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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_fold0 |
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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_fold0 |
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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: 0.7058 |
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- Qwk: 0.5975 |
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- Mse: 0.7057 |
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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 | 3.8864 | 0.0541 | 3.8830 | |
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| No log | 0.2667 | 4 | 2.5481 | 0.0079 | 2.5460 | |
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| No log | 0.4 | 6 | 1.6996 | 0.2037 | 1.6983 | |
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| No log | 0.5333 | 8 | 1.3776 | 0.2939 | 1.3765 | |
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| No log | 0.6667 | 10 | 1.3355 | 0.3347 | 1.3345 | |
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| No log | 0.8 | 12 | 1.2773 | 0.3590 | 1.2767 | |
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| No log | 0.9333 | 14 | 1.4284 | 0.3342 | 1.4277 | |
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| No log | 1.0667 | 16 | 1.1577 | 0.3897 | 1.1573 | |
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| No log | 1.2 | 18 | 0.9645 | 0.4536 | 0.9641 | |
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| No log | 1.3333 | 20 | 1.1001 | 0.4324 | 1.0996 | |
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| No log | 1.4667 | 22 | 1.0995 | 0.4399 | 1.0990 | |
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| No log | 1.6 | 24 | 0.9787 | 0.4704 | 0.9783 | |
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| No log | 1.7333 | 26 | 0.8116 | 0.5438 | 0.8112 | |
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| No log | 1.8667 | 28 | 0.8107 | 0.5471 | 0.8103 | |
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| No log | 2.0 | 30 | 0.9069 | 0.4983 | 0.9063 | |
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| No log | 2.1333 | 32 | 0.8730 | 0.5346 | 0.8726 | |
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| No log | 2.2667 | 34 | 0.9141 | 0.5284 | 0.9138 | |
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| No log | 2.4 | 36 | 0.7576 | 0.6068 | 0.7578 | |
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| No log | 2.5333 | 38 | 0.7560 | 0.6087 | 0.7563 | |
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| No log | 2.6667 | 40 | 0.8005 | 0.6059 | 0.8007 | |
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| No log | 2.8 | 42 | 0.9430 | 0.5399 | 0.9430 | |
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| No log | 2.9333 | 44 | 0.8990 | 0.5542 | 0.8990 | |
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| No log | 3.0667 | 46 | 0.8494 | 0.5672 | 0.8494 | |
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| No log | 3.2 | 48 | 0.8095 | 0.5752 | 0.8094 | |
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| No log | 3.3333 | 50 | 0.7424 | 0.6012 | 0.7425 | |
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| No log | 3.4667 | 52 | 0.7009 | 0.6100 | 0.7011 | |
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| No log | 3.6 | 54 | 0.7078 | 0.6055 | 0.7080 | |
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| No log | 3.7333 | 56 | 0.8222 | 0.5652 | 0.8223 | |
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| No log | 3.8667 | 58 | 0.8211 | 0.5742 | 0.8212 | |
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| No log | 4.0 | 60 | 0.7561 | 0.5870 | 0.7562 | |
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| No log | 4.1333 | 62 | 0.6981 | 0.6055 | 0.6982 | |
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| No log | 4.2667 | 64 | 0.6970 | 0.6051 | 0.6971 | |
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| No log | 4.4 | 66 | 0.7327 | 0.5991 | 0.7326 | |
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| No log | 4.5333 | 68 | 0.8809 | 0.5424 | 0.8806 | |
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| No log | 4.6667 | 70 | 0.8266 | 0.5559 | 0.8263 | |
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| No log | 4.8 | 72 | 0.7118 | 0.5954 | 0.7117 | |
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| No log | 4.9333 | 74 | 0.6923 | 0.6040 | 0.6923 | |
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| No log | 5.0667 | 76 | 0.7259 | 0.5893 | 0.7259 | |
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| No log | 5.2 | 78 | 0.7425 | 0.5832 | 0.7425 | |
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| No log | 5.3333 | 80 | 0.6843 | 0.6051 | 0.6843 | |
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| No log | 5.4667 | 82 | 0.6647 | 0.6118 | 0.6647 | |
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| No log | 5.6 | 84 | 0.6805 | 0.6104 | 0.6804 | |
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| No log | 5.7333 | 86 | 0.7021 | 0.5992 | 0.7019 | |
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| No log | 5.8667 | 88 | 0.6896 | 0.6158 | 0.6894 | |
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| No log | 6.0 | 90 | 0.6658 | 0.6204 | 0.6657 | |
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| No log | 6.1333 | 92 | 0.6774 | 0.6118 | 0.6774 | |
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| No log | 6.2667 | 94 | 0.7472 | 0.5748 | 0.7471 | |
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| No log | 6.4 | 96 | 0.8444 | 0.5491 | 0.8442 | |
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| No log | 6.5333 | 98 | 0.8227 | 0.5502 | 0.8225 | |
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| No log | 6.6667 | 100 | 0.7455 | 0.5671 | 0.7453 | |
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| No log | 6.8 | 102 | 0.7062 | 0.5907 | 0.7060 | |
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| No log | 6.9333 | 104 | 0.6458 | 0.6143 | 0.6457 | |
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| No log | 7.0667 | 106 | 0.6289 | 0.6250 | 0.6288 | |
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| No log | 7.2 | 108 | 0.6373 | 0.6205 | 0.6371 | |
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| No log | 7.3333 | 110 | 0.6669 | 0.6113 | 0.6666 | |
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| No log | 7.4667 | 112 | 0.7012 | 0.6035 | 0.7009 | |
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| No log | 7.6 | 114 | 0.6942 | 0.5999 | 0.6939 | |
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| No log | 7.7333 | 116 | 0.6669 | 0.6083 | 0.6668 | |
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| No log | 7.8667 | 118 | 0.6470 | 0.6177 | 0.6469 | |
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| No log | 8.0 | 120 | 0.6439 | 0.6292 | 0.6438 | |
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| No log | 8.1333 | 122 | 0.6501 | 0.6098 | 0.6500 | |
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| No log | 8.2667 | 124 | 0.6801 | 0.6013 | 0.6800 | |
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| No log | 8.4 | 126 | 0.7382 | 0.5951 | 0.7380 | |
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| No log | 8.5333 | 128 | 0.7558 | 0.5885 | 0.7556 | |
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| No log | 8.6667 | 130 | 0.7227 | 0.5947 | 0.7225 | |
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| No log | 8.8 | 132 | 0.6780 | 0.6014 | 0.6780 | |
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| No log | 8.9333 | 134 | 0.6554 | 0.6101 | 0.6554 | |
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| No log | 9.0667 | 136 | 0.6520 | 0.6154 | 0.6520 | |
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| No log | 9.2 | 138 | 0.6597 | 0.6100 | 0.6596 | |
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| No log | 9.3333 | 140 | 0.6690 | 0.6141 | 0.6689 | |
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| No log | 9.4667 | 142 | 0.6790 | 0.6041 | 0.6789 | |
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| No log | 9.6 | 144 | 0.6910 | 0.5976 | 0.6909 | |
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| No log | 9.7333 | 146 | 0.7025 | 0.5975 | 0.7024 | |
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| No log | 9.8667 | 148 | 0.7059 | 0.5975 | 0.7057 | |
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| No log | 10.0 | 150 | 0.7058 | 0.5975 | 0.7057 | |
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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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