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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_task6_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_task6_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: 0.2663 |
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- Qwk: 0.1037 |
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- Mse: 0.2666 |
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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 | 0.6210 | 0.0393 | 0.6211 | |
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| No log | 0.25 | 4 | 0.2908 | 0.1547 | 0.2908 | |
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| No log | 0.375 | 6 | 0.2874 | 0.0578 | 0.2874 | |
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| No log | 0.5 | 8 | 0.4029 | 0.0871 | 0.4030 | |
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| No log | 0.625 | 10 | 0.3376 | 0.0431 | 0.3380 | |
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| No log | 0.75 | 12 | 0.2435 | 0.0180 | 0.2438 | |
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| No log | 0.875 | 14 | 0.2523 | 0.0961 | 0.2524 | |
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| No log | 1.0 | 16 | 0.2567 | 0.1388 | 0.2568 | |
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| No log | 1.125 | 18 | 0.2419 | 0.0918 | 0.2421 | |
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| No log | 1.25 | 20 | 0.2428 | 0.1144 | 0.2430 | |
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| No log | 1.375 | 22 | 0.2547 | 0.1135 | 0.2549 | |
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| No log | 1.5 | 24 | 0.2577 | 0.1333 | 0.2580 | |
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| No log | 1.625 | 26 | 0.2622 | 0.1251 | 0.2625 | |
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| No log | 1.75 | 28 | 0.2584 | 0.1527 | 0.2587 | |
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| No log | 1.875 | 30 | 0.2572 | 0.1427 | 0.2574 | |
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| No log | 2.0 | 32 | 0.2550 | 0.1355 | 0.2552 | |
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| No log | 2.125 | 34 | 0.2553 | 0.1382 | 0.2554 | |
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| No log | 2.25 | 36 | 0.2485 | 0.1178 | 0.2486 | |
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| No log | 2.375 | 38 | 0.2485 | 0.0965 | 0.2487 | |
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| No log | 2.5 | 40 | 0.2463 | 0.0999 | 0.2465 | |
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| No log | 2.625 | 42 | 0.2473 | 0.1607 | 0.2475 | |
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| No log | 2.75 | 44 | 0.2547 | 0.2134 | 0.2549 | |
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| No log | 2.875 | 46 | 0.2547 | 0.1888 | 0.2549 | |
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| No log | 3.0 | 48 | 0.2540 | 0.1555 | 0.2542 | |
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| No log | 3.125 | 50 | 0.2562 | 0.1232 | 0.2565 | |
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| No log | 3.25 | 52 | 0.2605 | 0.1037 | 0.2607 | |
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| No log | 3.375 | 54 | 0.2527 | 0.1245 | 0.2529 | |
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| No log | 3.5 | 56 | 0.2460 | 0.1932 | 0.2462 | |
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| No log | 3.625 | 58 | 0.2492 | 0.1938 | 0.2494 | |
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| No log | 3.75 | 60 | 0.2473 | 0.1556 | 0.2476 | |
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| No log | 3.875 | 62 | 0.2559 | 0.1436 | 0.2563 | |
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| No log | 4.0 | 64 | 0.2788 | 0.0972 | 0.2792 | |
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| No log | 4.125 | 66 | 0.2859 | 0.0972 | 0.2863 | |
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| No log | 4.25 | 68 | 0.2581 | 0.1146 | 0.2584 | |
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| No log | 4.375 | 70 | 0.2414 | 0.1330 | 0.2417 | |
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| No log | 4.5 | 72 | 0.2402 | 0.1344 | 0.2404 | |
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| No log | 4.625 | 74 | 0.2406 | 0.1345 | 0.2408 | |
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| No log | 4.75 | 76 | 0.2471 | 0.1446 | 0.2473 | |
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| No log | 4.875 | 78 | 0.2567 | 0.1348 | 0.2570 | |
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| No log | 5.0 | 80 | 0.2688 | 0.1201 | 0.2692 | |
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| No log | 5.125 | 82 | 0.2619 | 0.1313 | 0.2622 | |
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| No log | 5.25 | 84 | 0.2502 | 0.1611 | 0.2505 | |
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| No log | 5.375 | 86 | 0.2499 | 0.1686 | 0.2501 | |
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| No log | 5.5 | 88 | 0.2497 | 0.1609 | 0.2499 | |
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| No log | 5.625 | 90 | 0.2590 | 0.1279 | 0.2592 | |
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| No log | 5.75 | 92 | 0.2625 | 0.1201 | 0.2628 | |
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| No log | 5.875 | 94 | 0.2585 | 0.1245 | 0.2588 | |
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| No log | 6.0 | 96 | 0.2639 | 0.1100 | 0.2642 | |
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| No log | 6.125 | 98 | 0.2653 | 0.1135 | 0.2656 | |
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| No log | 6.25 | 100 | 0.2567 | 0.1199 | 0.2570 | |
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| No log | 6.375 | 102 | 0.2499 | 0.1229 | 0.2502 | |
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| No log | 6.5 | 104 | 0.2482 | 0.1311 | 0.2484 | |
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| No log | 6.625 | 106 | 0.2482 | 0.1244 | 0.2485 | |
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| No log | 6.75 | 108 | 0.2511 | 0.1210 | 0.2514 | |
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| No log | 6.875 | 110 | 0.2518 | 0.1347 | 0.2521 | |
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| No log | 7.0 | 112 | 0.2478 | 0.1381 | 0.2481 | |
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| No log | 7.125 | 114 | 0.2465 | 0.1415 | 0.2468 | |
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| No log | 7.25 | 116 | 0.2476 | 0.1379 | 0.2478 | |
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| No log | 7.375 | 118 | 0.2505 | 0.1276 | 0.2508 | |
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| No log | 7.5 | 120 | 0.2531 | 0.1381 | 0.2534 | |
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| No log | 7.625 | 122 | 0.2620 | 0.1056 | 0.2623 | |
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| No log | 7.75 | 124 | 0.2719 | 0.1180 | 0.2723 | |
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| No log | 7.875 | 126 | 0.2767 | 0.1149 | 0.2770 | |
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| No log | 8.0 | 128 | 0.2722 | 0.1095 | 0.2726 | |
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| No log | 8.125 | 130 | 0.2637 | 0.1146 | 0.2640 | |
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| No log | 8.25 | 132 | 0.2588 | 0.1178 | 0.2591 | |
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| No log | 8.375 | 134 | 0.2564 | 0.1108 | 0.2567 | |
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| No log | 8.5 | 136 | 0.2573 | 0.1042 | 0.2576 | |
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| No log | 8.625 | 138 | 0.2581 | 0.0976 | 0.2584 | |
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| No log | 8.75 | 140 | 0.2594 | 0.0976 | 0.2597 | |
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| No log | 8.875 | 142 | 0.2629 | 0.0979 | 0.2632 | |
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| No log | 9.0 | 144 | 0.2665 | 0.0946 | 0.2669 | |
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| No log | 9.125 | 146 | 0.2676 | 0.0946 | 0.2679 | |
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| No log | 9.25 | 148 | 0.2670 | 0.0946 | 0.2673 | |
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| No log | 9.375 | 150 | 0.2667 | 0.0946 | 0.2671 | |
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| No log | 9.5 | 152 | 0.2663 | 0.0979 | 0.2666 | |
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| No log | 9.625 | 154 | 0.2661 | 0.0979 | 0.2664 | |
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| No log | 9.75 | 156 | 0.2659 | 0.0979 | 0.2663 | |
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| No log | 9.875 | 158 | 0.2661 | 0.1037 | 0.2664 | |
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| No log | 10.0 | 160 | 0.2663 | 0.1037 | 0.2666 | |
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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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