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--- |
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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_development_task1_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_development_task1_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: 0.3891 |
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- Qwk: 0.7487 |
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- Mse: 0.3891 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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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: 64 |
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- eval_batch_size: 64 |
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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: 10 |
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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 | 2.7046 | 0.0134 | 2.7046 | |
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| No log | 0.25 | 4 | 1.3006 | 0.1103 | 1.3006 | |
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| No log | 0.375 | 6 | 0.7355 | 0.3354 | 0.7355 | |
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| No log | 0.5 | 8 | 0.8932 | 0.3820 | 0.8932 | |
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| No log | 0.625 | 10 | 0.5839 | 0.4676 | 0.5839 | |
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| No log | 0.75 | 12 | 0.4634 | 0.5294 | 0.4634 | |
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| No log | 0.875 | 14 | 0.4578 | 0.5335 | 0.4578 | |
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| No log | 1.0 | 16 | 0.5111 | 0.5160 | 0.5111 | |
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| No log | 1.125 | 18 | 0.4822 | 0.6507 | 0.4822 | |
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| No log | 1.25 | 20 | 0.4309 | 0.6257 | 0.4309 | |
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| No log | 1.375 | 22 | 0.4637 | 0.6422 | 0.4637 | |
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| No log | 1.5 | 24 | 0.5888 | 0.7264 | 0.5888 | |
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| No log | 1.625 | 26 | 0.5751 | 0.7173 | 0.5751 | |
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| No log | 1.75 | 28 | 0.4309 | 0.6445 | 0.4309 | |
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| No log | 1.875 | 30 | 0.3977 | 0.6113 | 0.3977 | |
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| No log | 2.0 | 32 | 0.4095 | 0.6330 | 0.4095 | |
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| No log | 2.125 | 34 | 0.4861 | 0.7147 | 0.4861 | |
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| No log | 2.25 | 36 | 0.5155 | 0.7516 | 0.5155 | |
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| No log | 2.375 | 38 | 0.4703 | 0.7321 | 0.4703 | |
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| No log | 2.5 | 40 | 0.3861 | 0.6978 | 0.3861 | |
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| No log | 2.625 | 42 | 0.3964 | 0.7189 | 0.3964 | |
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| No log | 2.75 | 44 | 0.5105 | 0.7660 | 0.5105 | |
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| No log | 2.875 | 46 | 0.5630 | 0.7439 | 0.5630 | |
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| No log | 3.0 | 48 | 0.4666 | 0.7758 | 0.4666 | |
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| No log | 3.125 | 50 | 0.4033 | 0.7314 | 0.4033 | |
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| No log | 3.25 | 52 | 0.3886 | 0.7225 | 0.3886 | |
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| No log | 3.375 | 54 | 0.4264 | 0.7369 | 0.4264 | |
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| No log | 3.5 | 56 | 0.4681 | 0.7538 | 0.4681 | |
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| No log | 3.625 | 58 | 0.4255 | 0.7357 | 0.4255 | |
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| No log | 3.75 | 60 | 0.3784 | 0.7381 | 0.3784 | |
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| No log | 3.875 | 62 | 0.3835 | 0.7261 | 0.3835 | |
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| No log | 4.0 | 64 | 0.3863 | 0.7091 | 0.3863 | |
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| No log | 4.125 | 66 | 0.3964 | 0.7022 | 0.3964 | |
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| No log | 4.25 | 68 | 0.4674 | 0.7519 | 0.4674 | |
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| No log | 4.375 | 70 | 0.5670 | 0.7310 | 0.5670 | |
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| No log | 4.5 | 72 | 0.5082 | 0.7265 | 0.5082 | |
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| No log | 4.625 | 74 | 0.3989 | 0.7387 | 0.3989 | |
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| No log | 4.75 | 76 | 0.3568 | 0.7218 | 0.3568 | |
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| No log | 4.875 | 78 | 0.3670 | 0.7343 | 0.3670 | |
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| No log | 5.0 | 80 | 0.4147 | 0.7453 | 0.4147 | |
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| No log | 5.125 | 82 | 0.4613 | 0.7583 | 0.4613 | |
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| No log | 5.25 | 84 | 0.4365 | 0.7493 | 0.4365 | |
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| No log | 5.375 | 86 | 0.3787 | 0.7383 | 0.3787 | |
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| No log | 5.5 | 88 | 0.3637 | 0.7327 | 0.3637 | |
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| No log | 5.625 | 90 | 0.3896 | 0.7461 | 0.3896 | |
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| No log | 5.75 | 92 | 0.4827 | 0.7585 | 0.4827 | |
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| No log | 5.875 | 94 | 0.5207 | 0.7560 | 0.5207 | |
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| No log | 6.0 | 96 | 0.4771 | 0.7622 | 0.4771 | |
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| No log | 6.125 | 98 | 0.4131 | 0.7595 | 0.4131 | |
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| No log | 6.25 | 100 | 0.3861 | 0.7447 | 0.3861 | |
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| No log | 6.375 | 102 | 0.3770 | 0.7473 | 0.3770 | |
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| No log | 6.5 | 104 | 0.4030 | 0.7421 | 0.4030 | |
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| No log | 6.625 | 106 | 0.4334 | 0.7447 | 0.4334 | |
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| No log | 6.75 | 108 | 0.4677 | 0.7616 | 0.4677 | |
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| No log | 6.875 | 110 | 0.4931 | 0.7670 | 0.4931 | |
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| No log | 7.0 | 112 | 0.4703 | 0.7622 | 0.4703 | |
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| No log | 7.125 | 114 | 0.4736 | 0.7622 | 0.4736 | |
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| No log | 7.25 | 116 | 0.4565 | 0.7580 | 0.4565 | |
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| No log | 7.375 | 118 | 0.4114 | 0.7521 | 0.4114 | |
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| No log | 7.5 | 120 | 0.3925 | 0.7534 | 0.3925 | |
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| No log | 7.625 | 122 | 0.3937 | 0.7441 | 0.3937 | |
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| No log | 7.75 | 124 | 0.3906 | 0.7441 | 0.3906 | |
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| No log | 7.875 | 126 | 0.3958 | 0.7488 | 0.3958 | |
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| No log | 8.0 | 128 | 0.4005 | 0.7481 | 0.4005 | |
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| No log | 8.125 | 130 | 0.4095 | 0.7399 | 0.4095 | |
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| No log | 8.25 | 132 | 0.4044 | 0.7426 | 0.4044 | |
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| No log | 8.375 | 134 | 0.3885 | 0.7487 | 0.3885 | |
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| No log | 8.5 | 136 | 0.3727 | 0.7455 | 0.3727 | |
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| No log | 8.625 | 138 | 0.3751 | 0.7428 | 0.3751 | |
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| No log | 8.75 | 140 | 0.3851 | 0.7477 | 0.3851 | |
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| No log | 8.875 | 142 | 0.4024 | 0.7472 | 0.4024 | |
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| No log | 9.0 | 144 | 0.4118 | 0.7505 | 0.4118 | |
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| No log | 9.125 | 146 | 0.4171 | 0.7505 | 0.4171 | |
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| No log | 9.25 | 148 | 0.4179 | 0.7495 | 0.4179 | |
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| No log | 9.375 | 150 | 0.4096 | 0.7483 | 0.4096 | |
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| No log | 9.5 | 152 | 0.4015 | 0.7555 | 0.4015 | |
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| No log | 9.625 | 154 | 0.3949 | 0.7508 | 0.3949 | |
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| No log | 9.75 | 156 | 0.3905 | 0.7487 | 0.3905 | |
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| No log | 9.875 | 158 | 0.3894 | 0.7487 | 0.3894 | |
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| No log | 10.0 | 160 | 0.3891 | 0.7487 | 0.3891 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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