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arabert_cross_relevance_task5_fold3

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README.md CHANGED
@@ -3,20 +3,20 @@ base_model: aubmindlab/bert-base-arabertv02
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
- - name: arabert_cross_relevance_task5_fold3
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_task5_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:
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- - Loss: 0.2615
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  - Qwk: 0.0
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- - Mse: 0.2615
20
 
21
  ## Model description
22
 
@@ -36,49 +36,97 @@ More information needed
36
 
37
  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
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  - 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
 
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- | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
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- |:-------------:|:------:|:----:|:---------------:|:-------:|:------:|
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- | No log | 0.0308 | 2 | 1.7894 | 0.0 | 1.7894 |
51
- | No log | 0.0615 | 4 | 0.5746 | 0.0241 | 0.5746 |
52
- | No log | 0.0923 | 6 | 0.2626 | 0.0101 | 0.2626 |
53
- | No log | 0.1231 | 8 | 0.3467 | 0.0842 | 0.3467 |
54
- | No log | 0.1538 | 10 | 0.3204 | -0.0484 | 0.3204 |
55
- | No log | 0.1846 | 12 | 0.2946 | 0.0278 | 0.2946 |
56
- | No log | 0.2154 | 14 | 0.3020 | 0.0 | 0.3020 |
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- | No log | 0.2462 | 16 | 0.3536 | 0.0 | 0.3536 |
58
- | No log | 0.2769 | 18 | 0.3417 | 0.0 | 0.3417 |
59
- | No log | 0.3077 | 20 | 0.3100 | 0.0 | 0.3100 |
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- | No log | 0.3385 | 22 | 0.3160 | 0.0 | 0.3160 |
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- | No log | 0.3692 | 24 | 0.3028 | 0.0 | 0.3028 |
62
- | No log | 0.4 | 26 | 0.2898 | 0.0 | 0.2898 |
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- | No log | 0.4308 | 28 | 0.2803 | 0.0 | 0.2803 |
64
- | No log | 0.4615 | 30 | 0.2760 | 0.0 | 0.2760 |
65
- | No log | 0.4923 | 32 | 0.2736 | 0.0 | 0.2736 |
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- | No log | 0.5231 | 34 | 0.2752 | 0.0101 | 0.2752 |
67
- | No log | 0.5538 | 36 | 0.2821 | -0.0069 | 0.2821 |
68
- | No log | 0.5846 | 38 | 0.2933 | 0.0217 | 0.2933 |
69
- | No log | 0.6154 | 40 | 0.2959 | 0.0672 | 0.2959 |
70
- | No log | 0.6462 | 42 | 0.2871 | -0.0106 | 0.2871 |
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- | No log | 0.6769 | 44 | 0.2960 | 0.0267 | 0.2960 |
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- | No log | 0.7077 | 46 | 0.2930 | 0.0185 | 0.2930 |
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- | No log | 0.7385 | 48 | 0.2791 | 0.0035 | 0.2791 |
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- | No log | 0.7692 | 50 | 0.2677 | 0.0 | 0.2677 |
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- | No log | 0.8 | 52 | 0.2641 | 0.0 | 0.2641 |
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- | No log | 0.8308 | 54 | 0.2641 | 0.0 | 0.2641 |
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- | No log | 0.8615 | 56 | 0.2630 | 0.0 | 0.2630 |
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- | No log | 0.8923 | 58 | 0.2625 | 0.0 | 0.2625 |
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- | No log | 0.9231 | 60 | 0.2620 | 0.0 | 0.2620 |
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- | No log | 0.9538 | 62 | 0.2617 | 0.0 | 0.2617 |
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- | No log | 0.9846 | 64 | 0.2615 | 0.0 | 0.2615 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
82
 
83
 
84
  ### Framework versions
 
3
  tags:
4
  - generated_from_trainer
5
  model-index:
6
+ - name: arabert_cross_relevance_task5_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_task5_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: 0.3102
18
  - Qwk: 0.0
19
+ - Mse: 0.3106
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
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+ - num_epochs: 10
45
 
46
  ### Training results
47
 
48
+ | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse |
49
+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|
50
+ | No log | 0.125 | 2 | 0.8487 | 0.0102 | 0.8475 |
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+ | No log | 0.25 | 4 | 0.3505 | 0.1091 | 0.3504 |
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+ | No log | 0.375 | 6 | 0.4480 | 0.0599 | 0.4484 |
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+ | No log | 0.5 | 8 | 0.3079 | 0.0534 | 0.3080 |
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+ | No log | 0.625 | 10 | 0.3015 | 0.0245 | 0.3018 |
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+ | No log | 0.75 | 12 | 0.3131 | 0.0 | 0.3134 |
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+ | No log | 0.875 | 14 | 0.3140 | 0.0 | 0.3143 |
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+ | No log | 1.0 | 16 | 0.3539 | -0.0164 | 0.3543 |
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+ | No log | 1.125 | 18 | 0.3562 | -0.0164 | 0.3567 |
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+ | No log | 1.25 | 20 | 0.3449 | 0.0 | 0.3454 |
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+ | No log | 1.375 | 22 | 0.3408 | 0.0 | 0.3412 |
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+ | No log | 1.5 | 24 | 0.3416 | 0.0 | 0.3421 |
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+ | No log | 1.625 | 26 | 0.3321 | 0.0 | 0.3325 |
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+ | No log | 1.75 | 28 | 0.3068 | 0.0 | 0.3072 |
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+ | No log | 1.875 | 30 | 0.3135 | 0.0 | 0.3139 |
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+ | No log | 2.0 | 32 | 0.3564 | 0.0122 | 0.3570 |
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+ | No log | 2.125 | 34 | 0.3393 | 0.0 | 0.3399 |
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+ | No log | 2.25 | 36 | 0.2992 | 0.0 | 0.2996 |
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+ | No log | 2.375 | 38 | 0.3002 | 0.0 | 0.3005 |
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+ | No log | 2.5 | 40 | 0.3396 | 0.0122 | 0.3402 |
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+ | No log | 2.625 | 42 | 0.3703 | 0.0368 | 0.3710 |
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+ | No log | 2.75 | 44 | 0.3599 | 0.0203 | 0.3605 |
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+ | No log | 2.875 | 46 | 0.3243 | 0.0 | 0.3248 |
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+ | No log | 3.0 | 48 | 0.3164 | 0.0 | 0.3169 |
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+ | No log | 3.125 | 50 | 0.3455 | -0.0208 | 0.3460 |
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+ | No log | 3.25 | 52 | 0.3796 | -0.0707 | 0.3802 |
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+ | No log | 3.375 | 54 | 0.3560 | -0.0495 | 0.3565 |
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+ | No log | 3.5 | 56 | 0.3121 | 0.0 | 0.3125 |
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+ | No log | 3.625 | 58 | 0.2932 | 0.0 | 0.2935 |
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+ | No log | 3.75 | 60 | 0.2950 | 0.0 | 0.2953 |
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+ | No log | 3.875 | 62 | 0.3159 | 0.0 | 0.3163 |
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+ | No log | 4.0 | 64 | 0.3268 | 0.0 | 0.3273 |
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+ | No log | 4.125 | 66 | 0.3199 | 0.0 | 0.3203 |
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+ | No log | 4.25 | 68 | 0.3055 | 0.0 | 0.3059 |
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+ | No log | 4.375 | 70 | 0.3033 | 0.0 | 0.3037 |
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+ | No log | 4.5 | 72 | 0.3090 | 0.0 | 0.3094 |
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+ | No log | 4.625 | 74 | 0.3329 | 0.0 | 0.3333 |
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+ | No log | 4.75 | 76 | 0.3437 | 0.0 | 0.3442 |
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+ | No log | 4.875 | 78 | 0.3238 | 0.0 | 0.3242 |
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+ | No log | 5.0 | 80 | 0.2995 | 0.0 | 0.2998 |
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+ | No log | 5.125 | 82 | 0.2952 | 0.0 | 0.2954 |
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+ | No log | 5.25 | 84 | 0.3110 | 0.0122 | 0.3113 |
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+ | No log | 5.375 | 86 | 0.3451 | -0.0329 | 0.3455 |
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+ | No log | 5.5 | 88 | 0.3521 | -0.0373 | 0.3526 |
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+ | No log | 5.625 | 90 | 0.3417 | -0.0329 | 0.3422 |
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+ | No log | 5.75 | 92 | 0.3246 | 0.0122 | 0.3250 |
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+ | No log | 5.875 | 94 | 0.3260 | 0.0122 | 0.3264 |
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+ | No log | 6.0 | 96 | 0.3312 | 0.0 | 0.3316 |
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+ | No log | 6.125 | 98 | 0.3222 | 0.0 | 0.3226 |
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+ | No log | 6.25 | 100 | 0.3187 | 0.0 | 0.3191 |
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+ | No log | 6.375 | 102 | 0.3168 | 0.0122 | 0.3171 |
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+ | No log | 6.5 | 104 | 0.3231 | 0.0122 | 0.3235 |
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+ | No log | 6.625 | 106 | 0.3288 | 0.0122 | 0.3292 |
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+ | No log | 6.75 | 108 | 0.3225 | 0.0122 | 0.3229 |
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+ | No log | 6.875 | 110 | 0.3117 | 0.0122 | 0.3120 |
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+ | No log | 7.0 | 112 | 0.3032 | 0.0 | 0.3034 |
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+ | No log | 7.125 | 114 | 0.3022 | 0.0 | 0.3024 |
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+ | No log | 7.25 | 116 | 0.3089 | 0.0122 | 0.3091 |
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+ | No log | 7.375 | 118 | 0.3150 | 0.0122 | 0.3153 |
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+ | No log | 7.5 | 120 | 0.3157 | 0.0122 | 0.3161 |
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+ | No log | 7.625 | 122 | 0.3102 | 0.0122 | 0.3106 |
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+ | No log | 7.75 | 124 | 0.3060 | 0.0 | 0.3063 |
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+ | No log | 7.875 | 126 | 0.3061 | 0.0 | 0.3063 |
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+ | No log | 8.0 | 128 | 0.3089 | 0.0122 | 0.3092 |
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+ | No log | 8.125 | 130 | 0.3108 | 0.0122 | 0.3111 |
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+ | No log | 8.25 | 132 | 0.3154 | 0.0122 | 0.3158 |
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+ | No log | 8.375 | 134 | 0.3210 | 0.0122 | 0.3215 |
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+ | No log | 8.5 | 136 | 0.3202 | 0.0122 | 0.3206 |
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+ | No log | 8.625 | 138 | 0.3172 | 0.0122 | 0.3176 |
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+ | No log | 8.75 | 140 | 0.3139 | 0.0 | 0.3143 |
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+ | No log | 8.875 | 142 | 0.3121 | 0.0 | 0.3125 |
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+ | No log | 9.0 | 144 | 0.3115 | 0.0 | 0.3118 |
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+ | No log | 9.125 | 146 | 0.3118 | 0.0 | 0.3121 |
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+ | No log | 9.25 | 148 | 0.3121 | 0.0 | 0.3124 |
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+ | No log | 9.375 | 150 | 0.3120 | 0.0 | 0.3124 |
125
+ | No log | 9.5 | 152 | 0.3116 | 0.0 | 0.3119 |
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+ | No log | 9.625 | 154 | 0.3110 | 0.0 | 0.3114 |
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+ | No log | 9.75 | 156 | 0.3106 | 0.0 | 0.3109 |
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+ | No log | 9.875 | 158 | 0.3103 | 0.0 | 0.3106 |
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+ | No log | 10.0 | 160 | 0.3102 | 0.0 | 0.3106 |
130
 
131
 
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  ### Framework versions
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