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arabert_cross_relevance_task4_fold3

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metadata
base_model: aubmindlab/bert-base-arabertv02
tags:
  - generated_from_trainer
model-index:
  - name: arabert_cross_relevance_task4_fold3
    results: []

arabert_cross_relevance_task4_fold3

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3037
  • Qwk: 0.3732
  • Mse: 0.3037

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Qwk Mse
No log 0.1176 2 0.5630 0.1562 0.5630
No log 0.2353 4 0.4644 0.2174 0.4644
No log 0.3529 6 0.3950 0.1962 0.3950
No log 0.4706 8 0.3834 0.2684 0.3834
No log 0.5882 10 0.3306 0.3081 0.3306
No log 0.7059 12 0.3268 0.2811 0.3268
No log 0.8235 14 0.3154 0.3011 0.3154
No log 0.9412 16 0.3060 0.3218 0.3060
No log 1.0588 18 0.3117 0.3651 0.3117
No log 1.1765 20 0.3057 0.3773 0.3057
No log 1.2941 22 0.3034 0.3911 0.3034
No log 1.4118 24 0.2791 0.4002 0.2791
No log 1.5294 26 0.2627 0.4023 0.2627
No log 1.6471 28 0.2813 0.3853 0.2813
No log 1.7647 30 0.3082 0.3740 0.3082
No log 1.8824 32 0.2928 0.3614 0.2928
No log 2.0 34 0.2792 0.3430 0.2792
No log 2.1176 36 0.2640 0.3836 0.2640
No log 2.2353 38 0.2797 0.4090 0.2797
No log 2.3529 40 0.3047 0.3991 0.3047
No log 2.4706 42 0.3233 0.3483 0.3233
No log 2.5882 44 0.3173 0.3975 0.3173
No log 2.7059 46 0.2794 0.3702 0.2794
No log 2.8235 48 0.2545 0.3595 0.2545
No log 2.9412 50 0.2598 0.3274 0.2598
No log 3.0588 52 0.3170 0.2780 0.3170
No log 3.1765 54 0.3616 0.2701 0.3616
No log 3.2941 56 0.3399 0.3799 0.3399
No log 3.4118 58 0.2912 0.4991 0.2912
No log 3.5294 60 0.2788 0.5808 0.2788
No log 3.6471 62 0.2781 0.5944 0.2781
No log 3.7647 64 0.2655 0.5547 0.2655
No log 3.8824 66 0.2739 0.4479 0.2739
No log 4.0 68 0.3052 0.3580 0.3052
No log 4.1176 70 0.3257 0.2703 0.3257
No log 4.2353 72 0.3077 0.2765 0.3077
No log 4.3529 74 0.2673 0.3446 0.2673
No log 4.4706 76 0.2558 0.4205 0.2558
No log 4.5882 78 0.2699 0.4751 0.2699
No log 4.7059 80 0.3058 0.5205 0.3058
No log 4.8235 82 0.3248 0.5030 0.3248
No log 4.9412 84 0.3083 0.4300 0.3083
No log 5.0588 86 0.2844 0.3512 0.2844
No log 5.1765 88 0.2595 0.3405 0.2595
No log 5.2941 90 0.2544 0.3462 0.2544
No log 5.4118 92 0.2686 0.3378 0.2686
No log 5.5294 94 0.3037 0.3446 0.3037
No log 5.6471 96 0.3453 0.3453 0.3453
No log 5.7647 98 0.3438 0.3956 0.3438
No log 5.8824 100 0.3084 0.4184 0.3084
No log 6.0 102 0.2757 0.4015 0.2757
No log 6.1176 104 0.2744 0.3963 0.2744
No log 6.2353 106 0.2900 0.4343 0.2900
No log 6.3529 108 0.3167 0.4357 0.3167
No log 6.4706 110 0.3249 0.4225 0.3249
No log 6.5882 112 0.3104 0.3929 0.3104
No log 6.7059 114 0.2965 0.3961 0.2965
No log 6.8235 116 0.2870 0.3956 0.2870
No log 6.9412 118 0.2835 0.4017 0.2835
No log 7.0588 120 0.2798 0.4117 0.2798
No log 7.1765 122 0.2952 0.3838 0.2952
No log 7.2941 124 0.3094 0.3838 0.3094
No log 7.4118 126 0.3254 0.4226 0.3254
No log 7.5294 128 0.3223 0.4122 0.3223
No log 7.6471 130 0.3091 0.3910 0.3091
No log 7.7647 132 0.3042 0.3896 0.3042
No log 7.8824 134 0.2977 0.3822 0.2977
No log 8.0 136 0.2987 0.3536 0.2987
No log 8.1176 138 0.3110 0.3437 0.3110
No log 8.2353 140 0.3121 0.3392 0.3121
No log 8.3529 142 0.3056 0.3402 0.3056
No log 8.4706 144 0.3047 0.3462 0.3047
No log 8.5882 146 0.3035 0.3572 0.3035
No log 8.7059 148 0.3024 0.3690 0.3024
No log 8.8235 150 0.3034 0.3717 0.3034
No log 8.9412 152 0.3012 0.3774 0.3012
No log 9.0588 154 0.2988 0.3774 0.2988
No log 9.1765 156 0.3009 0.3774 0.3009
No log 9.2941 158 0.3001 0.3889 0.3001
No log 9.4118 160 0.3015 0.3946 0.3015
No log 9.5294 162 0.3032 0.3946 0.3032
No log 9.6471 164 0.3050 0.3846 0.3050
No log 9.7647 166 0.3044 0.3732 0.3044
No log 9.8824 168 0.3039 0.3732 0.3039
No log 10.0 170 0.3037 0.3732 0.3037

Framework versions

  • Transformers 4.44.0
  • Pytorch 2.4.0
  • Datasets 2.21.0
  • Tokenizers 0.19.1