--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_relevance_task7_fold1 results: [] --- # arabert_cross_relevance_task7_fold1 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: 0.3047 - Qwk: 0.0332 - Mse: 0.3047 ## 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 | 0.1333 | 2 | 1.2830 | 0.0016 | 1.2830 | | No log | 0.2667 | 4 | 0.3134 | 0.0127 | 0.3134 | | No log | 0.4 | 6 | 0.1648 | 0.1104 | 0.1648 | | No log | 0.5333 | 8 | 0.1251 | 0.0517 | 0.1251 | | No log | 0.6667 | 10 | 0.2224 | 0.0017 | 0.2224 | | No log | 0.8 | 12 | 0.2590 | 0.0094 | 0.2590 | | No log | 0.9333 | 14 | 0.1796 | 0.0127 | 0.1796 | | No log | 1.0667 | 16 | 0.1308 | 0.0397 | 0.1308 | | No log | 1.2 | 18 | 0.1449 | 0.0303 | 0.1449 | | No log | 1.3333 | 20 | 0.1645 | 0.0288 | 0.1645 | | No log | 1.4667 | 22 | 0.1859 | 0.0270 | 0.1859 | | No log | 1.6 | 24 | 0.1923 | 0.0425 | 0.1923 | | No log | 1.7333 | 26 | 0.1918 | 0.0319 | 0.1918 | | No log | 1.8667 | 28 | 0.2199 | 0.0290 | 0.2199 | | No log | 2.0 | 30 | 0.2212 | 0.0273 | 0.2212 | | No log | 2.1333 | 32 | 0.1858 | 0.0273 | 0.1858 | | No log | 2.2667 | 34 | 0.1779 | 0.0270 | 0.1779 | | No log | 2.4 | 36 | 0.2133 | 0.0270 | 0.2133 | | No log | 2.5333 | 38 | 0.2467 | 0.0339 | 0.2467 | | No log | 2.6667 | 40 | 0.2211 | 0.0355 | 0.2211 | | No log | 2.8 | 42 | 0.1890 | 0.0355 | 0.1890 | | No log | 2.9333 | 44 | 0.2091 | 0.0270 | 0.2091 | | No log | 3.0667 | 46 | 0.2659 | 0.0254 | 0.2659 | | No log | 3.2 | 48 | 0.2479 | 0.0235 | 0.2479 | | No log | 3.3333 | 50 | 0.2076 | 0.0284 | 0.2076 | | No log | 3.4667 | 52 | 0.1978 | 0.0351 | 0.1978 | | No log | 3.6 | 54 | 0.2247 | 0.0334 | 0.2247 | | No log | 3.7333 | 56 | 0.2784 | 0.0319 | 0.2784 | | No log | 3.8667 | 58 | 0.2815 | 0.0217 | 0.2815 | | No log | 4.0 | 60 | 0.2597 | 0.0235 | 0.2597 | | No log | 4.1333 | 62 | 0.2093 | 0.0304 | 0.2093 | | No log | 4.2667 | 64 | 0.2137 | 0.0287 | 0.2137 | | No log | 4.4 | 66 | 0.2532 | 0.0235 | 0.2532 | | No log | 4.5333 | 68 | 0.2399 | 0.0251 | 0.2399 | | No log | 4.6667 | 70 | 0.2137 | 0.0338 | 0.2137 | | No log | 4.8 | 72 | 0.2516 | 0.0235 | 0.2516 | | No log | 4.9333 | 74 | 0.2786 | 0.0319 | 0.2786 | | No log | 5.0667 | 76 | 0.3017 | 0.0319 | 0.3017 | | No log | 5.2 | 78 | 0.2701 | 0.0235 | 0.2701 | | No log | 5.3333 | 80 | 0.2234 | 0.0301 | 0.2234 | | No log | 5.4667 | 82 | 0.2231 | 0.0301 | 0.2231 | | No log | 5.6 | 84 | 0.2419 | 0.0284 | 0.2419 | | No log | 5.7333 | 86 | 0.2839 | 0.0233 | 0.2839 | | No log | 5.8667 | 88 | 0.2964 | 0.0233 | 0.2964 | | No log | 6.0 | 90 | 0.2986 | 0.0214 | 0.2986 | | No log | 6.1333 | 92 | 0.2565 | 0.0317 | 0.2565 | | No log | 6.2667 | 94 | 0.2203 | 0.0334 | 0.2203 | | No log | 6.4 | 96 | 0.2553 | 0.0317 | 0.2553 | | No log | 6.5333 | 98 | 0.3609 | 0.0193 | 0.3609 | | No log | 6.6667 | 100 | 0.4216 | 0.0206 | 0.4216 | | No log | 6.8 | 102 | 0.3627 | 0.0225 | 0.3627 | | No log | 6.9333 | 104 | 0.2543 | 0.0317 | 0.2543 | | No log | 7.0667 | 106 | 0.2003 | 0.0312 | 0.2003 | | No log | 7.2 | 108 | 0.2014 | 0.0295 | 0.2014 | | No log | 7.3333 | 110 | 0.2374 | 0.0301 | 0.2374 | | No log | 7.4667 | 112 | 0.3176 | 0.0263 | 0.3176 | | No log | 7.6 | 114 | 0.3811 | 0.0237 | 0.3811 | | No log | 7.7333 | 116 | 0.3686 | 0.0285 | 0.3686 | | No log | 7.8667 | 118 | 0.3010 | 0.0260 | 0.3010 | | No log | 8.0 | 120 | 0.2467 | 0.0317 | 0.2467 | | No log | 8.1333 | 122 | 0.2371 | 0.0334 | 0.2371 | | No log | 8.2667 | 124 | 0.2613 | 0.0361 | 0.2613 | | No log | 8.4 | 126 | 0.2959 | 0.0310 | 0.2959 | | No log | 8.5333 | 128 | 0.3317 | 0.0225 | 0.3317 | | No log | 8.6667 | 130 | 0.3288 | 0.0240 | 0.3288 | | No log | 8.8 | 132 | 0.2998 | 0.0370 | 0.2998 | | No log | 8.9333 | 134 | 0.2797 | 0.0341 | 0.2797 | | No log | 9.0667 | 136 | 0.2625 | 0.0441 | 0.2625 | | No log | 9.2 | 138 | 0.2672 | 0.0421 | 0.2672 | | No log | 9.3333 | 140 | 0.2738 | 0.0421 | 0.2738 | | No log | 9.4667 | 142 | 0.2892 | 0.0401 | 0.2892 | | No log | 9.6 | 144 | 0.3017 | 0.0366 | 0.3017 | | No log | 9.7333 | 146 | 0.3079 | 0.0332 | 0.3079 | | No log | 9.8667 | 148 | 0.3065 | 0.0332 | 0.3065 | | No log | 10.0 | 150 | 0.3047 | 0.0332 | 0.3047 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1