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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_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_development_task1_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: 0.8306 |
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- Qwk: 0.2565 |
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- Mse: 0.8306 |
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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 | 4.0034 | -0.0039 | 4.0034 | |
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| No log | 0.2667 | 4 | 1.7572 | 0.0385 | 1.7572 | |
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| No log | 0.4 | 6 | 0.8795 | 0.1253 | 0.8795 | |
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| No log | 0.5333 | 8 | 1.0722 | 0.1468 | 1.0722 | |
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| No log | 0.6667 | 10 | 1.9981 | 0.0739 | 1.9981 | |
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| No log | 0.8 | 12 | 1.4228 | 0.1298 | 1.4228 | |
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| No log | 0.9333 | 14 | 0.7120 | 0.1720 | 0.7120 | |
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| No log | 1.0667 | 16 | 0.5182 | 0.2951 | 0.5182 | |
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| No log | 1.2 | 18 | 0.6133 | 0.2736 | 0.6133 | |
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| No log | 1.3333 | 20 | 1.1336 | 0.1776 | 1.1336 | |
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| No log | 1.4667 | 22 | 1.2656 | 0.1714 | 1.2656 | |
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| No log | 1.6 | 24 | 0.8675 | 0.2380 | 0.8675 | |
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| No log | 1.7333 | 26 | 0.5730 | 0.3050 | 0.5730 | |
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| No log | 1.8667 | 28 | 0.5924 | 0.2784 | 0.5924 | |
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| No log | 2.0 | 30 | 0.6861 | 0.2120 | 0.6861 | |
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| No log | 2.1333 | 32 | 0.8867 | 0.2029 | 0.8867 | |
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| No log | 2.2667 | 34 | 0.9172 | 0.2121 | 0.9172 | |
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| No log | 2.4 | 36 | 0.7721 | 0.2159 | 0.7721 | |
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| No log | 2.5333 | 38 | 0.8001 | 0.2277 | 0.8001 | |
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| No log | 2.6667 | 40 | 0.8684 | 0.2498 | 0.8684 | |
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| No log | 2.8 | 42 | 0.9570 | 0.2264 | 0.9570 | |
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| No log | 2.9333 | 44 | 0.8803 | 0.2439 | 0.8803 | |
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| No log | 3.0667 | 46 | 0.7435 | 0.2799 | 0.7435 | |
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| No log | 3.2 | 48 | 0.6805 | 0.3082 | 0.6805 | |
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| No log | 3.3333 | 50 | 0.8424 | 0.2730 | 0.8424 | |
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| No log | 3.4667 | 52 | 0.8402 | 0.2670 | 0.8402 | |
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| No log | 3.6 | 54 | 0.8115 | 0.2861 | 0.8115 | |
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| No log | 3.7333 | 56 | 0.8179 | 0.2776 | 0.8179 | |
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| No log | 3.8667 | 58 | 0.7692 | 0.2822 | 0.7692 | |
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| No log | 4.0 | 60 | 0.6605 | 0.2944 | 0.6605 | |
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| No log | 4.1333 | 62 | 0.6724 | 0.3033 | 0.6724 | |
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| No log | 4.2667 | 64 | 0.7918 | 0.2700 | 0.7918 | |
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| No log | 4.4 | 66 | 0.9373 | 0.2649 | 0.9373 | |
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| No log | 4.5333 | 68 | 0.8734 | 0.2482 | 0.8734 | |
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| No log | 4.6667 | 70 | 0.6994 | 0.2866 | 0.6994 | |
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| No log | 4.8 | 72 | 0.5761 | 0.3307 | 0.5761 | |
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| No log | 4.9333 | 74 | 0.6497 | 0.2879 | 0.6497 | |
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| No log | 5.0667 | 76 | 0.7333 | 0.2628 | 0.7333 | |
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| No log | 5.2 | 78 | 1.0341 | 0.2345 | 1.0341 | |
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| No log | 5.3333 | 80 | 1.1378 | 0.2214 | 1.1378 | |
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| No log | 5.4667 | 82 | 0.9255 | 0.2527 | 0.9255 | |
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| No log | 5.6 | 84 | 0.6589 | 0.3108 | 0.6589 | |
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| No log | 5.7333 | 86 | 0.5709 | 0.3576 | 0.5709 | |
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| No log | 5.8667 | 88 | 0.6392 | 0.2982 | 0.6392 | |
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| No log | 6.0 | 90 | 0.7919 | 0.2436 | 0.7919 | |
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| No log | 6.1333 | 92 | 0.7855 | 0.2412 | 0.7855 | |
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| No log | 6.2667 | 94 | 0.6800 | 0.2919 | 0.6800 | |
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| No log | 6.4 | 96 | 0.6850 | 0.2998 | 0.6850 | |
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| No log | 6.5333 | 98 | 0.8473 | 0.2545 | 0.8473 | |
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| No log | 6.6667 | 100 | 0.9780 | 0.2417 | 0.9780 | |
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| No log | 6.8 | 102 | 0.9663 | 0.2331 | 0.9663 | |
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| No log | 6.9333 | 104 | 0.8213 | 0.2337 | 0.8213 | |
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| No log | 7.0667 | 106 | 0.6942 | 0.2789 | 0.6942 | |
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| No log | 7.2 | 108 | 0.7119 | 0.2738 | 0.7119 | |
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| No log | 7.3333 | 110 | 0.8067 | 0.2517 | 0.8067 | |
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| No log | 7.4667 | 112 | 0.8998 | 0.2447 | 0.8998 | |
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| No log | 7.6 | 114 | 0.9907 | 0.2199 | 0.9907 | |
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| No log | 7.7333 | 116 | 0.9290 | 0.2364 | 0.9290 | |
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| No log | 7.8667 | 118 | 0.7925 | 0.2551 | 0.7925 | |
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| No log | 8.0 | 120 | 0.7137 | 0.2738 | 0.7137 | |
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| No log | 8.1333 | 122 | 0.7202 | 0.2753 | 0.7202 | |
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| No log | 8.2667 | 124 | 0.7738 | 0.2663 | 0.7738 | |
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| No log | 8.4 | 126 | 0.8078 | 0.2539 | 0.8078 | |
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| No log | 8.5333 | 128 | 0.8794 | 0.2516 | 0.8794 | |
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| No log | 8.6667 | 130 | 0.9809 | 0.2362 | 0.9809 | |
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| No log | 8.8 | 132 | 1.0066 | 0.2362 | 1.0066 | |
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| No log | 8.9333 | 134 | 0.9524 | 0.2397 | 0.9524 | |
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| No log | 9.0667 | 136 | 0.8849 | 0.2464 | 0.8849 | |
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| No log | 9.2 | 138 | 0.8285 | 0.2565 | 0.8285 | |
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| No log | 9.3333 | 140 | 0.7806 | 0.2545 | 0.7806 | |
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| No log | 9.4667 | 142 | 0.7707 | 0.2569 | 0.7707 | |
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| No log | 9.6 | 144 | 0.7836 | 0.2545 | 0.7836 | |
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| No log | 9.7333 | 146 | 0.8063 | 0.2550 | 0.8063 | |
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| No log | 9.8667 | 148 | 0.8258 | 0.2565 | 0.8258 | |
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| No log | 10.0 | 150 | 0.8306 | 0.2565 | 0.8306 | |
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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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