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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_relevance_task5_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_relevance_task5_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: 0.2622 |
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- Qwk: 0.1283 |
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- Mse: 0.2622 |
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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 | 0.4161 | 0.0028 | 0.4160 | |
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| No log | 0.2667 | 4 | 0.3774 | 0.0409 | 0.3772 | |
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| No log | 0.4 | 6 | 0.3195 | 0.0376 | 0.3194 | |
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| No log | 0.5333 | 8 | 0.3532 | 0.0623 | 0.3530 | |
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| No log | 0.6667 | 10 | 0.3030 | 0.0611 | 0.3030 | |
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| No log | 0.8 | 12 | 0.2649 | 0.0787 | 0.2649 | |
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| No log | 0.9333 | 14 | 0.2826 | 0.0885 | 0.2828 | |
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| No log | 1.0667 | 16 | 0.2985 | 0.0923 | 0.2988 | |
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| No log | 1.2 | 18 | 0.2796 | 0.1040 | 0.2799 | |
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| No log | 1.3333 | 20 | 0.2595 | 0.0929 | 0.2597 | |
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| No log | 1.4667 | 22 | 0.2462 | 0.0852 | 0.2464 | |
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| No log | 1.6 | 24 | 0.2480 | 0.0852 | 0.2481 | |
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| No log | 1.7333 | 26 | 0.2542 | 0.0890 | 0.2544 | |
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| No log | 1.8667 | 28 | 0.2586 | 0.0997 | 0.2588 | |
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| No log | 2.0 | 30 | 0.2670 | 0.1014 | 0.2673 | |
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| No log | 2.1333 | 32 | 0.2648 | 0.1105 | 0.2650 | |
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| No log | 2.2667 | 34 | 0.2632 | 0.1459 | 0.2634 | |
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| No log | 2.4 | 36 | 0.2674 | 0.1834 | 0.2676 | |
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| No log | 2.5333 | 38 | 0.2628 | 0.1703 | 0.2629 | |
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| No log | 2.6667 | 40 | 0.2527 | 0.1229 | 0.2528 | |
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| No log | 2.8 | 42 | 0.2484 | 0.1022 | 0.2484 | |
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| No log | 2.9333 | 44 | 0.2561 | 0.0997 | 0.2562 | |
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| No log | 3.0667 | 46 | 0.2688 | 0.0846 | 0.2689 | |
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| No log | 3.2 | 48 | 0.2566 | 0.1007 | 0.2567 | |
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| No log | 3.3333 | 50 | 0.2524 | 0.0965 | 0.2525 | |
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| No log | 3.4667 | 52 | 0.2583 | 0.0935 | 0.2584 | |
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| No log | 3.6 | 54 | 0.2587 | 0.1253 | 0.2588 | |
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| No log | 3.7333 | 56 | 0.2574 | 0.1401 | 0.2575 | |
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| No log | 3.8667 | 58 | 0.2677 | 0.1075 | 0.2678 | |
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| No log | 4.0 | 60 | 0.2736 | 0.0953 | 0.2736 | |
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| No log | 4.1333 | 62 | 0.2558 | 0.1301 | 0.2559 | |
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| No log | 4.2667 | 64 | 0.2518 | 0.1067 | 0.2519 | |
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| No log | 4.4 | 66 | 0.2551 | 0.1166 | 0.2552 | |
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| No log | 4.5333 | 68 | 0.2520 | 0.1067 | 0.2521 | |
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| No log | 4.6667 | 70 | 0.2540 | 0.0866 | 0.2541 | |
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| No log | 4.8 | 72 | 0.2633 | 0.1021 | 0.2635 | |
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| No log | 4.9333 | 74 | 0.2704 | 0.0902 | 0.2705 | |
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| No log | 5.0667 | 76 | 0.2725 | 0.0963 | 0.2727 | |
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| No log | 5.2 | 78 | 0.2693 | 0.1081 | 0.2694 | |
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| No log | 5.3333 | 80 | 0.2662 | 0.1004 | 0.2663 | |
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| No log | 5.4667 | 82 | 0.2608 | 0.1055 | 0.2609 | |
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| No log | 5.6 | 84 | 0.2559 | 0.1013 | 0.2560 | |
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| No log | 5.7333 | 86 | 0.2577 | 0.1078 | 0.2578 | |
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| No log | 5.8667 | 88 | 0.2608 | 0.1146 | 0.2608 | |
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| No log | 6.0 | 90 | 0.2533 | 0.1144 | 0.2533 | |
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| No log | 6.1333 | 92 | 0.2490 | 0.1142 | 0.2491 | |
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| No log | 6.2667 | 94 | 0.2520 | 0.0942 | 0.2521 | |
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| No log | 6.4 | 96 | 0.2592 | 0.1080 | 0.2593 | |
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| No log | 6.5333 | 98 | 0.2666 | 0.1319 | 0.2667 | |
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| No log | 6.6667 | 100 | 0.2668 | 0.1521 | 0.2668 | |
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| No log | 6.8 | 102 | 0.2667 | 0.1560 | 0.2667 | |
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| No log | 6.9333 | 104 | 0.2680 | 0.1450 | 0.2681 | |
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| No log | 7.0667 | 106 | 0.2684 | 0.1482 | 0.2685 | |
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| No log | 7.2 | 108 | 0.2672 | 0.1529 | 0.2672 | |
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| No log | 7.3333 | 110 | 0.2659 | 0.1721 | 0.2660 | |
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| No log | 7.4667 | 112 | 0.2665 | 0.1614 | 0.2665 | |
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| No log | 7.6 | 114 | 0.2656 | 0.1651 | 0.2656 | |
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| No log | 7.7333 | 116 | 0.2636 | 0.1577 | 0.2637 | |
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| No log | 7.8667 | 118 | 0.2610 | 0.1613 | 0.2610 | |
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| No log | 8.0 | 120 | 0.2581 | 0.1575 | 0.2581 | |
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| No log | 8.1333 | 122 | 0.2559 | 0.1289 | 0.2559 | |
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| No log | 8.2667 | 124 | 0.2559 | 0.1070 | 0.2559 | |
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| No log | 8.4 | 126 | 0.2569 | 0.1026 | 0.2569 | |
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| No log | 8.5333 | 128 | 0.2575 | 0.1056 | 0.2575 | |
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| No log | 8.6667 | 130 | 0.2582 | 0.1274 | 0.2582 | |
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| No log | 8.8 | 132 | 0.2585 | 0.1272 | 0.2585 | |
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| No log | 8.9333 | 134 | 0.2596 | 0.1306 | 0.2595 | |
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| No log | 9.0667 | 136 | 0.2600 | 0.1101 | 0.2600 | |
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| No log | 9.2 | 138 | 0.2608 | 0.1101 | 0.2607 | |
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| No log | 9.3333 | 140 | 0.2612 | 0.1342 | 0.2612 | |
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| No log | 9.4667 | 142 | 0.2617 | 0.1137 | 0.2617 | |
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| No log | 9.6 | 144 | 0.2619 | 0.1283 | 0.2619 | |
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| No log | 9.7333 | 146 | 0.2620 | 0.1414 | 0.2620 | |
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| No log | 9.8667 | 148 | 0.2621 | 0.1414 | 0.2621 | |
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| No log | 10.0 | 150 | 0.2622 | 0.1283 | 0.2622 | |
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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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