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arabert_cross_relevance_task2_fold3

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  1. README.md +95 -38
  2. model.safetensors +1 -1
  3. runs/Sep02_02-03-55_a09311c9b42d/events.out.tfevents.1725242637.a09311c9b42d.22.0 +3 -0
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  8. runs/Sep02_02-27-39_a09311c9b42d/events.out.tfevents.1725244717.a09311c9b42d.22.5 +3 -0
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  14. runs/Sep02_03-03-13_a09311c9b42d/events.out.tfevents.1725246944.a09311c9b42d.22.11 +3 -0
  15. runs/Sep02_03-15-45_a09311c9b42d/events.out.tfevents.1725246946.a09311c9b42d.22.12 +3 -0
  16. runs/Sep02_03-15-45_a09311c9b42d/events.out.tfevents.1725247646.a09311c9b42d.22.13 +3 -0
  17. runs/Sep02_03-27-28_a09311c9b42d/events.out.tfevents.1725247649.a09311c9b42d.22.14 +3 -0
  18. runs/Sep02_03-27-28_a09311c9b42d/events.out.tfevents.1725248407.a09311c9b42d.22.15 +3 -0
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  23. runs/Sep02_04-02-37_a09311c9b42d/events.out.tfevents.1725249758.a09311c9b42d.22.20 +3 -0
  24. training_args.bin +1 -1
README.md CHANGED
@@ -3,20 +3,20 @@ base_model: aubmindlab/bert-base-arabertv02
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  tags:
4
  - generated_from_trainer
5
  model-index:
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- - name: arabert_cross_relevance_task2_fold3
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  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_task2_fold3
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.
16
  It achieves the following results on the evaluation set:
17
- - Loss: 0.2961
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- - Qwk: 0.3277
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- - Mse: 0.2961
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  ## Model description
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@@ -36,45 +36,102 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 2e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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  - seed: 42
42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 1
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46
  ### Training results
47
 
48
- | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
49
- |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
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- | No log | 0.0351 | 2 | 1.1621 | 0.0229 | 1.1621 |
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- | No log | 0.0702 | 4 | 0.5340 | 0.1841 | 0.5340 |
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- | No log | 0.1053 | 6 | 0.5506 | 0.1500 | 0.5506 |
53
- | No log | 0.1404 | 8 | 0.5057 | 0.1888 | 0.5057 |
54
- | No log | 0.1754 | 10 | 0.4434 | 0.1993 | 0.4434 |
55
- | No log | 0.2105 | 12 | 0.4171 | 0.2214 | 0.4171 |
56
- | No log | 0.2456 | 14 | 0.3762 | 0.2316 | 0.3762 |
57
- | No log | 0.2807 | 16 | 0.3295 | 0.2935 | 0.3295 |
58
- | No log | 0.3158 | 18 | 0.3210 | 0.2948 | 0.3210 |
59
- | No log | 0.3509 | 20 | 0.3093 | 0.2948 | 0.3093 |
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- | No log | 0.3860 | 22 | 0.3105 | 0.3062 | 0.3105 |
61
- | No log | 0.4211 | 24 | 0.3464 | 0.3679 | 0.3464 |
62
- | No log | 0.4561 | 26 | 0.3981 | 0.6151 | 0.3981 |
63
- | No log | 0.4912 | 28 | 0.3851 | 0.6021 | 0.3851 |
64
- | No log | 0.5263 | 30 | 0.3431 | 0.4831 | 0.3431 |
65
- | No log | 0.5614 | 32 | 0.3017 | 0.3166 | 0.3017 |
66
- | No log | 0.5965 | 34 | 0.2863 | 0.3277 | 0.2863 |
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- | No log | 0.6316 | 36 | 0.2906 | 0.3407 | 0.2906 |
68
- | No log | 0.6667 | 38 | 0.2981 | 0.3509 | 0.2981 |
69
- | No log | 0.7018 | 40 | 0.2999 | 0.3509 | 0.2999 |
70
- | No log | 0.7368 | 42 | 0.2988 | 0.3391 | 0.2988 |
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- | No log | 0.7719 | 44 | 0.2970 | 0.3148 | 0.2970 |
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- | No log | 0.8070 | 46 | 0.2972 | 0.3126 | 0.2972 |
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- | No log | 0.8421 | 48 | 0.2982 | 0.3126 | 0.2982 |
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- | No log | 0.8772 | 50 | 0.2966 | 0.3158 | 0.2966 |
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- | No log | 0.9123 | 52 | 0.2961 | 0.3277 | 0.2961 |
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- | No log | 0.9474 | 54 | 0.2957 | 0.3286 | 0.2957 |
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- | No log | 0.9825 | 56 | 0.2961 | 0.3277 | 0.2961 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
78
 
79
 
80
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task2_fold2
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_task2_fold2
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.
16
  It achieves the following results on the evaluation set:
17
+ - Loss: 0.6695
18
+ - Qwk: 0.0252
19
+ - Mse: 0.6695
20
 
21
  ## Model description
22
 
 
36
 
37
  The following hyperparameters were used during training:
38
  - learning_rate: 2e-05
39
+ - train_batch_size: 64
40
+ - eval_batch_size: 64
41
  - seed: 42
42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
43
  - lr_scheduler_type: linear
44
+ - num_epochs: 10
45
 
46
  ### Training results
47
 
48
+ | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
49
+ |:-------------:|:------:|:----:|:---------------:|:-------:|:------:|
50
+ | No log | 0.1176 | 2 | 0.3996 | 0.0319 | 0.3996 |
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+ | No log | 0.2353 | 4 | 0.4069 | 0.0909 | 0.4069 |
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+ | No log | 0.3529 | 6 | 0.3579 | -0.0167 | 0.3579 |
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+ | No log | 0.4706 | 8 | 0.3710 | 0.0 | 0.3710 |
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+ | No log | 0.5882 | 10 | 0.3188 | -0.0235 | 0.3188 |
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+ | No log | 0.7059 | 12 | 0.3518 | -0.1194 | 0.3518 |
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+ | No log | 0.8235 | 14 | 0.3275 | -0.0616 | 0.3275 |
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+ | No log | 0.9412 | 16 | 0.3104 | 0.0 | 0.3104 |
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+ | No log | 1.0588 | 18 | 0.3535 | 0.0 | 0.3535 |
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+ | No log | 1.1765 | 20 | 0.3752 | 0.0 | 0.3752 |
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+ | No log | 1.2941 | 22 | 0.3373 | 0.0 | 0.3373 |
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+ | No log | 1.4118 | 24 | 0.3102 | 0.0 | 0.3102 |
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+ | No log | 1.5294 | 26 | 0.2963 | 0.0 | 0.2963 |
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+ | No log | 1.6471 | 28 | 0.2934 | 0.0 | 0.2934 |
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+ | No log | 1.7647 | 30 | 0.2889 | 0.0 | 0.2889 |
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+ | No log | 1.8824 | 32 | 0.2810 | 0.0 | 0.2810 |
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+ | No log | 2.0 | 34 | 0.2866 | -0.0235 | 0.2866 |
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+ | No log | 2.1176 | 36 | 0.3061 | 0.0068 | 0.3061 |
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+ | No log | 2.2353 | 38 | 0.3392 | -0.0433 | 0.3392 |
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+ | No log | 2.3529 | 40 | 0.3020 | -0.0034 | 0.3020 |
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+ | No log | 2.4706 | 42 | 0.2698 | -0.0235 | 0.2698 |
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+ | No log | 2.5882 | 44 | 0.2696 | -0.0235 | 0.2696 |
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+ | No log | 2.7059 | 46 | 0.2745 | -0.0235 | 0.2745 |
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+ | No log | 2.8235 | 48 | 0.2757 | -0.0235 | 0.2757 |
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+ | No log | 2.9412 | 50 | 0.3094 | 0.0 | 0.3094 |
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+ | No log | 3.0588 | 52 | 0.3116 | 0.0 | 0.3116 |
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+ | No log | 3.1765 | 54 | 0.2780 | 0.0 | 0.2780 |
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+ | No log | 3.2941 | 56 | 0.2758 | -0.0235 | 0.2758 |
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+ | No log | 3.4118 | 58 | 0.2767 | -0.0235 | 0.2767 |
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+ | No log | 3.5294 | 60 | 0.2717 | -0.0235 | 0.2717 |
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+ | No log | 3.6471 | 62 | 0.2957 | 0.0 | 0.2957 |
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+ | No log | 3.7647 | 64 | 0.3009 | 0.0 | 0.3009 |
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+ | No log | 3.8824 | 66 | 0.2803 | 0.0 | 0.2803 |
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+ | No log | 4.0 | 68 | 0.2754 | -0.0235 | 0.2754 |
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+ | No log | 4.1176 | 70 | 0.2758 | -0.0235 | 0.2758 |
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+ | No log | 4.2353 | 72 | 0.2948 | -0.0235 | 0.2948 |
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+ | No log | 4.3529 | 74 | 0.3207 | 0.0 | 0.3207 |
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+ | No log | 4.4706 | 76 | 0.3204 | 0.0 | 0.3204 |
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+ | No log | 4.5882 | 78 | 0.2864 | -0.0235 | 0.2864 |
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+ | No log | 4.7059 | 80 | 0.2756 | -0.0235 | 0.2756 |
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+ | No log | 4.8235 | 82 | 0.2778 | -0.0235 | 0.2778 |
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+ | No log | 4.9412 | 84 | 0.2766 | -0.0235 | 0.2766 |
92
+ | No log | 5.0588 | 86 | 0.2988 | -0.0235 | 0.2988 |
93
+ | No log | 5.1765 | 88 | 0.3889 | 0.0224 | 0.3889 |
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+ | No log | 5.2941 | 90 | 0.4631 | 0.0123 | 0.4631 |
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+ | No log | 5.4118 | 92 | 0.4091 | 0.0224 | 0.4091 |
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+ | No log | 5.5294 | 94 | 0.3390 | -0.0235 | 0.3390 |
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+ | No log | 5.6471 | 96 | 0.3069 | -0.0235 | 0.3069 |
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+ | No log | 5.7647 | 98 | 0.3133 | -0.0235 | 0.3133 |
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+ | No log | 5.8824 | 100 | 0.3527 | -0.0235 | 0.3527 |
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+ | No log | 6.0 | 102 | 0.3823 | -0.0235 | 0.3823 |
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+ | No log | 6.1176 | 104 | 0.3926 | -0.0096 | 0.3926 |
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+ | No log | 6.2353 | 106 | 0.3681 | -0.0235 | 0.3681 |
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+ | No log | 6.3529 | 108 | 0.3415 | -0.0235 | 0.3415 |
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+ | No log | 6.4706 | 110 | 0.3362 | -0.0235 | 0.3362 |
105
+ | No log | 6.5882 | 112 | 0.3928 | -0.0323 | 0.3928 |
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+ | No log | 6.7059 | 114 | 0.4304 | -0.0093 | 0.4304 |
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+ | No log | 6.8235 | 116 | 0.4880 | 0.0152 | 0.4880 |
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+ | No log | 6.9412 | 118 | 0.5316 | -0.0043 | 0.5316 |
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+ | No log | 7.0588 | 120 | 0.5155 | 0.0090 | 0.5155 |
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+ | No log | 7.1765 | 122 | 0.4655 | 0.0135 | 0.4655 |
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+ | No log | 7.2941 | 124 | 0.4459 | 0.0029 | 0.4459 |
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+ | No log | 7.4118 | 126 | 0.4302 | -0.0180 | 0.4302 |
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+ | No log | 7.5294 | 128 | 0.4389 | -0.0260 | 0.4389 |
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+ | No log | 7.6471 | 130 | 0.4613 | -0.0025 | 0.4613 |
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+ | No log | 7.7647 | 132 | 0.4740 | 0.0311 | 0.4740 |
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+ | No log | 7.8824 | 134 | 0.4735 | 0.0311 | 0.4735 |
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+ | No log | 8.0 | 136 | 0.4930 | 0.0088 | 0.4930 |
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+ | No log | 8.1176 | 138 | 0.5329 | 0.0102 | 0.5329 |
119
+ | No log | 8.2353 | 140 | 0.5907 | -0.0105 | 0.5907 |
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+ | No log | 8.3529 | 142 | 0.6354 | -0.0082 | 0.6354 |
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+ | No log | 8.4706 | 144 | 0.6447 | -0.0082 | 0.6447 |
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+ | No log | 8.5882 | 146 | 0.6437 | 0.0032 | 0.6437 |
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+ | No log | 8.7059 | 148 | 0.6301 | -0.0201 | 0.6301 |
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+ | No log | 8.8235 | 150 | 0.6096 | -0.0201 | 0.6096 |
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+ | No log | 8.9412 | 152 | 0.6030 | -0.0201 | 0.6030 |
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+ | No log | 9.0588 | 154 | 0.6322 | -0.0082 | 0.6322 |
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+ | No log | 9.1765 | 156 | 0.6675 | 0.0142 | 0.6675 |
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+ | No log | 9.2941 | 158 | 0.7002 | 0.0252 | 0.7002 |
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+ | No log | 9.4118 | 160 | 0.7136 | 0.0455 | 0.7136 |
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+ | No log | 9.5294 | 162 | 0.7118 | 0.0455 | 0.7118 |
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+ | No log | 9.6471 | 164 | 0.7001 | 0.0355 | 0.7001 |
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+ | No log | 9.7647 | 166 | 0.6860 | 0.0252 | 0.6860 |
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+ | No log | 9.8824 | 168 | 0.6738 | 0.0252 | 0.6738 |
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+ | No log | 10.0 | 170 | 0.6695 | 0.0252 | 0.6695 |
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  ### Framework versions
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