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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_organization_task7_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_organization_task7_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: 0.5739 |
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- Qwk: 0.7967 |
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- Mse: 0.5739 |
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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 | 0.1333 | 2 | 1.9448 | 0.1649 | 1.9447 | |
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| No log | 0.2667 | 4 | 1.4779 | 0.0771 | 1.4779 | |
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| No log | 0.4 | 6 | 1.3512 | 0.4234 | 1.3512 | |
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| No log | 0.5333 | 8 | 0.9818 | 0.5170 | 0.9818 | |
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| No log | 0.6667 | 10 | 0.9848 | 0.7218 | 0.9848 | |
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| No log | 0.8 | 12 | 0.7546 | 0.7580 | 0.7546 | |
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| No log | 0.9333 | 14 | 0.6613 | 0.7635 | 0.6613 | |
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| No log | 1.0667 | 16 | 0.5901 | 0.7415 | 0.5901 | |
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| No log | 1.2 | 18 | 0.5891 | 0.6836 | 0.5891 | |
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| No log | 1.3333 | 20 | 0.6666 | 0.7927 | 0.6666 | |
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| No log | 1.4667 | 22 | 0.7821 | 0.7742 | 0.7821 | |
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| No log | 1.6 | 24 | 0.5788 | 0.7710 | 0.5788 | |
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| No log | 1.7333 | 26 | 0.5726 | 0.6635 | 0.5726 | |
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| No log | 1.8667 | 28 | 0.5773 | 0.7575 | 0.5773 | |
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| No log | 2.0 | 30 | 0.8482 | 0.7672 | 0.8482 | |
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| No log | 2.1333 | 32 | 0.9640 | 0.7499 | 0.9640 | |
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| No log | 2.2667 | 34 | 0.7191 | 0.7738 | 0.7191 | |
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| No log | 2.4 | 36 | 0.5565 | 0.7624 | 0.5565 | |
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| No log | 2.5333 | 38 | 0.5998 | 0.6630 | 0.5998 | |
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| No log | 2.6667 | 40 | 0.5526 | 0.7554 | 0.5526 | |
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| No log | 2.8 | 42 | 0.6355 | 0.7866 | 0.6355 | |
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| No log | 2.9333 | 44 | 0.7893 | 0.7696 | 0.7893 | |
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| No log | 3.0667 | 46 | 0.7015 | 0.7820 | 0.7015 | |
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| No log | 3.2 | 48 | 0.5349 | 0.7719 | 0.5349 | |
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| No log | 3.3333 | 50 | 0.5250 | 0.7364 | 0.5250 | |
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| No log | 3.4667 | 52 | 0.5324 | 0.7720 | 0.5324 | |
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| No log | 3.6 | 54 | 0.6922 | 0.7790 | 0.6922 | |
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| No log | 3.7333 | 56 | 0.7969 | 0.7647 | 0.7969 | |
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| No log | 3.8667 | 58 | 0.7515 | 0.7687 | 0.7515 | |
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| No log | 4.0 | 60 | 0.5754 | 0.7791 | 0.5754 | |
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| No log | 4.1333 | 62 | 0.5295 | 0.7890 | 0.5295 | |
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| No log | 4.2667 | 64 | 0.5568 | 0.7950 | 0.5568 | |
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| No log | 4.4 | 66 | 0.6597 | 0.7830 | 0.6597 | |
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| No log | 4.5333 | 68 | 0.7200 | 0.7855 | 0.7200 | |
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| No log | 4.6667 | 70 | 0.6382 | 0.7912 | 0.6382 | |
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| No log | 4.8 | 72 | 0.5464 | 0.7964 | 0.5464 | |
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| No log | 4.9333 | 74 | 0.5642 | 0.7927 | 0.5642 | |
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| No log | 5.0667 | 76 | 0.5529 | 0.7877 | 0.5529 | |
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| No log | 5.2 | 78 | 0.5685 | 0.7941 | 0.5685 | |
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| No log | 5.3333 | 80 | 0.5692 | 0.8019 | 0.5692 | |
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| No log | 5.4667 | 82 | 0.5649 | 0.8048 | 0.5649 | |
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| No log | 5.6 | 84 | 0.5735 | 0.8008 | 0.5735 | |
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| No log | 5.7333 | 86 | 0.5626 | 0.7884 | 0.5626 | |
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| No log | 5.8667 | 88 | 0.5496 | 0.7807 | 0.5496 | |
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| No log | 6.0 | 90 | 0.5597 | 0.7832 | 0.5597 | |
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| No log | 6.1333 | 92 | 0.5892 | 0.8044 | 0.5892 | |
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| No log | 6.2667 | 94 | 0.5985 | 0.8021 | 0.5985 | |
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| No log | 6.4 | 96 | 0.5764 | 0.7946 | 0.5764 | |
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| No log | 6.5333 | 98 | 0.5254 | 0.7832 | 0.5254 | |
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| No log | 6.6667 | 100 | 0.5198 | 0.7806 | 0.5198 | |
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| No log | 6.8 | 102 | 0.5624 | 0.7979 | 0.5624 | |
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| No log | 6.9333 | 104 | 0.5920 | 0.7935 | 0.5920 | |
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| No log | 7.0667 | 106 | 0.6267 | 0.8062 | 0.6267 | |
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| No log | 7.2 | 108 | 0.6433 | 0.8077 | 0.6433 | |
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| No log | 7.3333 | 110 | 0.5670 | 0.7975 | 0.5670 | |
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| No log | 7.4667 | 112 | 0.5349 | 0.7881 | 0.5349 | |
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| No log | 7.6 | 114 | 0.5360 | 0.7932 | 0.5360 | |
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| No log | 7.7333 | 116 | 0.5494 | 0.7932 | 0.5494 | |
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| No log | 7.8667 | 118 | 0.5884 | 0.8142 | 0.5884 | |
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| No log | 8.0 | 120 | 0.6313 | 0.8158 | 0.6313 | |
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| No log | 8.1333 | 122 | 0.6069 | 0.8159 | 0.6069 | |
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| No log | 8.2667 | 124 | 0.5732 | 0.8053 | 0.5732 | |
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| No log | 8.4 | 126 | 0.5567 | 0.7975 | 0.5567 | |
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| No log | 8.5333 | 128 | 0.5440 | 0.7789 | 0.5440 | |
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| No log | 8.6667 | 130 | 0.5462 | 0.7810 | 0.5462 | |
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| No log | 8.8 | 132 | 0.5522 | 0.7873 | 0.5522 | |
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| No log | 8.9333 | 134 | 0.5458 | 0.7876 | 0.5458 | |
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| No log | 9.0667 | 136 | 0.5390 | 0.7905 | 0.5390 | |
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| No log | 9.2 | 138 | 0.5392 | 0.7901 | 0.5392 | |
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| No log | 9.3333 | 140 | 0.5491 | 0.7943 | 0.5491 | |
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| No log | 9.4667 | 142 | 0.5675 | 0.7937 | 0.5675 | |
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| No log | 9.6 | 144 | 0.5753 | 0.7967 | 0.5753 | |
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| No log | 9.7333 | 146 | 0.5745 | 0.7967 | 0.5745 | |
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| No log | 9.8667 | 148 | 0.5743 | 0.7967 | 0.5743 | |
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| No log | 10.0 | 150 | 0.5739 | 0.7967 | 0.5739 | |
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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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