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detect-femicide-news-xlmr-nl-fft-freeze2

Text Classification
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PyTorch
TensorBoard
xlm-roberta
generated_from_trainer
Inference Endpoints
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@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4112
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  - Accuracy: 0.8571
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  - Precision Neg: 0.85
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  - Precision Pos: 0.875
@@ -54,106 +54,106 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Neg | Precision Pos | Recall Neg | Recall Pos | F1 Score Neg | F1 Score Pos |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:-------------:|:----------:|:----------:|:------------:|:------------:|
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- | 1.2929 | 1.0 | 23 | 1.0782 | 0.75 | 0.7391 | 0.8 | 0.9444 | 0.4 | 0.8293 | 0.5333 |
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- | 1.1345 | 2.0 | 46 | 0.8942 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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- | 0.9799 | 3.0 | 69 | 0.7418 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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- | 0.7871 | 4.0 | 92 | 0.5905 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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- | 0.6852 | 5.0 | 115 | 0.4981 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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- | 0.5988 | 6.0 | 138 | 0.4501 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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- | 0.5976 | 7.0 | 161 | 0.4441 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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- | 0.5877 | 8.0 | 184 | 0.4501 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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- | 0.5621 | 9.0 | 207 | 0.4503 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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- | 0.5658 | 10.0 | 230 | 0.4514 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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- | 0.5648 | 11.0 | 253 | 0.4505 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.559 | 12.0 | 276 | 0.4499 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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- | 0.5668 | 13.0 | 299 | 0.4449 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5542 | 14.0 | 322 | 0.4448 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5496 | 15.0 | 345 | 0.4406 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.555 | 16.0 | 368 | 0.4392 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5479 | 17.0 | 391 | 0.4389 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5487 | 18.0 | 414 | 0.4345 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5529 | 19.0 | 437 | 0.4312 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5439 | 20.0 | 460 | 0.4314 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5444 | 21.0 | 483 | 0.4317 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5322 | 22.0 | 506 | 0.4299 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5314 | 23.0 | 529 | 0.4265 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5286 | 24.0 | 552 | 0.4245 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5395 | 25.0 | 575 | 0.4256 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5419 | 26.0 | 598 | 0.4253 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.55 | 27.0 | 621 | 0.4264 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5525 | 28.0 | 644 | 0.4261 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5465 | 29.0 | 667 | 0.4251 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5304 | 30.0 | 690 | 0.4277 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.541 | 31.0 | 713 | 0.4268 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5344 | 32.0 | 736 | 0.4262 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5316 | 33.0 | 759 | 0.4219 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5415 | 34.0 | 782 | 0.4244 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5419 | 35.0 | 805 | 0.4221 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5284 | 36.0 | 828 | 0.4206 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5472 | 37.0 | 851 | 0.4193 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5172 | 38.0 | 874 | 0.4185 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.522 | 39.0 | 897 | 0.4168 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5261 | 40.0 | 920 | 0.4172 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5246 | 41.0 | 943 | 0.4167 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5249 | 42.0 | 966 | 0.4164 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5229 | 43.0 | 989 | 0.4155 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5144 | 44.0 | 1012 | 0.4155 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.527 | 45.0 | 1035 | 0.4181 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.525 | 46.0 | 1058 | 0.4184 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5258 | 47.0 | 1081 | 0.4167 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5297 | 48.0 | 1104 | 0.4156 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5299 | 49.0 | 1127 | 0.4167 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5273 | 50.0 | 1150 | 0.4167 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5296 | 51.0 | 1173 | 0.4170 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5094 | 52.0 | 1196 | 0.4168 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5171 | 53.0 | 1219 | 0.4167 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5179 | 54.0 | 1242 | 0.4161 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5144 | 55.0 | 1265 | 0.4158 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5452 | 56.0 | 1288 | 0.4141 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5193 | 57.0 | 1311 | 0.4155 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5288 | 58.0 | 1334 | 0.4146 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5343 | 59.0 | 1357 | 0.4139 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5224 | 60.0 | 1380 | 0.4132 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5177 | 61.0 | 1403 | 0.4137 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5299 | 62.0 | 1426 | 0.4146 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5293 | 63.0 | 1449 | 0.4139 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5183 | 64.0 | 1472 | 0.4131 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5124 | 65.0 | 1495 | 0.4132 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5102 | 66.0 | 1518 | 0.4131 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.523 | 67.0 | 1541 | 0.4137 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5142 | 68.0 | 1564 | 0.4135 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5122 | 69.0 | 1587 | 0.4131 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5198 | 70.0 | 1610 | 0.4132 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5195 | 71.0 | 1633 | 0.4133 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5228 | 72.0 | 1656 | 0.4131 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5065 | 73.0 | 1679 | 0.4129 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5174 | 74.0 | 1702 | 0.4118 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5189 | 75.0 | 1725 | 0.4119 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5243 | 76.0 | 1748 | 0.4119 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5102 | 77.0 | 1771 | 0.4128 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5318 | 78.0 | 1794 | 0.4130 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5214 | 79.0 | 1817 | 0.4128 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5163 | 80.0 | 1840 | 0.4133 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5235 | 81.0 | 1863 | 0.4128 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5393 | 82.0 | 1886 | 0.4131 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5284 | 83.0 | 1909 | 0.4128 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5242 | 84.0 | 1932 | 0.4122 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.505 | 85.0 | 1955 | 0.4120 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5211 | 86.0 | 1978 | 0.4120 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5367 | 87.0 | 2001 | 0.4122 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5068 | 88.0 | 2024 | 0.4122 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.51 | 89.0 | 2047 | 0.4119 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5302 | 90.0 | 2070 | 0.4118 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5208 | 91.0 | 2093 | 0.4119 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5199 | 92.0 | 2116 | 0.4119 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5142 | 93.0 | 2139 | 0.4116 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5225 | 94.0 | 2162 | 0.4116 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5123 | 95.0 | 2185 | 0.4116 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5123 | 96.0 | 2208 | 0.4113 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.4929 | 97.0 | 2231 | 0.4114 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5067 | 98.0 | 2254 | 0.4112 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5254 | 99.0 | 2277 | 0.4112 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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- | 0.5131 | 100.0 | 2300 | 0.4112 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4119
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  - Accuracy: 0.8571
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  - Precision Neg: 0.85
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  - Precision Pos: 0.875
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Neg | Precision Pos | Recall Neg | Recall Pos | F1 Score Neg | F1 Score Pos |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:-------------:|:----------:|:----------:|:------------:|:------------:|
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+ | 1.3215 | 1.0 | 23 | 1.0782 | 0.75 | 0.7391 | 0.8 | 0.9444 | 0.4 | 0.8293 | 0.5333 |
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+ | 1.0955 | 2.0 | 46 | 0.9057 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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+ | 0.9344 | 3.0 | 69 | 0.7420 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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+ | 0.8303 | 4.0 | 92 | 0.5952 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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+ | 0.6728 | 5.0 | 115 | 0.5078 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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+ | 0.649 | 6.0 | 138 | 0.4546 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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+ | 0.6008 | 7.0 | 161 | 0.4454 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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+ | 0.5439 | 8.0 | 184 | 0.4495 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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+ | 0.5557 | 9.0 | 207 | 0.4479 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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+ | 0.5637 | 10.0 | 230 | 0.4470 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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+ | 0.5709 | 11.0 | 253 | 0.4500 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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+ | 0.5496 | 12.0 | 276 | 0.4456 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5586 | 13.0 | 299 | 0.4484 | 0.8214 | 0.8095 | 0.8571 | 0.9444 | 0.6 | 0.8718 | 0.7059 |
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+ | 0.562 | 14.0 | 322 | 0.4435 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5555 | 15.0 | 345 | 0.4427 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5449 | 16.0 | 368 | 0.4404 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.555 | 17.0 | 391 | 0.4384 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5541 | 18.0 | 414 | 0.4383 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5463 | 19.0 | 437 | 0.4379 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5548 | 20.0 | 460 | 0.4357 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5365 | 21.0 | 483 | 0.4342 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5473 | 22.0 | 506 | 0.4308 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5467 | 23.0 | 529 | 0.4309 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.543 | 24.0 | 552 | 0.4312 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.543 | 25.0 | 575 | 0.4289 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5309 | 26.0 | 598 | 0.4290 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5406 | 27.0 | 621 | 0.4246 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5295 | 28.0 | 644 | 0.4248 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
85
+ | 0.535 | 29.0 | 667 | 0.4247 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5401 | 30.0 | 690 | 0.4265 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5285 | 31.0 | 713 | 0.4262 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5492 | 32.0 | 736 | 0.4247 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.5473 | 33.0 | 759 | 0.4224 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
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+ | 0.547 | 34.0 | 782 | 0.4250 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
91
+ | 0.5394 | 35.0 | 805 | 0.4280 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
92
+ | 0.5361 | 36.0 | 828 | 0.4247 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
93
+ | 0.5294 | 37.0 | 851 | 0.4238 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
94
+ | 0.5302 | 38.0 | 874 | 0.4236 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
95
+ | 0.5384 | 39.0 | 897 | 0.4215 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
96
+ | 0.5396 | 40.0 | 920 | 0.4209 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
97
+ | 0.5305 | 41.0 | 943 | 0.4192 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
98
+ | 0.5241 | 42.0 | 966 | 0.4204 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
99
+ | 0.5433 | 43.0 | 989 | 0.4190 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
100
+ | 0.5246 | 44.0 | 1012 | 0.4169 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
101
+ | 0.525 | 45.0 | 1035 | 0.4177 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
102
+ | 0.5306 | 46.0 | 1058 | 0.4169 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
103
+ | 0.5228 | 47.0 | 1081 | 0.4167 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
104
+ | 0.5094 | 48.0 | 1104 | 0.4176 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
105
+ | 0.5207 | 49.0 | 1127 | 0.4170 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
106
+ | 0.5087 | 50.0 | 1150 | 0.4169 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
107
+ | 0.5229 | 51.0 | 1173 | 0.4163 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
108
+ | 0.5221 | 52.0 | 1196 | 0.4160 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
109
+ | 0.5147 | 53.0 | 1219 | 0.4166 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
110
+ | 0.524 | 54.0 | 1242 | 0.4157 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
111
+ | 0.5171 | 55.0 | 1265 | 0.4149 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
112
+ | 0.5116 | 56.0 | 1288 | 0.4138 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
113
+ | 0.5373 | 57.0 | 1311 | 0.4139 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
114
+ | 0.5274 | 58.0 | 1334 | 0.4131 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
115
+ | 0.5375 | 59.0 | 1357 | 0.4133 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
116
+ | 0.528 | 60.0 | 1380 | 0.4136 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
117
+ | 0.5282 | 61.0 | 1403 | 0.4147 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
118
+ | 0.528 | 62.0 | 1426 | 0.4142 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
119
+ | 0.5357 | 63.0 | 1449 | 0.4132 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
120
+ | 0.5177 | 64.0 | 1472 | 0.4132 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
121
+ | 0.5358 | 65.0 | 1495 | 0.4133 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
122
+ | 0.5224 | 66.0 | 1518 | 0.4124 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
123
+ | 0.5121 | 67.0 | 1541 | 0.4125 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
124
+ | 0.5394 | 68.0 | 1564 | 0.4137 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
125
+ | 0.52 | 69.0 | 1587 | 0.4140 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
126
+ | 0.5103 | 70.0 | 1610 | 0.4131 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
127
+ | 0.5224 | 71.0 | 1633 | 0.4134 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
128
+ | 0.5351 | 72.0 | 1656 | 0.4129 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
129
+ | 0.5181 | 73.0 | 1679 | 0.4138 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
130
+ | 0.532 | 74.0 | 1702 | 0.4139 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
131
+ | 0.5216 | 75.0 | 1725 | 0.4142 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
132
+ | 0.5083 | 76.0 | 1748 | 0.4138 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
133
+ | 0.531 | 77.0 | 1771 | 0.4132 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
134
+ | 0.5245 | 78.0 | 1794 | 0.4125 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
135
+ | 0.5191 | 79.0 | 1817 | 0.4127 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
136
+ | 0.516 | 80.0 | 1840 | 0.4126 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
137
+ | 0.5098 | 81.0 | 1863 | 0.4128 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
138
+ | 0.5173 | 82.0 | 1886 | 0.4127 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
139
+ | 0.5119 | 83.0 | 1909 | 0.4129 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
140
+ | 0.5296 | 84.0 | 1932 | 0.4125 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
141
+ | 0.5105 | 85.0 | 1955 | 0.4131 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
142
+ | 0.5108 | 86.0 | 1978 | 0.4124 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
143
+ | 0.5156 | 87.0 | 2001 | 0.4125 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
144
+ | 0.5143 | 88.0 | 2024 | 0.4124 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
145
+ | 0.5099 | 89.0 | 2047 | 0.4122 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
146
+ | 0.5163 | 90.0 | 2070 | 0.4120 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
147
+ | 0.5224 | 91.0 | 2093 | 0.4118 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
148
+ | 0.4936 | 92.0 | 2116 | 0.4120 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
149
+ | 0.5236 | 93.0 | 2139 | 0.4118 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
150
+ | 0.5261 | 94.0 | 2162 | 0.4118 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
151
+ | 0.5134 | 95.0 | 2185 | 0.4119 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
152
+ | 0.5064 | 96.0 | 2208 | 0.4118 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
153
+ | 0.5072 | 97.0 | 2231 | 0.4118 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
154
+ | 0.5264 | 98.0 | 2254 | 0.4118 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
155
+ | 0.5344 | 99.0 | 2277 | 0.4118 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
156
+ | 0.522 | 100.0 | 2300 | 0.4119 | 0.8571 | 0.85 | 0.875 | 0.9444 | 0.7 | 0.8947 | 0.7778 |
157
 
158
 
159
  ### Framework versions