Hugging Face's logo

simonycl
/
best_model-yelp_polarity-16-100

Text Classification
Transformers
PyTorch
albert
Generated from Trainer
Inference Endpoints
Model card Files Community
1
simonycl commited on
Commit
9ed96be
·
1 Parent(s): 97e6283

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-16-100
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: 0.3649
21
- - Accuracy: 0.9375
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 | 0.4545 | 0.9375 |
54
- | No log | 2.0 | 2 | 0.4554 | 0.9375 |
55
- | No log | 3.0 | 3 | 0.4547 | 0.9375 |
56
- | No log | 4.0 | 4 | 0.4527 | 0.9375 |
57
- | No log | 5.0 | 5 | 0.4500 | 0.9375 |
58
- | No log | 6.0 | 6 | 0.4459 | 0.9375 |
59
- | No log | 7.0 | 7 | 0.4399 | 0.9375 |
60
- | No log | 8.0 | 8 | 0.4325 | 0.9375 |
61
- | No log | 9.0 | 9 | 0.4229 | 0.9375 |
62
- | 0.0615 | 10.0 | 10 | 0.4163 | 0.9375 |
63
- | 0.0615 | 11.0 | 11 | 0.4128 | 0.9375 |
64
- | 0.0615 | 12.0 | 12 | 0.4064 | 0.9375 |
65
- | 0.0615 | 13.0 | 13 | 0.3967 | 0.9375 |
66
- | 0.0615 | 14.0 | 14 | 0.3834 | 0.9375 |
67
- | 0.0615 | 15.0 | 15 | 0.3664 | 0.9375 |
68
- | 0.0615 | 16.0 | 16 | 0.3437 | 0.9375 |
69
- | 0.0615 | 17.0 | 17 | 0.3272 | 0.9375 |
70
- | 0.0615 | 18.0 | 18 | 0.3177 | 0.9375 |
71
- | 0.0615 | 19.0 | 19 | 0.3141 | 0.9375 |
72
- | 0.0434 | 20.0 | 20 | 0.3169 | 0.9375 |
73
- | 0.0434 | 21.0 | 21 | 0.3263 | 0.9375 |
74
- | 0.0434 | 22.0 | 22 | 0.3365 | 0.9375 |
75
- | 0.0434 | 23.0 | 23 | 0.3472 | 0.9375 |
76
- | 0.0434 | 24.0 | 24 | 0.3639 | 0.9375 |
77
- | 0.0434 | 25.0 | 25 | 0.3799 | 0.9375 |
78
- | 0.0434 | 26.0 | 26 | 0.3938 | 0.9375 |
79
- | 0.0434 | 27.0 | 27 | 0.4059 | 0.9375 |
80
- | 0.0434 | 28.0 | 28 | 0.4103 | 0.9375 |
81
- | 0.0434 | 29.0 | 29 | 0.4072 | 0.9375 |
82
- | 0.0006 | 30.0 | 30 | 0.4046 | 0.9375 |
83
- | 0.0006 | 31.0 | 31 | 0.4023 | 0.9375 |
84
- | 0.0006 | 32.0 | 32 | 0.4003 | 0.9375 |
85
- | 0.0006 | 33.0 | 33 | 0.3990 | 0.9375 |
86
- | 0.0006 | 34.0 | 34 | 0.3979 | 0.9375 |
87
- | 0.0006 | 35.0 | 35 | 0.3969 | 0.9375 |
88
- | 0.0006 | 36.0 | 36 | 0.3961 | 0.9375 |
89
- | 0.0006 | 37.0 | 37 | 0.3955 | 0.9375 |
90
- | 0.0006 | 38.0 | 38 | 0.3951 | 0.9375 |
91
- | 0.0006 | 39.0 | 39 | 0.3954 | 0.9375 |
92
- | 0.0003 | 40.0 | 40 | 0.3960 | 0.9375 |
93
- | 0.0003 | 41.0 | 41 | 0.3961 | 0.9375 |
94
- | 0.0003 | 42.0 | 42 | 0.3949 | 0.9375 |
95
- | 0.0003 | 43.0 | 43 | 0.3912 | 0.9375 |
96
- | 0.0003 | 44.0 | 44 | 0.3875 | 0.9375 |
97
- | 0.0003 | 45.0 | 45 | 0.3851 | 0.9375 |
98
- | 0.0003 | 46.0 | 46 | 0.3833 | 0.9375 |
99
- | 0.0003 | 47.0 | 47 | 0.3822 | 0.9375 |
100
- | 0.0003 | 48.0 | 48 | 0.3812 | 0.9375 |
101
- | 0.0003 | 49.0 | 49 | 0.3807 | 0.9375 |
102
- | 0.0003 | 50.0 | 50 | 0.3805 | 0.9375 |
103
- | 0.0003 | 51.0 | 51 | 0.3807 | 0.9375 |
104
- | 0.0003 | 52.0 | 52 | 0.3812 | 0.9375 |
105
- | 0.0003 | 53.0 | 53 | 0.3820 | 0.9375 |
106
- | 0.0003 | 54.0 | 54 | 0.3830 | 0.9375 |
107
- | 0.0003 | 55.0 | 55 | 0.3841 | 0.9375 |
108
- | 0.0003 | 56.0 | 56 | 0.3859 | 0.9375 |
109
- | 0.0003 | 57.0 | 57 | 0.3885 | 0.9375 |
110
- | 0.0003 | 58.0 | 58 | 0.3923 | 0.9375 |
111
- | 0.0003 | 59.0 | 59 | 0.3958 | 0.9375 |
112
- | 0.0003 | 60.0 | 60 | 0.3992 | 0.9375 |
113
- | 0.0003 | 61.0 | 61 | 0.4026 | 0.9375 |
114
- | 0.0003 | 62.0 | 62 | 0.4059 | 0.9375 |
115
- | 0.0003 | 63.0 | 63 | 0.4093 | 0.9375 |
116
- | 0.0003 | 64.0 | 64 | 0.4125 | 0.9375 |
117
- | 0.0003 | 65.0 | 65 | 0.4152 | 0.9375 |
118
- | 0.0003 | 66.0 | 66 | 0.4179 | 0.9375 |
119
- | 0.0003 | 67.0 | 67 | 0.4207 | 0.9375 |
120
- | 0.0003 | 68.0 | 68 | 0.4234 | 0.9375 |
121
- | 0.0003 | 69.0 | 69 | 0.4291 | 0.9375 |
122
- | 0.0002 | 70.0 | 70 | 0.4345 | 0.9375 |
123
- | 0.0002 | 71.0 | 71 | 0.4392 | 0.9375 |
124
- | 0.0002 | 72.0 | 72 | 0.4434 | 0.9375 |
125
- | 0.0002 | 73.0 | 73 | 0.4568 | 0.9375 |
126
- | 0.0002 | 74.0 | 74 | 0.4678 | 0.9375 |
127
- | 0.0002 | 75.0 | 75 | 0.4775 | 0.9375 |
128
- | 0.0002 | 76.0 | 76 | 0.4831 | 0.9375 |
129
- | 0.0002 | 77.0 | 77 | 0.4880 | 0.9375 |
130
- | 0.0002 | 78.0 | 78 | 0.4925 | 0.9375 |
131
- | 0.0002 | 79.0 | 79 | 0.4964 | 0.9375 |
132
- | 0.0002 | 80.0 | 80 | 0.4984 | 0.9375 |
133
- | 0.0002 | 81.0 | 81 | 0.4999 | 0.9375 |
134
- | 0.0002 | 82.0 | 82 | 0.5013 | 0.9375 |
135
- | 0.0002 | 83.0 | 83 | 0.5027 | 0.9375 |
136
- | 0.0002 | 84.0 | 84 | 0.5039 | 0.9375 |
137
- | 0.0002 | 85.0 | 85 | 0.5050 | 0.9375 |
138
- | 0.0002 | 86.0 | 86 | 0.5061 | 0.9375 |
139
- | 0.0002 | 87.0 | 87 | 0.5071 | 0.9375 |
140
- | 0.0002 | 88.0 | 88 | 0.5081 | 0.9375 |
141
- | 0.0002 | 89.0 | 89 | 0.5090 | 0.9375 |
142
- | 0.0002 | 90.0 | 90 | 0.5099 | 0.9375 |
143
- | 0.0002 | 91.0 | 91 | 0.5102 | 0.9375 |
144
- | 0.0002 | 92.0 | 92 | 0.5105 | 0.9375 |
145
- | 0.0002 | 93.0 | 93 | 0.5109 | 0.9375 |
146
- | 0.0002 | 94.0 | 94 | 0.5114 | 0.9375 |
147
- | 0.0002 | 95.0 | 95 | 0.5115 | 0.9375 |
148
- | 0.0002 | 96.0 | 96 | 0.5117 | 0.9375 |
149
- | 0.0002 | 97.0 | 97 | 0.4927 | 0.9375 |
150
- | 0.0002 | 98.0 | 98 | 0.4685 | 0.9375 |
151
- | 0.0002 | 99.0 | 99 | 0.4380 | 0.9375 |
152
- | 0.0003 | 100.0 | 100 | 0.4010 | 0.9375 |
153
- | 0.0003 | 101.0 | 101 | 0.3594 | 0.9375 |
154
- | 0.0003 | 102.0 | 102 | 0.3201 | 0.9375 |
155
- | 0.0003 | 103.0 | 103 | 0.2908 | 0.9375 |
156
- | 0.0003 | 104.0 | 104 | 0.2745 | 0.9688 |
157
- | 0.0003 | 105.0 | 105 | 0.2665 | 0.9688 |
158
- | 0.0003 | 106.0 | 106 | 0.2624 | 0.9688 |
159
- | 0.0003 | 107.0 | 107 | 0.2597 | 0.9688 |
160
- | 0.0003 | 108.0 | 108 | 0.2575 | 0.9688 |
161
- | 0.0003 | 109.0 | 109 | 0.2558 | 0.9688 |
162
- | 0.0002 | 110.0 | 110 | 0.2544 | 0.9688 |
163
- | 0.0002 | 111.0 | 111 | 0.2531 | 0.9688 |
164
- | 0.0002 | 112.0 | 112 | 0.2521 | 0.9688 |
165
- | 0.0002 | 113.0 | 113 | 0.2513 | 0.9688 |
166
- | 0.0002 | 114.0 | 114 | 0.2506 | 0.9688 |
167
- | 0.0002 | 115.0 | 115 | 0.2502 | 0.9688 |
168
- | 0.0002 | 116.0 | 116 | 0.2501 | 0.9688 |
169
- | 0.0002 | 117.0 | 117 | 0.2500 | 0.9688 |
170
- | 0.0002 | 118.0 | 118 | 0.2501 | 0.9688 |
171
- | 0.0002 | 119.0 | 119 | 0.2503 | 0.9688 |
172
- | 0.0001 | 120.0 | 120 | 0.2505 | 0.9688 |
173
- | 0.0001 | 121.0 | 121 | 0.2532 | 0.9688 |
174
- | 0.0001 | 122.0 | 122 | 0.2560 | 0.9688 |
175
- | 0.0001 | 123.0 | 123 | 0.2585 | 0.9688 |
176
- | 0.0001 | 124.0 | 124 | 0.2608 | 0.9688 |
177
- | 0.0001 | 125.0 | 125 | 0.2630 | 0.9688 |
178
- | 0.0001 | 126.0 | 126 | 0.2654 | 0.9688 |
179
- | 0.0001 | 127.0 | 127 | 0.2676 | 0.9688 |
180
- | 0.0001 | 128.0 | 128 | 0.2696 | 0.9688 |
181
- | 0.0001 | 129.0 | 129 | 0.2717 | 0.9688 |
182
- | 0.0002 | 130.0 | 130 | 0.2737 | 0.9688 |
183
- | 0.0002 | 131.0 | 131 | 0.2759 | 0.9688 |
184
- | 0.0002 | 132.0 | 132 | 0.2783 | 0.9688 |
185
- | 0.0002 | 133.0 | 133 | 0.2808 | 0.9688 |
186
- | 0.0002 | 134.0 | 134 | 0.2837 | 0.9688 |
187
- | 0.0002 | 135.0 | 135 | 0.2871 | 0.9688 |
188
- | 0.0002 | 136.0 | 136 | 0.2908 | 0.9688 |
189
- | 0.0002 | 137.0 | 137 | 0.2950 | 0.9688 |
190
- | 0.0002 | 138.0 | 138 | 0.2995 | 0.9688 |
191
- | 0.0002 | 139.0 | 139 | 0.3043 | 0.9375 |
192
- | 0.0001 | 140.0 | 140 | 0.3094 | 0.9375 |
193
- | 0.0001 | 141.0 | 141 | 0.3147 | 0.9375 |
194
- | 0.0001 | 142.0 | 142 | 0.3201 | 0.9375 |
195
- | 0.0001 | 143.0 | 143 | 0.3257 | 0.9375 |
196
- | 0.0001 | 144.0 | 144 | 0.3316 | 0.9375 |
197
- | 0.0001 | 145.0 | 145 | 0.3375 | 0.9375 |
198
- | 0.0001 | 146.0 | 146 | 0.3434 | 0.9375 |
199
- | 0.0001 | 147.0 | 147 | 0.3492 | 0.9375 |
200
- | 0.0001 | 148.0 | 148 | 0.3547 | 0.9375 |
201
- | 0.0001 | 149.0 | 149 | 0.3599 | 0.9375 |
202
- | 0.0001 | 150.0 | 150 | 0.3649 | 0.9375 |
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-16-100
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: 1.1862
21
+ - Accuracy: 0.8125
22
 
23
  ## Model description
24
 
 
50
 
51
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
52
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
53
+ | No log | 1.0 | 1 | 1.0619 | 0.8438 |
54
+ | No log | 2.0 | 2 | 1.0610 | 0.8438 |
55
+ | No log | 3.0 | 3 | 1.0591 | 0.8438 |
56
+ | No log | 4.0 | 4 | 1.0563 | 0.8438 |
57
+ | No log | 5.0 | 5 | 1.0524 | 0.8438 |
58
+ | No log | 6.0 | 6 | 1.0473 | 0.8438 |
59
+ | No log | 7.0 | 7 | 1.0408 | 0.8438 |
60
+ | No log | 8.0 | 8 | 1.0325 | 0.8438 |
61
+ | No log | 9.0 | 9 | 1.0221 | 0.8438 |
62
+ | 0.5215 | 10.0 | 10 | 1.0093 | 0.8438 |
63
+ | 0.5215 | 11.0 | 11 | 0.9939 | 0.8438 |
64
+ | 0.5215 | 12.0 | 12 | 0.9775 | 0.8438 |
65
+ | 0.5215 | 13.0 | 13 | 0.9630 | 0.8438 |
66
+ | 0.5215 | 14.0 | 14 | 0.9517 | 0.8438 |
67
+ | 0.5215 | 15.0 | 15 | 0.9431 | 0.8125 |
68
+ | 0.5215 | 16.0 | 16 | 0.9352 | 0.7812 |
69
+ | 0.5215 | 17.0 | 17 | 0.9263 | 0.7812 |
70
+ | 0.5215 | 18.0 | 18 | 0.9195 | 0.7812 |
71
+ | 0.5215 | 19.0 | 19 | 0.9178 | 0.7812 |
72
+ | 0.3945 | 20.0 | 20 | 0.9230 | 0.8125 |
73
+ | 0.3945 | 21.0 | 21 | 0.9374 | 0.8125 |
74
+ | 0.3945 | 22.0 | 22 | 0.9628 | 0.8125 |
75
+ | 0.3945 | 23.0 | 23 | 1.0035 | 0.8438 |
76
+ | 0.3945 | 24.0 | 24 | 1.0608 | 0.8125 |
77
+ | 0.3945 | 25.0 | 25 | 1.1258 | 0.8125 |
78
+ | 0.3945 | 26.0 | 26 | 1.1859 | 0.8125 |
79
+ | 0.3945 | 27.0 | 27 | 1.2311 | 0.8125 |
80
+ | 0.3945 | 28.0 | 28 | 1.2580 | 0.8125 |
81
+ | 0.3945 | 29.0 | 29 | 1.2702 | 0.8125 |
82
+ | 0.2334 | 30.0 | 30 | 1.2750 | 0.8125 |
83
+ | 0.2334 | 31.0 | 31 | 1.2763 | 0.8125 |
84
+ | 0.2334 | 32.0 | 32 | 1.2763 | 0.8125 |
85
+ | 0.2334 | 33.0 | 33 | 1.2757 | 0.8125 |
86
+ | 0.2334 | 34.0 | 34 | 1.2733 | 0.8125 |
87
+ | 0.2334 | 35.0 | 35 | 1.2687 | 0.8125 |
88
+ | 0.2334 | 36.0 | 36 | 1.2612 | 0.8125 |
89
+ | 0.2334 | 37.0 | 37 | 1.2508 | 0.8125 |
90
+ | 0.2334 | 38.0 | 38 | 1.2376 | 0.8125 |
91
+ | 0.2334 | 39.0 | 39 | 1.2213 | 0.8125 |
92
+ | 0.024 | 40.0 | 40 | 1.2024 | 0.8125 |
93
+ | 0.024 | 41.0 | 41 | 1.1803 | 0.8125 |
94
+ | 0.024 | 42.0 | 42 | 1.1548 | 0.8125 |
95
+ | 0.024 | 43.0 | 43 | 1.1254 | 0.8125 |
96
+ | 0.024 | 44.0 | 44 | 1.0929 | 0.8125 |
97
+ | 0.024 | 45.0 | 45 | 1.0591 | 0.8125 |
98
+ | 0.024 | 46.0 | 46 | 1.0257 | 0.8125 |
99
+ | 0.024 | 47.0 | 47 | 0.9942 | 0.8125 |
100
+ | 0.024 | 48.0 | 48 | 0.9662 | 0.8125 |
101
+ | 0.024 | 49.0 | 49 | 0.9436 | 0.8125 |
102
+ | 0.0008 | 50.0 | 50 | 0.9266 | 0.8125 |
103
+ | 0.0008 | 51.0 | 51 | 0.9148 | 0.8125 |
104
+ | 0.0008 | 52.0 | 52 | 0.9073 | 0.8125 |
105
+ | 0.0008 | 53.0 | 53 | 0.9039 | 0.8125 |
106
+ | 0.0008 | 54.0 | 54 | 0.9049 | 0.8125 |
107
+ | 0.0008 | 55.0 | 55 | 0.9087 | 0.8125 |
108
+ | 0.0008 | 56.0 | 56 | 0.9152 | 0.8125 |
109
+ | 0.0008 | 57.0 | 57 | 0.9238 | 0.8125 |
110
+ | 0.0008 | 58.0 | 58 | 0.9340 | 0.8125 |
111
+ | 0.0008 | 59.0 | 59 | 0.9450 | 0.8125 |
112
+ | 0.0006 | 60.0 | 60 | 0.9566 | 0.8438 |
113
+ | 0.0006 | 61.0 | 61 | 0.9682 | 0.8438 |
114
+ | 0.0006 | 62.0 | 62 | 0.9797 | 0.8438 |
115
+ | 0.0006 | 63.0 | 63 | 0.9912 | 0.8438 |
116
+ | 0.0006 | 64.0 | 64 | 1.0028 | 0.8438 |
117
+ | 0.0006 | 65.0 | 65 | 1.0141 | 0.8438 |
118
+ | 0.0006 | 66.0 | 66 | 1.0251 | 0.8438 |
119
+ | 0.0006 | 67.0 | 67 | 1.0358 | 0.8438 |
120
+ | 0.0006 | 68.0 | 68 | 1.0460 | 0.8438 |
121
+ | 0.0006 | 69.0 | 69 | 1.0558 | 0.8438 |
122
+ | 0.0005 | 70.0 | 70 | 1.0646 | 0.8438 |
123
+ | 0.0005 | 71.0 | 71 | 1.0730 | 0.8438 |
124
+ | 0.0005 | 72.0 | 72 | 1.0808 | 0.8438 |
125
+ | 0.0005 | 73.0 | 73 | 1.0882 | 0.8438 |
126
+ | 0.0005 | 74.0 | 74 | 1.0951 | 0.8438 |
127
+ | 0.0005 | 75.0 | 75 | 1.1013 | 0.8125 |
128
+ | 0.0005 | 76.0 | 76 | 1.1070 | 0.8125 |
129
+ | 0.0005 | 77.0 | 77 | 1.1122 | 0.8125 |
130
+ | 0.0005 | 78.0 | 78 | 1.1170 | 0.8125 |
131
+ | 0.0005 | 79.0 | 79 | 1.1214 | 0.8125 |
132
+ | 0.0004 | 80.0 | 80 | 1.1255 | 0.8125 |
133
+ | 0.0004 | 81.0 | 81 | 1.1292 | 0.8125 |
134
+ | 0.0004 | 82.0 | 82 | 1.1324 | 0.8125 |
135
+ | 0.0004 | 83.0 | 83 | 1.1354 | 0.8125 |
136
+ | 0.0004 | 84.0 | 84 | 1.1383 | 0.8125 |
137
+ | 0.0004 | 85.0 | 85 | 1.1411 | 0.8125 |
138
+ | 0.0004 | 86.0 | 86 | 1.1437 | 0.8125 |
139
+ | 0.0004 | 87.0 | 87 | 1.1462 | 0.8125 |
140
+ | 0.0004 | 88.0 | 88 | 1.1484 | 0.8125 |
141
+ | 0.0004 | 89.0 | 89 | 1.1506 | 0.8125 |
142
+ | 0.0004 | 90.0 | 90 | 1.1527 | 0.8125 |
143
+ | 0.0004 | 91.0 | 91 | 1.1546 | 0.8125 |
144
+ | 0.0004 | 92.0 | 92 | 1.1563 | 0.8125 |
145
+ | 0.0004 | 93.0 | 93 | 1.1579 | 0.8125 |
146
+ | 0.0004 | 94.0 | 94 | 1.1596 | 0.8125 |
147
+ | 0.0004 | 95.0 | 95 | 1.1611 | 0.8125 |
148
+ | 0.0004 | 96.0 | 96 | 1.1624 | 0.8125 |
149
+ | 0.0004 | 97.0 | 97 | 1.1636 | 0.8125 |
150
+ | 0.0004 | 98.0 | 98 | 1.1648 | 0.8125 |
151
+ | 0.0004 | 99.0 | 99 | 1.1658 | 0.8125 |
152
+ | 0.0003 | 100.0 | 100 | 1.1668 | 0.8125 |
153
+ | 0.0003 | 101.0 | 101 | 1.1678 | 0.8125 |
154
+ | 0.0003 | 102.0 | 102 | 1.1689 | 0.8125 |
155
+ | 0.0003 | 103.0 | 103 | 1.1697 | 0.8125 |
156
+ | 0.0003 | 104.0 | 104 | 1.1706 | 0.8125 |
157
+ | 0.0003 | 105.0 | 105 | 1.1715 | 0.8125 |
158
+ | 0.0003 | 106.0 | 106 | 1.1722 | 0.8125 |
159
+ | 0.0003 | 107.0 | 107 | 1.1728 | 0.8125 |
160
+ | 0.0003 | 108.0 | 108 | 1.1734 | 0.8125 |
161
+ | 0.0003 | 109.0 | 109 | 1.1739 | 0.8125 |
162
+ | 0.0003 | 110.0 | 110 | 1.1745 | 0.8125 |
163
+ | 0.0003 | 111.0 | 111 | 1.1749 | 0.8125 |
164
+ | 0.0003 | 112.0 | 112 | 1.1754 | 0.8125 |
165
+ | 0.0003 | 113.0 | 113 | 1.1759 | 0.8125 |
166
+ | 0.0003 | 114.0 | 114 | 1.1764 | 0.8125 |
167
+ | 0.0003 | 115.0 | 115 | 1.1768 | 0.8125 |
168
+ | 0.0003 | 116.0 | 116 | 1.1772 | 0.8125 |
169
+ | 0.0003 | 117.0 | 117 | 1.1774 | 0.8125 |
170
+ | 0.0003 | 118.0 | 118 | 1.1776 | 0.8125 |
171
+ | 0.0003 | 119.0 | 119 | 1.1776 | 0.8125 |
172
+ | 0.0003 | 120.0 | 120 | 1.1778 | 0.8125 |
173
+ | 0.0003 | 121.0 | 121 | 1.1780 | 0.8125 |
174
+ | 0.0003 | 122.0 | 122 | 1.1781 | 0.8125 |
175
+ | 0.0003 | 123.0 | 123 | 1.1783 | 0.8125 |
176
+ | 0.0003 | 124.0 | 124 | 1.1784 | 0.8125 |
177
+ | 0.0003 | 125.0 | 125 | 1.1787 | 0.8125 |
178
+ | 0.0003 | 126.0 | 126 | 1.1790 | 0.8125 |
179
+ | 0.0003 | 127.0 | 127 | 1.1794 | 0.8125 |
180
+ | 0.0003 | 128.0 | 128 | 1.1797 | 0.8125 |
181
+ | 0.0003 | 129.0 | 129 | 1.1800 | 0.8125 |
182
+ | 0.0003 | 130.0 | 130 | 1.1803 | 0.8125 |
183
+ | 0.0003 | 131.0 | 131 | 1.1807 | 0.8125 |
184
+ | 0.0003 | 132.0 | 132 | 1.1809 | 0.8125 |
185
+ | 0.0003 | 133.0 | 133 | 1.1812 | 0.8125 |
186
+ | 0.0003 | 134.0 | 134 | 1.1815 | 0.8125 |
187
+ | 0.0003 | 135.0 | 135 | 1.1818 | 0.8125 |
188
+ | 0.0003 | 136.0 | 136 | 1.1823 | 0.8125 |
189
+ | 0.0003 | 137.0 | 137 | 1.1828 | 0.8125 |
190
+ | 0.0003 | 138.0 | 138 | 1.1832 | 0.8125 |
191
+ | 0.0003 | 139.0 | 139 | 1.1835 | 0.8125 |
192
+ | 0.0002 | 140.0 | 140 | 1.1837 | 0.8125 |
193
+ | 0.0002 | 141.0 | 141 | 1.1838 | 0.8125 |
194
+ | 0.0002 | 142.0 | 142 | 1.1840 | 0.8125 |
195
+ | 0.0002 | 143.0 | 143 | 1.1841 | 0.8125 |
196
+ | 0.0002 | 144.0 | 144 | 1.1844 | 0.8125 |
197
+ | 0.0002 | 145.0 | 145 | 1.1845 | 0.8125 |
198
+ | 0.0002 | 146.0 | 146 | 1.1848 | 0.8125 |
199
+ | 0.0002 | 147.0 | 147 | 1.1851 | 0.8125 |
200
+ | 0.0002 | 148.0 | 148 | 1.1855 | 0.8125 |
201
+ | 0.0002 | 149.0 | 149 | 1.1859 | 0.8125 |
202
+ | 0.0002 | 150.0 | 150 | 1.1862 | 0.8125 |
203
 
204
 
205
  ### Framework versions