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arabert_cross_relevance_task3_fold5

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  1. README.md +87 -92
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@@ -3,20 +3,20 @@ base_model: aubmindlab/bert-base-arabertv02
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  tags:
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  - generated_from_trainer
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  model-index:
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- - name: arabert_cross_relevance_task3_fold4
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  results: []
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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  should probably proofread and complete it, then remove this comment. -->
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- # arabert_cross_relevance_task3_fold4
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  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2244
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- - Qwk: 0.3147
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- - Mse: 0.2244
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  ## Model description
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@@ -45,93 +45,88 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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- |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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- | No log | 0.1176 | 2 | 0.6247 | 0.1100 | 0.6247 |
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- | No log | 0.2353 | 4 | 0.4274 | 0.2657 | 0.4274 |
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- | No log | 0.3529 | 6 | 0.3933 | 0.3269 | 0.3933 |
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- | No log | 0.4706 | 8 | 0.3251 | 0.1665 | 0.3251 |
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- | No log | 0.5882 | 10 | 0.4511 | 0.2506 | 0.4511 |
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- | No log | 0.7059 | 12 | 0.3380 | 0.2405 | 0.3380 |
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- | No log | 0.8235 | 14 | 0.2594 | 0.1665 | 0.2594 |
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- | No log | 0.9412 | 16 | 0.2948 | 0.2149 | 0.2948 |
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- | No log | 1.0588 | 18 | 0.2980 | 0.2995 | 0.2980 |
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- | No log | 1.1765 | 20 | 0.2541 | 0.2638 | 0.2541 |
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- | No log | 1.2941 | 22 | 0.2285 | 0.2330 | 0.2285 |
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- | No log | 1.4118 | 24 | 0.2279 | 0.2837 | 0.2279 |
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- | No log | 1.5294 | 26 | 0.2347 | 0.2760 | 0.2347 |
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- | No log | 1.6471 | 28 | 0.2414 | 0.3095 | 0.2414 |
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- | No log | 1.7647 | 30 | 0.2534 | 0.3281 | 0.2534 |
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- | No log | 1.8824 | 32 | 0.2613 | 0.3439 | 0.2613 |
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- | No log | 2.0 | 34 | 0.2476 | 0.3483 | 0.2476 |
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- | No log | 2.1176 | 36 | 0.2444 | 0.3210 | 0.2444 |
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- | No log | 2.2353 | 38 | 0.2368 | 0.3126 | 0.2368 |
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- | No log | 2.3529 | 40 | 0.2271 | 0.3358 | 0.2271 |
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- | No log | 2.4706 | 42 | 0.2280 | 0.3354 | 0.2280 |
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- | No log | 2.5882 | 44 | 0.2317 | 0.3468 | 0.2317 |
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- | No log | 2.7059 | 46 | 0.2288 | 0.3795 | 0.2288 |
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- | No log | 2.8235 | 48 | 0.2284 | 0.3808 | 0.2284 |
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- | No log | 2.9412 | 50 | 0.2248 | 0.4119 | 0.2248 |
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- | No log | 3.0588 | 52 | 0.2179 | 0.3948 | 0.2179 |
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- | No log | 3.1765 | 54 | 0.2135 | 0.3797 | 0.2135 |
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- | No log | 3.2941 | 56 | 0.2038 | 0.3300 | 0.2038 |
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- | No log | 3.4118 | 58 | 0.2043 | 0.3232 | 0.2043 |
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- | No log | 3.5294 | 60 | 0.2143 | 0.3534 | 0.2143 |
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- | No log | 3.6471 | 62 | 0.2325 | 0.4158 | 0.2325 |
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- | No log | 3.7647 | 64 | 0.2488 | 0.4475 | 0.2488 |
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- | No log | 3.8824 | 66 | 0.2377 | 0.3842 | 0.2377 |
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- | No log | 4.0 | 68 | 0.2342 | 0.3300 | 0.2342 |
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- | No log | 4.1176 | 70 | 0.2380 | 0.4475 | 0.2380 |
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- | No log | 4.2353 | 72 | 0.2243 | 0.4095 | 0.2243 |
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- | No log | 4.3529 | 74 | 0.2117 | 0.3895 | 0.2117 |
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- | No log | 4.4706 | 76 | 0.2105 | 0.3541 | 0.2105 |
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- | No log | 4.5882 | 78 | 0.2109 | 0.3824 | 0.2109 |
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- | No log | 4.7059 | 80 | 0.2150 | 0.4058 | 0.2150 |
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- | No log | 4.8235 | 82 | 0.2189 | 0.4186 | 0.2189 |
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- | No log | 4.9412 | 84 | 0.2207 | 0.3858 | 0.2207 |
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- | No log | 5.0588 | 86 | 0.2206 | 0.3152 | 0.2206 |
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- | No log | 5.1765 | 88 | 0.2173 | 0.2918 | 0.2173 |
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- | No log | 5.2941 | 90 | 0.2159 | 0.3281 | 0.2159 |
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- | No log | 5.4118 | 92 | 0.2217 | 0.3375 | 0.2217 |
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- | No log | 5.5294 | 94 | 0.2240 | 0.4196 | 0.2240 |
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- | No log | 5.6471 | 96 | 0.2310 | 0.4755 | 0.2310 |
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- | No log | 5.7647 | 98 | 0.2348 | 0.4823 | 0.2348 |
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- | No log | 5.8824 | 100 | 0.2267 | 0.3877 | 0.2267 |
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- | No log | 6.0 | 102 | 0.2189 | 0.3233 | 0.2189 |
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- | No log | 6.1176 | 104 | 0.2198 | 0.3013 | 0.2198 |
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- | No log | 6.2353 | 106 | 0.2188 | 0.3233 | 0.2188 |
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- | No log | 6.3529 | 108 | 0.2193 | 0.3440 | 0.2193 |
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- | No log | 6.4706 | 110 | 0.2212 | 0.3392 | 0.2212 |
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- | No log | 6.5882 | 112 | 0.2240 | 0.3533 | 0.2240 |
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- | No log | 6.7059 | 114 | 0.2234 | 0.4012 | 0.2234 |
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- | No log | 6.8235 | 116 | 0.2253 | 0.3980 | 0.2253 |
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- | No log | 6.9412 | 118 | 0.2273 | 0.3906 | 0.2273 |
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- | No log | 7.0588 | 120 | 0.2269 | 0.4035 | 0.2269 |
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- | No log | 7.1765 | 122 | 0.2251 | 0.3784 | 0.2251 |
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- | No log | 7.2941 | 124 | 0.2253 | 0.4107 | 0.2253 |
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- | No log | 7.4118 | 126 | 0.2255 | 0.3891 | 0.2255 |
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- | No log | 7.5294 | 128 | 0.2218 | 0.3462 | 0.2218 |
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- | No log | 7.6471 | 130 | 0.2198 | 0.3255 | 0.2198 |
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- | No log | 7.7647 | 132 | 0.2206 | 0.3328 | 0.2206 |
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- | No log | 7.8824 | 134 | 0.2204 | 0.3286 | 0.2204 |
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- | No log | 8.0 | 136 | 0.2202 | 0.3416 | 0.2202 |
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- | No log | 8.1176 | 138 | 0.2237 | 0.3458 | 0.2237 |
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- | No log | 8.2353 | 140 | 0.2257 | 0.3529 | 0.2257 |
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- | No log | 8.3529 | 142 | 0.2246 | 0.3433 | 0.2246 |
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- | No log | 8.4706 | 144 | 0.2235 | 0.3464 | 0.2235 |
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- | No log | 8.5882 | 146 | 0.2231 | 0.3396 | 0.2231 |
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- | No log | 8.7059 | 148 | 0.2225 | 0.3328 | 0.2225 |
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- | No log | 8.8235 | 150 | 0.2224 | 0.3119 | 0.2224 |
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- | No log | 8.9412 | 152 | 0.2226 | 0.3159 | 0.2226 |
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- | No log | 9.0588 | 154 | 0.2231 | 0.3205 | 0.2231 |
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- | No log | 9.1765 | 156 | 0.2239 | 0.3275 | 0.2239 |
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- | No log | 9.2941 | 158 | 0.2243 | 0.3275 | 0.2243 |
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- | No log | 9.4118 | 160 | 0.2236 | 0.3147 | 0.2236 |
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- | No log | 9.5294 | 162 | 0.2234 | 0.3080 | 0.2234 |
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- | No log | 9.6471 | 164 | 0.2238 | 0.3080 | 0.2238 |
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- | No log | 9.7647 | 166 | 0.2243 | 0.3080 | 0.2243 |
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- | No log | 9.8824 | 168 | 0.2244 | 0.3147 | 0.2244 |
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- | No log | 10.0 | 170 | 0.2244 | 0.3147 | 0.2244 |
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  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task3_fold5
7
  results: []
8
  ---
9
 
10
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
11
  should probably proofread and complete it, then remove this comment. -->
12
 
13
+ # arabert_cross_relevance_task3_fold5
14
 
15
  This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2278
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+ - Qwk: 0.3503
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+ - Mse: 0.2272
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
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+ | No log | 0.125 | 2 | 0.4369 | 0.2251 | 0.4365 |
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+ | No log | 0.25 | 4 | 0.2909 | 0.1687 | 0.2903 |
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+ | No log | 0.375 | 6 | 0.2730 | 0.2811 | 0.2726 |
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+ | No log | 0.5 | 8 | 0.3037 | 0.3049 | 0.3032 |
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+ | No log | 0.625 | 10 | 0.2562 | 0.2310 | 0.2559 |
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+ | No log | 0.75 | 12 | 0.2376 | 0.3126 | 0.2374 |
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+ | No log | 0.875 | 14 | 0.2395 | 0.3156 | 0.2394 |
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+ | No log | 1.0 | 16 | 0.2207 | 0.3200 | 0.2206 |
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+ | No log | 1.125 | 18 | 0.2110 | 0.3141 | 0.2108 |
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+ | No log | 1.25 | 20 | 0.2044 | 0.3240 | 0.2042 |
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+ | No log | 1.375 | 22 | 0.1940 | 0.3474 | 0.1939 |
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+ | No log | 1.5 | 24 | 0.1935 | 0.3423 | 0.1934 |
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+ | No log | 1.625 | 26 | 0.1971 | 0.3465 | 0.1970 |
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+ | No log | 1.75 | 28 | 0.1987 | 0.3444 | 0.1987 |
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+ | No log | 1.875 | 30 | 0.1940 | 0.3650 | 0.1939 |
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+ | No log | 2.0 | 32 | 0.1935 | 0.3667 | 0.1934 |
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+ | No log | 2.125 | 34 | 0.1905 | 0.3581 | 0.1903 |
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+ | No log | 2.25 | 36 | 0.1874 | 0.3617 | 0.1872 |
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+ | No log | 2.375 | 38 | 0.1955 | 0.3549 | 0.1954 |
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+ | No log | 2.5 | 40 | 0.1888 | 0.3513 | 0.1887 |
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+ | No log | 2.625 | 42 | 0.1910 | 0.3504 | 0.1908 |
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+ | No log | 2.75 | 44 | 0.1989 | 0.3557 | 0.1987 |
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+ | No log | 2.875 | 46 | 0.1822 | 0.3658 | 0.1820 |
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+ | No log | 3.0 | 48 | 0.1794 | 0.3695 | 0.1792 |
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+ | No log | 3.125 | 50 | 0.1806 | 0.3586 | 0.1804 |
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+ | No log | 3.25 | 52 | 0.1801 | 0.3642 | 0.1799 |
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+ | No log | 3.375 | 54 | 0.1932 | 0.3566 | 0.1930 |
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+ | No log | 3.5 | 56 | 0.1965 | 0.3665 | 0.1964 |
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+ | No log | 3.625 | 58 | 0.1835 | 0.3933 | 0.1832 |
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+ | No log | 3.75 | 60 | 0.1823 | 0.4014 | 0.1821 |
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+ | No log | 3.875 | 62 | 0.1810 | 0.3904 | 0.1808 |
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+ | No log | 4.0 | 64 | 0.1812 | 0.3641 | 0.1809 |
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+ | No log | 4.125 | 66 | 0.1872 | 0.3508 | 0.1869 |
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+ | No log | 4.25 | 68 | 0.1876 | 0.3444 | 0.1873 |
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+ | No log | 4.375 | 70 | 0.1871 | 0.3465 | 0.1869 |
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+ | No log | 4.5 | 72 | 0.1839 | 0.3476 | 0.1836 |
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+ | No log | 4.625 | 74 | 0.1851 | 0.3502 | 0.1848 |
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+ | No log | 4.75 | 76 | 0.1995 | 0.3556 | 0.1992 |
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+ | No log | 4.875 | 78 | 0.2297 | 0.3406 | 0.2295 |
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+ | No log | 5.0 | 80 | 0.2197 | 0.3527 | 0.2195 |
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+ | No log | 5.125 | 82 | 0.2076 | 0.3687 | 0.2074 |
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+ | No log | 5.25 | 84 | 0.2032 | 0.3594 | 0.2029 |
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+ | No log | 5.375 | 86 | 0.1949 | 0.3789 | 0.1946 |
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+ | No log | 5.5 | 88 | 0.1891 | 0.3720 | 0.1888 |
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+ | No log | 5.625 | 90 | 0.1897 | 0.3616 | 0.1894 |
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+ | No log | 5.75 | 92 | 0.2058 | 0.3531 | 0.2054 |
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+ | No log | 5.875 | 94 | 0.2551 | 0.3116 | 0.2547 |
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+ | No log | 6.0 | 96 | 0.2912 | 0.2956 | 0.2910 |
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+ | No log | 6.125 | 98 | 0.2694 | 0.3103 | 0.2690 |
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+ | No log | 6.25 | 100 | 0.2180 | 0.3539 | 0.2176 |
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+ | No log | 6.375 | 102 | 0.1895 | 0.3898 | 0.1891 |
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+ | No log | 6.5 | 104 | 0.1849 | 0.3916 | 0.1845 |
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+ | No log | 6.625 | 106 | 0.1941 | 0.3673 | 0.1936 |
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+ | No log | 6.75 | 108 | 0.2121 | 0.3477 | 0.2117 |
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+ | No log | 6.875 | 110 | 0.2249 | 0.3320 | 0.2245 |
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+ | No log | 7.0 | 112 | 0.2260 | 0.3320 | 0.2256 |
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+ | No log | 7.125 | 114 | 0.2089 | 0.3539 | 0.2085 |
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+ | No log | 7.25 | 116 | 0.1910 | 0.3665 | 0.1905 |
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+ | No log | 7.375 | 118 | 0.1866 | 0.3736 | 0.1861 |
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+ | No log | 7.5 | 120 | 0.1896 | 0.3689 | 0.1891 |
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+ | No log | 7.625 | 122 | 0.2002 | 0.3543 | 0.1997 |
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+ | No log | 7.75 | 124 | 0.2193 | 0.3459 | 0.2188 |
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+ | No log | 7.875 | 126 | 0.2204 | 0.3441 | 0.2200 |
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+ | No log | 8.0 | 128 | 0.2176 | 0.3432 | 0.2171 |
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+ | No log | 8.125 | 130 | 0.2102 | 0.3423 | 0.2097 |
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+ | No log | 8.25 | 132 | 0.2052 | 0.3459 | 0.2046 |
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+ | No log | 8.375 | 134 | 0.1977 | 0.3634 | 0.1972 |
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+ | No log | 8.5 | 136 | 0.1998 | 0.3555 | 0.1993 |
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+ | No log | 8.625 | 138 | 0.2030 | 0.3505 | 0.2024 |
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+ | No log | 8.75 | 140 | 0.2003 | 0.3581 | 0.1998 |
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+ | No log | 8.875 | 142 | 0.2002 | 0.3589 | 0.1996 |
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+ | No log | 9.0 | 144 | 0.2005 | 0.3559 | 0.2000 |
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+ | No log | 9.125 | 146 | 0.2054 | 0.3522 | 0.2048 |
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+ | No log | 9.25 | 148 | 0.2092 | 0.3477 | 0.2086 |
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+ | No log | 9.375 | 150 | 0.2149 | 0.3495 | 0.2144 |
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+ | No log | 9.5 | 152 | 0.2218 | 0.3503 | 0.2213 |
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+ | No log | 9.625 | 154 | 0.2252 | 0.3503 | 0.2246 |
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+ | No log | 9.75 | 156 | 0.2286 | 0.3459 | 0.2280 |
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+ | No log | 9.875 | 158 | 0.2281 | 0.3459 | 0.2276 |
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+ | No log | 10.0 | 160 | 0.2278 | 0.3503 | 0.2272 |
 
 
 
 
 
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  ### Framework versions