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arabert_cross_relevance_task3_fold5

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Training in progress, step 160

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  1. README.md +93 -39
  2. model.safetensors +1 -1
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README.md CHANGED
@@ -3,20 +3,20 @@ base_model: aubmindlab/bert-base-arabertv02
3
  tags:
4
  - generated_from_trainer
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  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.
16
  It achieves the following results on the evaluation set:
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- - Loss: 0.1927
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- - Qwk: 0.3583
19
- - Mse: 0.1927
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  ## Model description
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@@ -36,48 +36,102 @@ More information needed
36
 
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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
43
  - 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
  |:-------------:|:------:|:----:|:---------------:|:------:|:------:|
50
- | No log | 0.0317 | 2 | 0.7649 | 0.0249 | 0.7649 |
51
- | No log | 0.0635 | 4 | 0.4874 | 0.1486 | 0.4874 |
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- | No log | 0.0952 | 6 | 0.3246 | 0.3768 | 0.3246 |
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- | No log | 0.1270 | 8 | 0.4428 | 0.4187 | 0.4428 |
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- | No log | 0.1587 | 10 | 0.3587 | 0.2702 | 0.3587 |
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- | No log | 0.1905 | 12 | 0.2865 | 0.2527 | 0.2865 |
56
- | No log | 0.2222 | 14 | 0.2562 | 0.2830 | 0.2562 |
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- | No log | 0.2540 | 16 | 0.2311 | 0.2998 | 0.2311 |
58
- | No log | 0.2857 | 18 | 0.2125 | 0.3152 | 0.2125 |
59
- | No log | 0.3175 | 20 | 0.2154 | 0.3860 | 0.2154 |
60
- | No log | 0.3492 | 22 | 0.2502 | 0.5544 | 0.2502 |
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- | No log | 0.3810 | 24 | 0.2642 | 0.6590 | 0.2642 |
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- | No log | 0.4127 | 26 | 0.2431 | 0.6239 | 0.2431 |
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- | No log | 0.4444 | 28 | 0.2115 | 0.4874 | 0.2115 |
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- | No log | 0.4762 | 30 | 0.1950 | 0.4156 | 0.1950 |
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- | No log | 0.5079 | 32 | 0.1937 | 0.3883 | 0.1937 |
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- | No log | 0.5397 | 34 | 0.1952 | 0.3613 | 0.1952 |
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- | No log | 0.5714 | 36 | 0.1955 | 0.3557 | 0.1955 |
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- | No log | 0.6032 | 38 | 0.1939 | 0.3547 | 0.1939 |
69
- | No log | 0.6349 | 40 | 0.1915 | 0.3536 | 0.1915 |
70
- | No log | 0.6667 | 42 | 0.1923 | 0.3536 | 0.1923 |
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- | No log | 0.6984 | 44 | 0.1919 | 0.3490 | 0.1919 |
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- | No log | 0.7302 | 46 | 0.1928 | 0.3490 | 0.1928 |
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- | No log | 0.7619 | 48 | 0.1923 | 0.3490 | 0.1923 |
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- | No log | 0.7937 | 50 | 0.1945 | 0.3468 | 0.1945 |
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- | No log | 0.8254 | 52 | 0.1988 | 0.3305 | 0.1988 |
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- | No log | 0.8571 | 54 | 0.2000 | 0.3305 | 0.2000 |
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- | No log | 0.8889 | 56 | 0.1995 | 0.3363 | 0.1995 |
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- | No log | 0.9206 | 58 | 0.1967 | 0.3363 | 0.1967 |
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- | No log | 0.9524 | 60 | 0.1943 | 0.3408 | 0.1943 |
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- | No log | 0.9841 | 62 | 0.1927 | 0.3583 | 0.1927 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
81
 
82
 
83
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task3_fold4
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_fold4
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: 0.2244
18
+ - Qwk: 0.3147
19
+ - Mse: 0.2244
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 | 0.6247 | 0.1100 | 0.6247 |
51
+ | 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 |
126
+ | No log | 9.0588 | 154 | 0.2231 | 0.3205 | 0.2231 |
127
+ | No log | 9.1765 | 156 | 0.2239 | 0.3275 | 0.2239 |
128
+ | No log | 9.2941 | 158 | 0.2243 | 0.3275 | 0.2243 |
129
+ | No log | 9.4118 | 160 | 0.2236 | 0.3147 | 0.2236 |
130
+ | No log | 9.5294 | 162 | 0.2234 | 0.3080 | 0.2234 |
131
+ | No log | 9.6471 | 164 | 0.2238 | 0.3080 | 0.2238 |
132
+ | No log | 9.7647 | 166 | 0.2243 | 0.3080 | 0.2243 |
133
+ | No log | 9.8824 | 168 | 0.2244 | 0.3147 | 0.2244 |
134
+ | No log | 10.0 | 170 | 0.2244 | 0.3147 | 0.2244 |
135
 
136
 
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  ### Framework versions
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