0 | 22 | 0.4589 | 0.75 |
75
- | 0.3792 | 23.0 | 23 | 0.4564 | 0.7812 |
76
- | 0.3792 | 24.0 | 24 | 0.4538 | 0.7812 |
77
- | 0.3792 | 25.0 | 25 | 0.4511 | 0.7812 |
78
- | 0.3792 | 26.0 | 26 | 0.4485 | 0.7812 |
79
- | 0.3792 | 27.0 | 27 | 0.4458 | 0.7812 |
80
- | 0.3792 | 28.0 | 28 | 0.4429 | 0.7812 |
81
- | 0.3792 | 29.0 | 29 | 0.4401 | 0.7812 |
82
- | 0.3464 | 30.0 | 30 | 0.4374 | 0.7812 |
83
- | 0.3464 | 31.0 | 31 | 0.4345 | 0.7812 |
84
- | 0.3464 | 32.0 | 32 | 0.4320 | 0.7812 |
85
- | 0.3464 | 33.0 | 33 | 0.4294 | 0.7812 |
86
- | 0.3464 | 34.0 | 34 | 0.4271 | 0.7812 |
87
- | 0.3464 | 35.0 | 35 | 0.4246 | 0.7812 |
88
- | 0.3464 | 36.0 | 36 | 0.4223 | 0.7812 |
89
- | 0.3464 | 37.0 | 37 | 0.4198 | 0.7812 |
90
- | 0.3464 | 38.0 | 38 | 0.4173 | 0.7812 |
91
- | 0.3464 | 39.0 | 39 | 0.4148 | 0.7812 |
92
- | 0.2744 | 40.0 | 40 | 0.4125 | 0.7812 |
93
- | 0.2744 | 41.0 | 41 | 0.4103 | 0.7812 |
94
- | 0.2744 | 42.0 | 42 | 0.4080 | 0.7812 |
95
- | 0.2744 | 43.0 | 43 | 0.4059 | 0.7812 |
96
- | 0.2744 | 44.0 | 44 | 0.4037 | 0.7812 |
97
- | 0.2744 | 45.0 | 45 | 0.4013 | 0.7812 |
98
- | 0.2744 | 46.0 | 46 | 0.3996 | 0.7812 |
99
- | 0.2744 | 47.0 | 47 | 0.3979 | 0.7812 |
100
- | 0.2744 | 48.0 | 48 | 0.3958 | 0.8438 |
101
- | 0.2744 | 49.0 | 49 | 0.3936 | 0.8438 |
102
- | 0.1968 | 50.0 | 50 | 0.3912 | 0.8438 |
103
- | 0.1968 | 51.0 | 51 | 0.3894 | 0.8438 |
104
- | 0.1968 | 52.0 | 52 | 0.3880 | 0.8438 |
105
- | 0.1968 | 53.0 | 53 | 0.3861 | 0.8438 |
106
- | 0.1968 | 54.0 | 54 | 0.3850 | 0.8438 |
107
- | 0.1968 | 55.0 | 55 | 0.3839 | 0.8438 |
108
- | 0.1968 | 56.0 | 56 | 0.3828 | 0.8438 |
109
- | 0.1968 | 57.0 | 57 | 0.3811 | 0.8438 |
110
- | 0.1968 | 58.0 | 58 | 0.3797 | 0.8438 |
111
- | 0.1968 | 59.0 | 59 | 0.3789 | 0.8438 |
112
- | 0.1355 | 60.0 | 60 | 0.3778 | 0.8438 |
113
- | 0.1355 | 61.0 | 61 | 0.3770 | 0.8438 |
114
- | 0.1355 | 62.0 | 62 | 0.3765 | 0.8438 |
115
- | 0.1355 | 63.0 | 63 | 0.3775 | 0.8438 |
116
- | 0.1355 | 64.0 | 64 | 0.3799 | 0.8438 |
117
- | 0.1355 | 65.0 | 65 | 0.3820 | 0.8438 |
118
- | 0.1355 | 66.0 | 66 | 0.3847 | 0.8438 |
119
- | 0.1355 | 67.0 | 67 | 0.3870 | 0.8125 |
120
- | 0.1355 | 68.0 | 68 | 0.3898 | 0.7812 |
121
- | 0.1355 | 69.0 | 69 | 0.3929 | 0.7812 |
122
- | 0.0796 | 70.0 | 70 | 0.3951 | 0.7812 |
123
- | 0.0796 | 71.0 | 71 | 0.3951 | 0.7812 |
124
- | 0.0796 | 72.0 | 72 | 0.3968 | 0.7812 |
125
- | 0.0796 | 73.0 | 73 | 0.3985 | 0.7812 |
126
- | 0.0796 | 74.0 | 74 | 0.3994 | 0.8125 |
127
- | 0.0796 | 75.0 | 75 | 0.4001 | 0.8125 |
128
- | 0.0796 | 76.0 | 76 | 0.3999 | 0.8438 |
129
- | 0.0796 | 77.0 | 77 | 0.3990 | 0.8438 |
130
- | 0.0796 | 78.0 | 78 | 0.3996 | 0.8438 |
131
- | 0.0796 | 79.0 | 79 | 0.4010 | 0.8438 |
132
- | 0.0465 | 80.0 | 80 | 0.4037 | 0.8438 |
133
- | 0.0465 | 81.0 | 81 | 0.4059 | 0.8438 |
134
- | 0.0465 | 82.0 | 82 | 0.4084 | 0.8438 |
135
- | 0.0465 | 83.0 | 83 | 0.4106 | 0.8438 |
136
- | 0.0465 | 84.0 | 84 | 0.4126 | 0.8438 |
137
- | 0.0465 | 85.0 | 85 | 0.4141 | 0.8438 |
138
- | 0.0465 | 86.0 | 86 | 0.4147 | 0.8438 |
139
- | 0.0465 | 87.0 | 87 | 0.4152 | 0.8438 |
140
- | 0.0465 | 88.0 | 88 | 0.4157 | 0.8438 |
141
- | 0.0465 | 89.0 | 89 | 0.4167 | 0.875 |
142
- | 0.0267 | 90.0 | 90 | 0.4177 | 0.875 |
143
- | 0.0267 | 91.0 | 91 | 0.4191 | 0.875 |
144
- | 0.0267 | 92.0 | 92 | 0.4214 | 0.875 |
145
- | 0.0267 | 93.0 | 93 | 0.4240 | 0.875 |
146
- | 0.0267 | 94.0 | 94 | 0.4269 | 0.875 |
147
- | 0.0267 | 95.0 | 95 | 0.4302 | 0.875 |
148
- | 0.0267 | 96.0 | 96 | 0.4338 | 0.875 |
149
- | 0.0267 | 97.0 | 97 | 0.4375 | 0.875 |
150
- | 0.0267 | 98.0 | 98 | 0.4414 | 0.875 |
151
- | 0.0267 | 99.0 | 99 | 0.4453 | 0.875 |
152
- | 0.0158 | 100.0 | 100 | 0.4493 | 0.875 |
153
- | 0.0158 | 101.0 | 101 | 0.4533 | 0.8438 |
154
- | 0.0158 | 102.0 | 102 | 0.4575 | 0.8438 |
155
- | 0.0158 | 103.0 | 103 | 0.4618 | 0.8438 |
156
- | 0.0158 | 104.0 | 104 | 0.4654 | 0.8438 |
157
- | 0.0158 | 105.0 | 105 | 0.4685 | 0.8438 |
158
- | 0.0158 | 106.0 | 106 | 0.4719 | 0.8438 |
159
- | 0.0158 | 107.0 | 107 | 0.4751 | 0.8438 |
160
- | 0.0158 | 108.0 | 108 | 0.4782 | 0.8438 |
161
- | 0.0158 | 109.0 | 109 | 0.4812 | 0.8438 |
162
- | 0.0107 | 110.0 | 110 | 0.4839 | 0.8438 |
163
- | 0.0107 | 111.0 | 111 | 0.4867 | 0.8438 |
164
- | 0.0107 | 112.0 | 112 | 0.4890 | 0.8438 |
165
- | 0.0107 | 113.0 | 113 | 0.4911 | 0.8438 |
166
- | 0.0107 | 114.0 | 114 | 0.4930 | 0.8438 |
167
- | 0.0107 | 115.0 | 115 | 0.4949 | 0.8438 |
168
- | 0.0107 | 116.0 | 116 | 0.4966 | 0.8438 |
169
- | 0.0107 | 117.0 | 117 | 0.4982 | 0.8438 |
170
- | 0.0107 | 118.0 | 118 | 0.4997 | 0.8438 |
171
- | 0.0107 | 119.0 | 119 | 0.5010 | 0.8438 |
172
- | 0.0078 | 120.0 | 120 | 0.5019 | 0.8438 |
173
- | 0.0078 | 121.0 | 121 | 0.5028 | 0.8438 |
174
- | 0.0078 | 122.0 | 122 | 0.5040 | 0.8438 |
175
- | 0.0078 | 123.0 | 123 | 0.5052 | 0.8438 |
176
- | 0.0078 | 124.0 | 124 | 0.5063 | 0.875 |
177
- | 0.0078 | 125.0 | 125 | 0.5073 | 0.875 |
178
- | 0.0078 | 126.0 | 126 | 0.5083 | 0.875 |
179
- | 0.0078 | 127.0 | 127 | 0.5096 | 0.875 |
180
- | 0.0078 | 128.0 | 128 | 0.5107 | 0.875 |
181
- | 0.0078 | 129.0 | 129 | 0.5121 | 0.875 |
182
- | 0.0061 | 130.0 | 130 | 0.5135 | 0.875 |
183
- | 0.0061 | 131.0 | 131 | 0.5150 | 0.875 |
184
- | 0.0061 | 132.0 | 132 | 0.5167 | 0.875 |
185
- | 0.0061 | 133.0 | 133 | 0.5185 | 0.875 |
186
- | 0.0061 | 134.0 | 134 | 0.5204 | 0.875 |
187
- | 0.0061 | 135.0 | 135 | 0.5224 | 0.875 |
188
- | 0.0061 | 136.0 | 136 | 0.5245 | 0.875 |
189
- | 0.0061 | 137.0 | 137 | 0.5268 | 0.875 |
190
- | 0.0061 | 138.0 | 138 | 0.5289 | 0.875 |
191
- | 0.0061 | 139.0 | 139 | 0.5309 | 0.875 |
192
- | 0.0048 | 140.0 | 140 | 0.5331 | 0.8438 |
193
- | 0.0048 | 141.0 | 141 | 0.5353 | 0.8438 |
194
- | 0.0048 | 142.0 | 142 | 0.5373 | 0.8438 |
195
- | 0.0048 | 143.0 | 143 | 0.5394 | 0.8438 |
196
- | 0.0048 | 144.0 | 144 | 0.5415 | 0.8438 |
197
- | 0.0048 | 145.0 | 145 | 0.5435 | 0.8438 |
198
- | 0.0048 | 146.0 | 146 | 0.5453 | 0.8438 |
199
- | 0.0048 | 147.0 | 147 | 0.5470 | 0.8438 |
200
- | 0.0048 | 148.0 | 148 | 0.5484 | 0.8438 |
201
- | 0.0048 | 149.0 | 149 | 0.5496 | 0.8438 |
202
- | 0.0042 | 150.0 | 150 | 0.5510 | 0.8438 |
203
 
204
 
205
  ### Framework versions
 
1
  ---
2
+ license: apache-2.0
3
+ base_model: albert-base-v2
4
  tags:
5
  - generated_from_trainer
6
  metrics:
 
15
 
16
  # best_model-yelp_polarity-16-21
17
 
18
+ This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
19
  It achieves the following results on the evaluation set:
20
+ - Loss: 0.8234
21
+ - Accuracy: 0.75
22
 
23
  ## Model description
24
 
 
50
 
51
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
52
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
53
+ | No log | 1.0 | 1 | 0.8218 | 0.625 |
54
+ | No log | 2.0 | 2 | 0.8206 | 0.625 |
55
+ | No log | 3.0 | 3 | 0.8183 | 0.625 |
56
+ | No log | 4.0 | 4 | 0.8150 | 0.625 |
57
+ | No log | 5.0 | 5 | 0.8107 | 0.625 |
58
+ | No log | 6.0 | 6 | 0.8057 | 0.625 |
59
+ | No log | 7.0 | 7 | 0.8001 | 0.6562 |
60
+ | No log | 8.0 | 8 | 0.7944 | 0.6875 |
61
+ | No log | 9.0 | 9 | 0.7887 | 0.7188 |
62
+ | 0.5647 | 10.0 | 10 | 0.7834 | 0.7188 |
63
+ | 0.5647 | 11.0 | 11 | 0.7784 | 0.7188 |
64
+ | 0.5647 | 12.0 | 12 | 0.7738 | 0.7188 |
65
+ | 0.5647 | 13.0 | 13 | 0.7695 | 0.7188 |
66
+ | 0.5647 | 14.0 | 14 | 0.7651 | 0.7188 |
67
+ | 0.5647 | 15.0 | 15 | 0.7606 | 0.7188 |
68
+ | 0.5647 | 16.0 | 16 | 0.7558 | 0.7188 |
69
+ | 0.5647 | 17.0 | 17 | 0.7506 | 0.7188 |
70
+ | 0.5647 | 18.0 | 18 | 0.7451 | 0.7188 |
71
+ | 0.5647 | 19.0 | 19 | 0.7392 | 0.7188 |
72
+ | 0.472 | 20.0 | 20 | 0.7329 | 0.7188 |
73
+ | 0.472 | 21.0 | 21 | 0.7262 | 0.7188 |
74
+ | 0.472 | 22.0 | 22 | 0.7190 | 0.7188 |
75
+ | 0.472 | 23.0 | 23 | 0.7112 | 0.75 |
76
+ | 0.472 | 24.0 | 24 | 0.7029 | 0.75 |
77
+ | 0.472 | 25.0 | 25 | 0.6941 | 0.75 |
78
+ | 0.472 | 26.0 | 26 | 0.6847 | 0.75 |
79
+ | 0.472 | 27.0 | 27 | 0.6749 | 0.75 |
80
+ | 0.472 | 28.0 | 28 | 0.6647 | 0.75 |
81
+ | 0.472 | 29.0 | 29 | 0.6545 | 0.75 |
82
+ | 0.3267 | 30.0 | 30 | 0.6445 | 0.75 |
83
+ | 0.3267 | 31.0 | 31 | 0.6350 | 0.6562 |
84
+ | 0.3267 | 32.0 | 32 | 0.6261 | 0.6562 |
85
+ | 0.3267 | 33.0 | 33 | 0.6177 | 0.6875 |
86
+ | 0.3267 | 34.0 | 34 | 0.6100 | 0.6875 |
87
+ | 0.3267 | 35.0 | 35 | 0.6031 | 0.6875 |
88
+ | 0.3267 | 36.0 | 36 | 0.5973 | 0.6875 |
89
+ | 0.3267 | 37.0 | 37 | 0.5926 | 0.7188 |
90
+ | 0.3267 | 38.0 | 38 | 0.5895 | 0.7188 |
91
+ | 0.3267 | 39.0 | 39 | 0.5869 | 0.7188 |
92
+ | 0.1824 | 40.0 | 40 | 0.5842 | 0.75 |
93
+ | 0.1824 | 41.0 | 41 | 0.5796 | 0.75 |
94
+ | 0.1824 | 42.0 | 42 | 0.5730 | 0.75 |
95
+ | 0.1824 | 43.0 | 43 | 0.5651 | 0.75 |
96
+ | 0.1824 | 44.0 | 44 | 0.5555 | 0.75 |
97
+ | 0.1824 | 45.0 | 45 | 0.5466 | 0.7812 |
98
+ | 0.1824 | 46.0 | 46 | 0.5408 | 0.7812 |
99
+ | 0.1824 | 47.0 | 47 | 0.5379 | 0.7812 |
100
+ | 0.1824 | 48.0 | 48 | 0.5386 | 0.7812 |
101
+ | 0.1824 | 49.0 | 49 | 0.5419 | 0.7812 |
102
+ | 0.0885 | 50.0 | 50 | 0.5482 | 0.7812 |
103
+ | 0.0885 | 51.0 | 51 | 0.5568 | 0.7812 |
104
+ | 0.0885 | 52.0 | 52 | 0.5662 | 0.7812 |
105
+ | 0.0885 | 53.0 | 53 | 0.5761 | 0.7812 |
106
+ | 0.0885 | 54.0 | 54 | 0.5834 | 0.7812 |
107
+ | 0.0885 | 55.0 | 55 | 0.5897 | 0.8125 |
108
+ | 0.0885 | 56.0 | 56 | 0.5929 | 0.8125 |
109
+ | 0.0885 | 57.0 | 57 | 0.5930 | 0.8125 |
110
+ | 0.0885 | 58.0 | 58 | 0.5905 | 0.7812 |
111
+ | 0.0885 | 59.0 | 59 | 0.5869 | 0.7812 |
112
+ | 0.0497 | 60.0 | 60 | 0.5830 | 0.7812 |
113
+ | 0.0497 | 61.0 | 61 | 0.5795 | 0.75 |
114
+ | 0.0497 | 62.0 | 62 | 0.5776 | 0.75 |
115
+ | 0.0497 | 63.0 | 63 | 0.5777 | 0.75 |
116
+ | 0.0497 | 64.0 | 64 | 0.5800 | 0.75 |
117
+ | 0.0497 | 65.0 | 65 | 0.5832 | 0.75 |
118
+ | 0.0497 | 66.0 | 66 | 0.5887 | 0.75 |
119
+ | 0.0497 | 67.0 | 67 | 0.5962 | 0.7812 |
120
+ | 0.0497 | 68.0 | 68 | 0.6062 | 0.7812 |
121
+ | 0.0497 | 69.0 | 69 | 0.6192 | 0.75 |
122
+ | 0.0306 | 70.0 | 70 | 0.6332 | 0.75 |
123
+ | 0.0306 | 71.0 | 71 | 0.6475 | 0.75 |
124
+ | 0.0306 | 72.0 | 72 | 0.6610 | 0.75 |
125
+ | 0.0306 | 73.0 | 73 | 0.6726 | 0.75 |
126
+ | 0.0306 | 74.0 | 74 | 0.6824 | 0.75 |
127
+ | 0.0306 | 75.0 | 75 | 0.6910 | 0.75 |
128
+ | 0.0306 | 76.0 | 76 | 0.6989 | 0.75 |
129
+ | 0.0306 | 77.0 | 77 | 0.7058 | 0.75 |
130
+ | 0.0306 | 78.0 | 78 | 0.7122 | 0.75 |
131
+ | 0.0306 | 79.0 | 79 | 0.7179 | 0.7188 |
132
+ | 0.0175 | 80.0 | 80 | 0.7230 | 0.7188 |
133
+ | 0.0175 | 81.0 | 81 | 0.7281 | 0.7188 |
134
+ | 0.0175 | 82.0 | 82 | 0.7331 | 0.7188 |
135
+ | 0.0175 | 83.0 | 83 | 0.7385 | 0.7188 |
136
+ | 0.0175 | 84.0 | 84 | 0.7428 | 0.7188 |
137
+ | 0.0175 | 85.0 | 85 | 0.7462 | 0.7188 |
138
+ | 0.0175 | 86.0 | 86 | 0.7491 | 0.75 |
139
+ | 0.0175 | 87.0 | 87 | 0.7520 | 0.75 |
140
+ | 0.0175 | 88.0 | 88 | 0.7544 | 0.75 |
141
+ | 0.0175 | 89.0 | 89 | 0.7566 | 0.75 |
142
+ | 0.0111 | 90.0 | 90 | 0.7584 | 0.75 |
143
+ | 0.0111 | 91.0 | 91 | 0.7604 | 0.75 |
144
+ | 0.0111 | 92.0 | 92 | 0.7622 | 0.75 |
145
+ | 0.0111 | 93.0 | 93 | 0.7641 | 0.75 |
146
+ | 0.0111 | 94.0 | 94 | 0.7665 | 0.75 |
147
+ | 0.0111 | 95.0 | 95 | 0.7693 | 0.75 |
148
+ | 0.0111 | 96.0 | 96 | 0.7724 | 0.75 |
149
+ | 0.0111 | 97.0 | 97 | 0.7757 | 0.75 |
150
+ | 0.0111 | 98.0 | 98 | 0.7792 | 0.75 |
151
+ | 0.0111 | 99.0 | 99 | 0.7828 | 0.75 |
152
+ | 0.0078 | 100.0 | 100 | 0.7868 | 0.75 |
153
+ | 0.0078 | 101.0 | 101 | 0.7911 | 0.75 |
154
+ | 0.0078 | 102.0 | 102 | 0.7959 | 0.75 |
155
+ | 0.0078 | 103.0 | 103 | 0.8010 | 0.75 |
156
+ | 0.0078 | 104.0 | 104 | 0.8059 | 0.75 |
157
+ | 0.0078 | 105.0 | 105 | 0.8106 | 0.75 |
158
+ | 0.0078 | 106.0 | 106 | 0.8150 | 0.75 |
159
+ | 0.0078 | 107.0 | 107 | 0.8193 | 0.75 |
160
+ | 0.0078 | 108.0 | 108 | 0.8230 | 0.75 |
161
+ | 0.0078 | 109.0 | 109 | 0.8263 | 0.75 |
162
+ | 0.0061 | 110.0 | 110 | 0.8290 | 0.75 |
163
+ | 0.0061 | 111.0 | 111 | 0.8312 | 0.75 |
164
+ | 0.0061 | 112.0 | 112 | 0.8328 | 0.75 |
165
+ | 0.0061 | 113.0 | 113 | 0.8339 | 0.75 |
166
+ | 0.0061 | 114.0 | 114 | 0.8345 | 0.75 |
167
+ | 0.0061 | 115.0 | 115 | 0.8348 | 0.75 |
168
+ | 0.0061 | 116.0 | 116 | 0.8347 | 0.75 |
169
+ | 0.0061 | 117.0 | 117 | 0.8338 | 0.75 |
170
+ | 0.0061 | 118.0 | 118 | 0.8329 | 0.75 |
171
+ | 0.0061 | 119.0 | 119 | 0.8322 | 0.75 |
172
+ | 0.0048 | 120.0 | 120 | 0.8315 | 0.75 |
173
+ | 0.0048 | 121.0 | 121 | 0.8308 | 0.75 |
174
+ | 0.0048 | 122.0 | 122 | 0.8301 | 0.75 |
175
+ | 0.0048 | 123.0 | 123 | 0.8296 | 0.75 |
176
+ | 0.0048 | 124.0 | 124 | 0.8294 | 0.75 |
177
+ | 0.0048 | 125.0 | 125 | 0.8296 | 0.75 |
178
+ | 0.0048 | 126.0 | 126 | 0.8299 | 0.75 |
179
+ | 0.0048 | 127.0 | 127 | 0.8302 | 0.75 |
180
+ | 0.0048 | 128.0 | 128 | 0.8302 | 0.75 |
181
+ | 0.0048 | 129.0 | 129 | 0.8304 | 0.75 |
182
+ | 0.0039 | 130.0 | 130 | 0.8306 | 0.75 |
183
+ | 0.0039 | 131.0 | 131 | 0.8305 | 0.75 |
184
+ | 0.0039 | 132.0 | 132 | 0.8301 | 0.75 |
185
+ | 0.0039 | 133.0 | 133 | 0.8296 | 0.7812 |
186
+ | 0.0039 | 134.0 | 134 | 0.8292 | 0.7812 |
187
+ | 0.0039 | 135.0 | 135 | 0.8283 | 0.7812 |
188
+ | 0.0039 | 136.0 | 136 | 0.8272 | 0.7812 |
189
+ | 0.0039 | 137.0 | 137 | 0.8259 | 0.7812 |
190
+ | 0.0039 | 138.0 | 138 | 0.8247 | 0.7812 |
191
+ | 0.0039 | 139.0 | 139 | 0.8237 | 0.75 |
192
+ | 0.0032 | 140.0 | 140 | 0.8228 | 0.75 |
193
+ | 0.0032 | 141.0 | 141 | 0.8222 | 0.75 |
194
+ | 0.0032 | 142.0 | 142 | 0.8222 | 0.75 |
195
+ | 0.0032 | 143.0 | 143 | 0.8220 | 0.75 |
196
+ | 0.0032 | 144.0 | 144 | 0.8220 | 0.75 |
197
+ | 0.0032 | 145.0 | 145 | 0.8218 | 0.75 |
198
+ | 0.0032 | 146.0 | 146 | 0.8217 | 0.75 |
199
+ | 0.0032 | 147.0 | 147 | 0.8218 | 0.75 |
200
+ | 0.0032 | 148.0 | 148 | 0.8222 | 0.75 |
201
+ | 0.0032 | 149.0 | 149 | 0.8228 | 0.75 |
202
+ | 0.0028 | 150.0 | 150 | 0.8234 | 0.75 |
203
 
204
 
205
  ### Framework versions