--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_relevance_task1_fold4 results: [] --- # arabert_cross_relevance_task1_fold4 This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co./aubmindlab/bert-base-arabertv02) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2462 - Qwk: 0.2970 - Mse: 0.2462 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| | No log | 0.125 | 2 | 1.1439 | 0.0152 | 1.1439 | | No log | 0.25 | 4 | 0.4542 | 0.1058 | 0.4542 | | No log | 0.375 | 6 | 0.3468 | 0.2290 | 0.3468 | | No log | 0.5 | 8 | 0.3648 | 0.1816 | 0.3648 | | No log | 0.625 | 10 | 0.4917 | 0.2054 | 0.4917 | | No log | 0.75 | 12 | 0.3361 | 0.2720 | 0.3361 | | No log | 0.875 | 14 | 0.2581 | 0.2606 | 0.2581 | | No log | 1.0 | 16 | 0.2596 | 0.3452 | 0.2596 | | No log | 1.125 | 18 | 0.2652 | 0.3776 | 0.2652 | | No log | 1.25 | 20 | 0.2495 | 0.3605 | 0.2495 | | No log | 1.375 | 22 | 0.2883 | 0.2801 | 0.2883 | | No log | 1.5 | 24 | 0.3460 | 0.2241 | 0.3460 | | No log | 1.625 | 26 | 0.3144 | 0.2483 | 0.3144 | | No log | 1.75 | 28 | 0.2568 | 0.3617 | 0.2568 | | No log | 1.875 | 30 | 0.2645 | 0.3732 | 0.2645 | | No log | 2.0 | 32 | 0.2745 | 0.3354 | 0.2745 | | No log | 2.125 | 34 | 0.2642 | 0.3416 | 0.2642 | | No log | 2.25 | 36 | 0.2371 | 0.3323 | 0.2371 | | No log | 2.375 | 38 | 0.2288 | 0.3278 | 0.2288 | | No log | 2.5 | 40 | 0.2336 | 0.3517 | 0.2336 | | No log | 2.625 | 42 | 0.2327 | 0.3836 | 0.2327 | | No log | 2.75 | 44 | 0.2341 | 0.4092 | 0.2341 | | No log | 2.875 | 46 | 0.2410 | 0.3449 | 0.2410 | | No log | 3.0 | 48 | 0.2695 | 0.3349 | 0.2695 | | No log | 3.125 | 50 | 0.2860 | 0.2593 | 0.2860 | | No log | 3.25 | 52 | 0.2584 | 0.2899 | 0.2584 | | No log | 3.375 | 54 | 0.2408 | 0.3216 | 0.2408 | | No log | 3.5 | 56 | 0.2232 | 0.3190 | 0.2232 | | No log | 3.625 | 58 | 0.2179 | 0.3172 | 0.2179 | | No log | 3.75 | 60 | 0.2229 | 0.3029 | 0.2229 | | No log | 3.875 | 62 | 0.2274 | 0.2855 | 0.2274 | | No log | 4.0 | 64 | 0.2344 | 0.2787 | 0.2344 | | No log | 4.125 | 66 | 0.2449 | 0.2616 | 0.2449 | | No log | 4.25 | 68 | 0.2478 | 0.2753 | 0.2478 | | No log | 4.375 | 70 | 0.2462 | 0.3017 | 0.2462 | | No log | 4.5 | 72 | 0.2513 | 0.3343 | 0.2513 | | No log | 4.625 | 74 | 0.2528 | 0.3607 | 0.2528 | | No log | 4.75 | 76 | 0.2439 | 0.3638 | 0.2439 | | No log | 4.875 | 78 | 0.2300 | 0.3536 | 0.2300 | | No log | 5.0 | 80 | 0.2244 | 0.3127 | 0.2244 | | No log | 5.125 | 82 | 0.2243 | 0.3034 | 0.2243 | | No log | 5.25 | 84 | 0.2290 | 0.2891 | 0.2290 | | No log | 5.375 | 86 | 0.2240 | 0.3203 | 0.2240 | | No log | 5.5 | 88 | 0.2237 | 0.3522 | 0.2237 | | No log | 5.625 | 90 | 0.2245 | 0.3408 | 0.2245 | | No log | 5.75 | 92 | 0.2258 | 0.3271 | 0.2258 | | No log | 5.875 | 94 | 0.2291 | 0.3021 | 0.2291 | | No log | 6.0 | 96 | 0.2407 | 0.2882 | 0.2407 | | No log | 6.125 | 98 | 0.2527 | 0.2783 | 0.2527 | | No log | 6.25 | 100 | 0.2560 | 0.2686 | 0.2560 | | No log | 6.375 | 102 | 0.2524 | 0.2882 | 0.2524 | | No log | 6.5 | 104 | 0.2478 | 0.3136 | 0.2478 | | No log | 6.625 | 106 | 0.2439 | 0.3199 | 0.2439 | | No log | 6.75 | 108 | 0.2489 | 0.3136 | 0.2489 | | No log | 6.875 | 110 | 0.2507 | 0.3033 | 0.2507 | | No log | 7.0 | 112 | 0.2439 | 0.3109 | 0.2439 | | No log | 7.125 | 114 | 0.2358 | 0.3238 | 0.2358 | | No log | 7.25 | 116 | 0.2350 | 0.3238 | 0.2350 | | No log | 7.375 | 118 | 0.2450 | 0.3069 | 0.2450 | | No log | 7.5 | 120 | 0.2670 | 0.2709 | 0.2670 | | No log | 7.625 | 122 | 0.2757 | 0.2529 | 0.2757 | | No log | 7.75 | 124 | 0.2626 | 0.2709 | 0.2626 | | No log | 7.875 | 126 | 0.2540 | 0.2774 | 0.2540 | | No log | 8.0 | 128 | 0.2430 | 0.2904 | 0.2430 | | No log | 8.125 | 130 | 0.2346 | 0.2878 | 0.2346 | | No log | 8.25 | 132 | 0.2324 | 0.2981 | 0.2324 | | No log | 8.375 | 134 | 0.2325 | 0.2981 | 0.2325 | | No log | 8.5 | 136 | 0.2349 | 0.2878 | 0.2349 | | No log | 8.625 | 138 | 0.2374 | 0.3005 | 0.2374 | | No log | 8.75 | 140 | 0.2415 | 0.2942 | 0.2415 | | No log | 8.875 | 142 | 0.2456 | 0.2942 | 0.2456 | | No log | 9.0 | 144 | 0.2483 | 0.2942 | 0.2483 | | No log | 9.125 | 146 | 0.2484 | 0.2942 | 0.2484 | | No log | 9.25 | 148 | 0.2480 | 0.2970 | 0.2480 | | No log | 9.375 | 150 | 0.2488 | 0.2970 | 0.2488 | | No log | 9.5 | 152 | 0.2480 | 0.2970 | 0.2480 | | No log | 9.625 | 154 | 0.2465 | 0.2970 | 0.2465 | | No log | 9.75 | 156 | 0.2462 | 0.2942 | 0.2462 | | No log | 9.875 | 158 | 0.2463 | 0.2970 | 0.2463 | | No log | 10.0 | 160 | 0.2462 | 0.2970 | 0.2462 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1