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best_model-yelp_polarity-32-100

Text Classification
Transformers
PyTorch
albert
Generated from Trainer
Inference Endpoints
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  ---
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- license: mit
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- base_model: roberta-base
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -15,10 +15,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # best_model-yelp_polarity-32-100
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- This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4649
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- - Accuracy: 0.9531
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  ## Model description
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@@ -50,156 +50,156 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
52
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
53
- | No log | 1.0 | 2 | 0.4546 | 0.9531 |
54
- | No log | 2.0 | 4 | 0.4598 | 0.9531 |
55
- | No log | 3.0 | 6 | 0.4661 | 0.9531 |
56
- | No log | 4.0 | 8 | 0.4814 | 0.9375 |
57
- | 0.5203 | 5.0 | 10 | 0.4985 | 0.9375 |
58
- | 0.5203 | 6.0 | 12 | 0.5179 | 0.9375 |
59
- | 0.5203 | 7.0 | 14 | 0.5372 | 0.9375 |
60
- | 0.5203 | 8.0 | 16 | 0.5624 | 0.9375 |
61
- | 0.5203 | 9.0 | 18 | 0.5780 | 0.9375 |
62
- | 0.5493 | 10.0 | 20 | 0.6019 | 0.9375 |
63
- | 0.5493 | 11.0 | 22 | 0.6239 | 0.9375 |
64
- | 0.5493 | 12.0 | 24 | 0.6582 | 0.9219 |
65
- | 0.5493 | 13.0 | 26 | 0.7018 | 0.9219 |
66
- | 0.5493 | 14.0 | 28 | 0.7868 | 0.9062 |
67
- | 0.4311 | 15.0 | 30 | 0.8397 | 0.9062 |
68
- | 0.4311 | 16.0 | 32 | 0.8642 | 0.9062 |
69
- | 0.4311 | 17.0 | 34 | 0.8456 | 0.9062 |
70
- | 0.4311 | 18.0 | 36 | 0.7841 | 0.9062 |
71
- | 0.4311 | 19.0 | 38 | 0.6959 | 0.9062 |
72
- | 0.3814 | 20.0 | 40 | 0.6684 | 0.9062 |
73
- | 0.3814 | 21.0 | 42 | 0.6086 | 0.9219 |
74
- | 0.3814 | 22.0 | 44 | 0.5737 | 0.9375 |
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- | 0.3814 | 23.0 | 46 | 0.5216 | 0.9375 |
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- | 0.3814 | 24.0 | 48 | 0.4856 | 0.9375 |
77
- | 0.3304 | 25.0 | 50 | 0.4508 | 0.9531 |
78
- | 0.3304 | 26.0 | 52 | 0.4121 | 0.9531 |
79
- | 0.3304 | 27.0 | 54 | 0.3536 | 0.9531 |
80
- | 0.3304 | 28.0 | 56 | 0.2920 | 0.9688 |
81
- | 0.3304 | 29.0 | 58 | 0.2699 | 0.9688 |
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- | 0.2882 | 30.0 | 60 | 0.2532 | 0.9688 |
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- | 0.2882 | 31.0 | 62 | 0.2417 | 0.9688 |
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- | 0.2882 | 32.0 | 64 | 0.2335 | 0.9688 |
85
- | 0.2882 | 33.0 | 66 | 0.2233 | 0.9688 |
86
- | 0.2882 | 34.0 | 68 | 0.2204 | 0.9688 |
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- | 0.0526 | 35.0 | 70 | 0.2195 | 0.9688 |
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- | 0.0526 | 36.0 | 72 | 0.2246 | 0.9688 |
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- | 0.0526 | 37.0 | 74 | 0.2375 | 0.9688 |
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- | 0.0526 | 38.0 | 76 | 0.2515 | 0.9688 |
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- | 0.0526 | 39.0 | 78 | 0.2652 | 0.9688 |
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- | 0.0054 | 40.0 | 80 | 0.2865 | 0.9531 |
93
- | 0.0054 | 41.0 | 82 | 0.3170 | 0.9531 |
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- | 0.0054 | 42.0 | 84 | 0.3356 | 0.9531 |
95
- | 0.0054 | 43.0 | 86 | 0.3346 | 0.9531 |
96
- | 0.0054 | 44.0 | 88 | 0.3329 | 0.9531 |
97
- | 0.0011 | 45.0 | 90 | 0.3320 | 0.9531 |
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- | 0.0011 | 46.0 | 92 | 0.3160 | 0.9531 |
99
- | 0.0011 | 47.0 | 94 | 0.3016 | 0.9531 |
100
- | 0.0011 | 48.0 | 96 | 0.2909 | 0.9688 |
101
- | 0.0011 | 49.0 | 98 | 0.2851 | 0.9688 |
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- | 0.0003 | 50.0 | 100 | 0.2829 | 0.9688 |
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- | 0.0003 | 51.0 | 102 | 0.2822 | 0.9688 |
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- | 0.0003 | 52.0 | 104 | 0.2822 | 0.9688 |
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- | 0.0003 | 53.0 | 106 | 0.2827 | 0.9688 |
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- | 0.0003 | 54.0 | 108 | 0.2836 | 0.9688 |
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- | 0.0001 | 55.0 | 110 | 0.2852 | 0.9688 |
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- | 0.0001 | 56.0 | 112 | 0.2871 | 0.9688 |
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- | 0.0001 | 57.0 | 114 | 0.2892 | 0.9688 |
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- | 0.0001 | 58.0 | 116 | 0.2920 | 0.9688 |
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- | 0.0001 | 59.0 | 118 | 0.2965 | 0.9688 |
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- | 0.0001 | 60.0 | 120 | 0.3036 | 0.9688 |
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- | 0.0001 | 61.0 | 122 | 0.3120 | 0.9531 |
114
- | 0.0001 | 62.0 | 124 | 0.3212 | 0.9531 |
115
- | 0.0001 | 63.0 | 126 | 0.3298 | 0.9531 |
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- | 0.0001 | 64.0 | 128 | 0.3377 | 0.9531 |
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- | 0.0001 | 65.0 | 130 | 0.3450 | 0.9531 |
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- | 0.0001 | 66.0 | 132 | 0.3513 | 0.9531 |
119
- | 0.0001 | 67.0 | 134 | 0.3585 | 0.9531 |
120
- | 0.0001 | 68.0 | 136 | 0.3646 | 0.9531 |
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- | 0.0001 | 69.0 | 138 | 0.3696 | 0.9531 |
122
- | 0.0001 | 70.0 | 140 | 0.3741 | 0.9531 |
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- | 0.0001 | 71.0 | 142 | 0.3783 | 0.9531 |
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- | 0.0001 | 72.0 | 144 | 0.3819 | 0.9531 |
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- | 0.0001 | 73.0 | 146 | 0.3852 | 0.9531 |
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- | 0.0001 | 74.0 | 148 | 0.3873 | 0.9531 |
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- | 0.0001 | 75.0 | 150 | 0.3896 | 0.9531 |
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- | 0.0001 | 76.0 | 152 | 0.3912 | 0.9531 |
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- | 0.0001 | 77.0 | 154 | 0.3921 | 0.9531 |
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- | 0.0001 | 78.0 | 156 | 0.3928 | 0.9531 |
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- | 0.0001 | 79.0 | 158 | 0.3933 | 0.9531 |
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- | 0.0 | 80.0 | 160 | 0.3939 | 0.9531 |
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- | 0.0 | 81.0 | 162 | 0.3949 | 0.9531 |
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- | 0.0 | 82.0 | 164 | 0.3961 | 0.9531 |
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- | 0.0 | 83.0 | 166 | 0.3973 | 0.9531 |
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- | 0.0 | 84.0 | 168 | 0.3989 | 0.9531 |
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- | 0.0 | 85.0 | 170 | 0.4004 | 0.9531 |
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- | 0.0 | 86.0 | 172 | 0.4020 | 0.9531 |
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- | 0.0 | 87.0 | 174 | 0.4036 | 0.9531 |
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- | 0.0 | 88.0 | 176 | 0.4052 | 0.9531 |
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- | 0.0 | 89.0 | 178 | 0.4067 | 0.9531 |
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- | 0.0 | 90.0 | 180 | 0.4084 | 0.9531 |
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- | 0.0 | 91.0 | 182 | 0.4101 | 0.9531 |
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- | 0.0 | 92.0 | 184 | 0.4118 | 0.9531 |
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- | 0.0 | 93.0 | 186 | 0.4135 | 0.9531 |
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- | 0.0 | 94.0 | 188 | 0.4149 | 0.9531 |
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- | 0.0 | 95.0 | 190 | 0.4163 | 0.9531 |
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- | 0.0 | 96.0 | 192 | 0.4176 | 0.9531 |
149
- | 0.0 | 97.0 | 194 | 0.4189 | 0.9531 |
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- | 0.0 | 98.0 | 196 | 0.4204 | 0.9531 |
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- | 0.0 | 99.0 | 198 | 0.4218 | 0.9531 |
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- | 0.0 | 100.0 | 200 | 0.4232 | 0.9531 |
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- | 0.0 | 101.0 | 202 | 0.4246 | 0.9531 |
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- | 0.0 | 102.0 | 204 | 0.4261 | 0.9531 |
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- | 0.0 | 103.0 | 206 | 0.4277 | 0.9531 |
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- | 0.0 | 104.0 | 208 | 0.4291 | 0.9531 |
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- | 0.0 | 105.0 | 210 | 0.4304 | 0.9531 |
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- | 0.0 | 106.0 | 212 | 0.4315 | 0.9531 |
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- | 0.0 | 107.0 | 214 | 0.4327 | 0.9531 |
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- | 0.0 | 108.0 | 216 | 0.4339 | 0.9531 |
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- | 0.0 | 109.0 | 218 | 0.4350 | 0.9531 |
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- | 0.0 | 110.0 | 220 | 0.4362 | 0.9531 |
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- | 0.0 | 111.0 | 222 | 0.4373 | 0.9531 |
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- | 0.0 | 112.0 | 224 | 0.4381 | 0.9531 |
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- | 0.0 | 113.0 | 226 | 0.4391 | 0.9531 |
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- | 0.0 | 114.0 | 228 | 0.4400 | 0.9531 |
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- | 0.0 | 115.0 | 230 | 0.4410 | 0.9531 |
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- | 0.0 | 116.0 | 232 | 0.4421 | 0.9531 |
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- | 0.0 | 117.0 | 234 | 0.4432 | 0.9531 |
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- | 0.0 | 118.0 | 236 | 0.4443 | 0.9531 |
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- | 0.0 | 119.0 | 238 | 0.4453 | 0.9531 |
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- | 0.0 | 120.0 | 240 | 0.4467 | 0.9531 |
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- | 0.0 | 121.0 | 242 | 0.4479 | 0.9531 |
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- | 0.0 | 122.0 | 244 | 0.4489 | 0.9531 |
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- | 0.0 | 123.0 | 246 | 0.4498 | 0.9531 |
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- | 0.0 | 124.0 | 248 | 0.4507 | 0.9531 |
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- | 0.0 | 125.0 | 250 | 0.4514 | 0.9531 |
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- | 0.0 | 126.0 | 252 | 0.4521 | 0.9531 |
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- | 0.0 | 127.0 | 254 | 0.4528 | 0.9531 |
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- | 0.0 | 128.0 | 256 | 0.4534 | 0.9531 |
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- | 0.0 | 129.0 | 258 | 0.4540 | 0.9531 |
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- | 0.0 | 130.0 | 260 | 0.4547 | 0.9531 |
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- | 0.0 | 131.0 | 262 | 0.4553 | 0.9531 |
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- | 0.0 | 132.0 | 264 | 0.4560 | 0.9531 |
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- | 0.0 | 133.0 | 266 | 0.4567 | 0.9531 |
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- | 0.0 | 134.0 | 268 | 0.4574 | 0.9531 |
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- | 0.0 | 135.0 | 270 | 0.4580 | 0.9531 |
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- | 0.0 | 136.0 | 272 | 0.4584 | 0.9531 |
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- | 0.0 | 137.0 | 274 | 0.4589 | 0.9531 |
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- | 0.0 | 138.0 | 276 | 0.4594 | 0.9531 |
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- | 0.0 | 139.0 | 278 | 0.4597 | 0.9531 |
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- | 0.0 | 140.0 | 280 | 0.4602 | 0.9531 |
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- | 0.0 | 141.0 | 282 | 0.4607 | 0.9531 |
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- | 0.0 | 142.0 | 284 | 0.4612 | 0.9531 |
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- | 0.0 | 143.0 | 286 | 0.4616 | 0.9531 |
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- | 0.0 | 144.0 | 288 | 0.4621 | 0.9531 |
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- | 0.0 | 145.0 | 290 | 0.4625 | 0.9531 |
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- | 0.0 | 146.0 | 292 | 0.4630 | 0.9531 |
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- | 0.0 | 147.0 | 294 | 0.4635 | 0.9531 |
200
- | 0.0 | 148.0 | 296 | 0.4640 | 0.9531 |
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- | 0.0 | 149.0 | 298 | 0.4644 | 0.9531 |
202
- | 0.0 | 150.0 | 300 | 0.4649 | 0.9531 |
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  ### Framework versions
 
1
  ---
2
+ license: apache-2.0
3
+ base_model: albert-base-v2
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  tags:
5
  - generated_from_trainer
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  metrics:
 
15
 
16
  # best_model-yelp_polarity-32-100
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: 0.6759
21
+ - Accuracy: 0.9219
22
 
23
  ## Model description
24
 
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 1.0 | 2 | 0.6263 | 0.9219 |
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+ | No log | 2.0 | 4 | 0.6212 | 0.9375 |
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+ | No log | 3.0 | 6 | 0.6183 | 0.9375 |
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+ | No log | 4.0 | 8 | 0.6196 | 0.9375 |
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+ | 0.3722 | 5.0 | 10 | 0.6224 | 0.9375 |
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+ | 0.3722 | 6.0 | 12 | 0.6235 | 0.9219 |
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+ | 0.3722 | 7.0 | 14 | 0.6204 | 0.9375 |
60
+ | 0.3722 | 8.0 | 16 | 0.6164 | 0.9375 |
61
+ | 0.3722 | 9.0 | 18 | 0.6145 | 0.9375 |
62
+ | 0.3647 | 10.0 | 20 | 0.6147 | 0.9375 |
63
+ | 0.3647 | 11.0 | 22 | 0.6156 | 0.9375 |
64
+ | 0.3647 | 12.0 | 24 | 0.6168 | 0.9375 |
65
+ | 0.3647 | 13.0 | 26 | 0.6201 | 0.9219 |
66
+ | 0.3647 | 14.0 | 28 | 0.6271 | 0.9219 |
67
+ | 0.3406 | 15.0 | 30 | 0.6346 | 0.9219 |
68
+ | 0.3406 | 16.0 | 32 | 0.6356 | 0.9219 |
69
+ | 0.3406 | 17.0 | 34 | 0.6223 | 0.9219 |
70
+ | 0.3406 | 18.0 | 36 | 0.6258 | 0.9219 |
71
+ | 0.3406 | 19.0 | 38 | 0.6385 | 0.9219 |
72
+ | 0.2674 | 20.0 | 40 | 0.6640 | 0.9219 |
73
+ | 0.2674 | 21.0 | 42 | 0.6955 | 0.9219 |
74
+ | 0.2674 | 22.0 | 44 | 0.7032 | 0.9219 |
75
+ | 0.2674 | 23.0 | 46 | 0.7005 | 0.9219 |
76
+ | 0.2674 | 24.0 | 48 | 0.6918 | 0.9219 |
77
+ | 0.1287 | 25.0 | 50 | 0.6602 | 0.9219 |
78
+ | 0.1287 | 26.0 | 52 | 0.6141 | 0.9219 |
79
+ | 0.1287 | 27.0 | 54 | 0.5937 | 0.8906 |
80
+ | 0.1287 | 28.0 | 56 | 0.5987 | 0.9062 |
81
+ | 0.1287 | 29.0 | 58 | 0.6046 | 0.8906 |
82
+ | 0.0668 | 30.0 | 60 | 0.5944 | 0.8906 |
83
+ | 0.0668 | 31.0 | 62 | 0.5954 | 0.8906 |
84
+ | 0.0668 | 32.0 | 64 | 0.5907 | 0.9062 |
85
+ | 0.0668 | 33.0 | 66 | 0.5787 | 0.9062 |
86
+ | 0.0668 | 34.0 | 68 | 0.5778 | 0.9062 |
87
+ | 0.0463 | 35.0 | 70 | 0.5876 | 0.9062 |
88
+ | 0.0463 | 36.0 | 72 | 0.6117 | 0.9219 |
89
+ | 0.0463 | 37.0 | 74 | 0.6575 | 0.9219 |
90
+ | 0.0463 | 38.0 | 76 | 0.6886 | 0.9219 |
91
+ | 0.0463 | 39.0 | 78 | 0.7052 | 0.9219 |
92
+ | 0.0233 | 40.0 | 80 | 0.7125 | 0.9219 |
93
+ | 0.0233 | 41.0 | 82 | 0.7227 | 0.9219 |
94
+ | 0.0233 | 42.0 | 84 | 0.7260 | 0.9219 |
95
+ | 0.0233 | 43.0 | 86 | 0.7399 | 0.9219 |
96
+ | 0.0233 | 44.0 | 88 | 0.7464 | 0.9219 |
97
+ | 0.0012 | 45.0 | 90 | 0.7493 | 0.9219 |
98
+ | 0.0012 | 46.0 | 92 | 0.7494 | 0.9219 |
99
+ | 0.0012 | 47.0 | 94 | 0.7478 | 0.9219 |
100
+ | 0.0012 | 48.0 | 96 | 0.7453 | 0.9219 |
101
+ | 0.0012 | 49.0 | 98 | 0.7420 | 0.9219 |
102
+ | 0.0001 | 50.0 | 100 | 0.7381 | 0.9219 |
103
+ | 0.0001 | 51.0 | 102 | 0.7340 | 0.9219 |
104
+ | 0.0001 | 52.0 | 104 | 0.7297 | 0.9219 |
105
+ | 0.0001 | 53.0 | 106 | 0.7253 | 0.9219 |
106
+ | 0.0001 | 54.0 | 108 | 0.7210 | 0.9219 |
107
+ | 0.0 | 55.0 | 110 | 0.7168 | 0.9219 |
108
+ | 0.0 | 56.0 | 112 | 0.7128 | 0.9219 |
109
+ | 0.0 | 57.0 | 114 | 0.7090 | 0.9219 |
110
+ | 0.0 | 58.0 | 116 | 0.7054 | 0.9219 |
111
+ | 0.0 | 59.0 | 118 | 0.7020 | 0.9219 |
112
+ | 0.0 | 60.0 | 120 | 0.6989 | 0.9219 |
113
+ | 0.0 | 61.0 | 122 | 0.6961 | 0.9219 |
114
+ | 0.0 | 62.0 | 124 | 0.6934 | 0.9219 |
115
+ | 0.0 | 63.0 | 126 | 0.6909 | 0.9219 |
116
+ | 0.0 | 64.0 | 128 | 0.6887 | 0.9219 |
117
+ | 0.0 | 65.0 | 130 | 0.6865 | 0.9219 |
118
+ | 0.0 | 66.0 | 132 | 0.6846 | 0.9219 |
119
+ | 0.0 | 67.0 | 134 | 0.6827 | 0.9219 |
120
+ | 0.0 | 68.0 | 136 | 0.6811 | 0.9219 |
121
+ | 0.0 | 69.0 | 138 | 0.6795 | 0.9219 |
122
+ | 0.0 | 70.0 | 140 | 0.6780 | 0.9219 |
123
+ | 0.0 | 71.0 | 142 | 0.6766 | 0.9219 |
124
+ | 0.0 | 72.0 | 144 | 0.6754 | 0.9219 |
125
+ | 0.0 | 73.0 | 146 | 0.6742 | 0.9219 |
126
+ | 0.0 | 74.0 | 148 | 0.6731 | 0.9219 |
127
+ | 0.0 | 75.0 | 150 | 0.6721 | 0.9219 |
128
+ | 0.0 | 76.0 | 152 | 0.6711 | 0.9219 |
129
+ | 0.0 | 77.0 | 154 | 0.6702 | 0.9219 |
130
+ | 0.0 | 78.0 | 156 | 0.6693 | 0.9219 |
131
+ | 0.0 | 79.0 | 158 | 0.6685 | 0.9219 |
132
+ | 0.0 | 80.0 | 160 | 0.6677 | 0.9219 |
133
+ | 0.0 | 81.0 | 162 | 0.6670 | 0.9219 |
134
+ | 0.0 | 82.0 | 164 | 0.6664 | 0.9219 |
135
+ | 0.0 | 83.0 | 166 | 0.6658 | 0.9219 |
136
+ | 0.0 | 84.0 | 168 | 0.6653 | 0.9219 |
137
+ | 0.0 | 85.0 | 170 | 0.6648 | 0.9219 |
138
+ | 0.0 | 86.0 | 172 | 0.6644 | 0.9219 |
139
+ | 0.0 | 87.0 | 174 | 0.6641 | 0.9062 |
140
+ | 0.0 | 88.0 | 176 | 0.6638 | 0.9062 |
141
+ | 0.0 | 89.0 | 178 | 0.6635 | 0.9062 |
142
+ | 0.0 | 90.0 | 180 | 0.6633 | 0.9062 |
143
+ | 0.0 | 91.0 | 182 | 0.6631 | 0.9062 |
144
+ | 0.0 | 92.0 | 184 | 0.6629 | 0.9062 |
145
+ | 0.0 | 93.0 | 186 | 0.6628 | 0.9062 |
146
+ | 0.0 | 94.0 | 188 | 0.6628 | 0.9062 |
147
+ | 0.0 | 95.0 | 190 | 0.6627 | 0.9062 |
148
+ | 0.0 | 96.0 | 192 | 0.6627 | 0.9062 |
149
+ | 0.0 | 97.0 | 194 | 0.6627 | 0.9062 |
150
+ | 0.0 | 98.0 | 196 | 0.6627 | 0.9062 |
151
+ | 0.0 | 99.0 | 198 | 0.6628 | 0.9062 |
152
+ | 0.0 | 100.0 | 200 | 0.6628 | 0.9062 |
153
+ | 0.0 | 101.0 | 202 | 0.6629 | 0.9062 |
154
+ | 0.0 | 102.0 | 204 | 0.6629 | 0.9062 |
155
+ | 0.0 | 103.0 | 206 | 0.6630 | 0.9062 |
156
+ | 0.0 | 104.0 | 208 | 0.6632 | 0.9062 |
157
+ | 0.0 | 105.0 | 210 | 0.6633 | 0.9062 |
158
+ | 0.0 | 106.0 | 212 | 0.6634 | 0.9219 |
159
+ | 0.0 | 107.0 | 214 | 0.6636 | 0.9219 |
160
+ | 0.0 | 108.0 | 216 | 0.6638 | 0.9219 |
161
+ | 0.0 | 109.0 | 218 | 0.6640 | 0.9219 |
162
+ | 0.0 | 110.0 | 220 | 0.6642 | 0.9219 |
163
+ | 0.0 | 111.0 | 222 | 0.6644 | 0.9219 |
164
+ | 0.0 | 112.0 | 224 | 0.6646 | 0.9219 |
165
+ | 0.0 | 113.0 | 226 | 0.6648 | 0.9219 |
166
+ | 0.0 | 114.0 | 228 | 0.6650 | 0.9219 |
167
+ | 0.0 | 115.0 | 230 | 0.6653 | 0.9219 |
168
+ | 0.0 | 116.0 | 232 | 0.6656 | 0.9219 |
169
+ | 0.0 | 117.0 | 234 | 0.6659 | 0.9219 |
170
+ | 0.0 | 118.0 | 236 | 0.6661 | 0.9219 |
171
+ | 0.0 | 119.0 | 238 | 0.6664 | 0.9219 |
172
+ | 0.0 | 120.0 | 240 | 0.6667 | 0.9219 |
173
+ | 0.0 | 121.0 | 242 | 0.6670 | 0.9219 |
174
+ | 0.0 | 122.0 | 244 | 0.6672 | 0.9219 |
175
+ | 0.0 | 123.0 | 246 | 0.6675 | 0.9219 |
176
+ | 0.0 | 124.0 | 248 | 0.6679 | 0.9219 |
177
+ | 0.0 | 125.0 | 250 | 0.6681 | 0.9219 |
178
+ | 0.0 | 126.0 | 252 | 0.6684 | 0.9219 |
179
+ | 0.0 | 127.0 | 254 | 0.6687 | 0.9219 |
180
+ | 0.0 | 128.0 | 256 | 0.6691 | 0.9219 |
181
+ | 0.0 | 129.0 | 258 | 0.6694 | 0.9219 |
182
+ | 0.0 | 130.0 | 260 | 0.6698 | 0.9219 |
183
+ | 0.0 | 131.0 | 262 | 0.6702 | 0.9219 |
184
+ | 0.0 | 132.0 | 264 | 0.6706 | 0.9219 |
185
+ | 0.0 | 133.0 | 266 | 0.6709 | 0.9219 |
186
+ | 0.0 | 134.0 | 268 | 0.6712 | 0.9219 |
187
+ | 0.0 | 135.0 | 270 | 0.6716 | 0.9219 |
188
+ | 0.0 | 136.0 | 272 | 0.6719 | 0.9219 |
189
+ | 0.0 | 137.0 | 274 | 0.6722 | 0.9219 |
190
+ | 0.0 | 138.0 | 276 | 0.6725 | 0.9219 |
191
+ | 0.0 | 139.0 | 278 | 0.6727 | 0.9219 |
192
+ | 0.0 | 140.0 | 280 | 0.6730 | 0.9219 |
193
+ | 0.0 | 141.0 | 282 | 0.6732 | 0.9219 |
194
+ | 0.0 | 142.0 | 284 | 0.6734 | 0.9219 |
195
+ | 0.0 | 143.0 | 286 | 0.6737 | 0.9219 |
196
+ | 0.0 | 144.0 | 288 | 0.6740 | 0.9219 |
197
+ | 0.0 | 145.0 | 290 | 0.6744 | 0.9219 |
198
+ | 0.0 | 146.0 | 292 | 0.6747 | 0.9219 |
199
+ | 0.0 | 147.0 | 294 | 0.6750 | 0.9219 |
200
+ | 0.0 | 148.0 | 296 | 0.6753 | 0.9219 |
201
+ | 0.0 | 149.0 | 298 | 0.6757 | 0.9219 |
202
+ | 0.0 | 150.0 | 300 | 0.6759 | 0.9219 |
203
 
204
 
205
  ### Framework versions