--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_development_task1_fold5 results: [] --- # arabert_cross_development_task1_fold5 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: 0.3225 - Qwk: 0.7089 - Mse: 0.3218 ## 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 | 1.6054 | 0.1118 | 1.6042 | | No log | 0.2667 | 4 | 0.7796 | 0.3420 | 0.7792 | | No log | 0.4 | 6 | 0.8606 | 0.4875 | 0.8600 | | No log | 0.5333 | 8 | 0.7185 | 0.6145 | 0.7176 | | No log | 0.6667 | 10 | 0.4960 | 0.5784 | 0.4951 | | No log | 0.8 | 12 | 0.4504 | 0.5814 | 0.4497 | | No log | 0.9333 | 14 | 0.4103 | 0.6104 | 0.4096 | | No log | 1.0667 | 16 | 0.3725 | 0.6808 | 0.3715 | | No log | 1.2 | 18 | 0.4101 | 0.8013 | 0.4091 | | No log | 1.3333 | 20 | 0.3292 | 0.7235 | 0.3286 | | No log | 1.4667 | 22 | 0.3212 | 0.6809 | 0.3206 | | No log | 1.6 | 24 | 0.3406 | 0.7512 | 0.3398 | | No log | 1.7333 | 26 | 0.3852 | 0.7534 | 0.3842 | | No log | 1.8667 | 28 | 0.3920 | 0.7341 | 0.3909 | | No log | 2.0 | 30 | 0.4486 | 0.7835 | 0.4475 | | No log | 2.1333 | 32 | 0.4015 | 0.7929 | 0.4005 | | No log | 2.2667 | 34 | 0.2966 | 0.7228 | 0.2959 | | No log | 2.4 | 36 | 0.3163 | 0.6675 | 0.3156 | | No log | 2.5333 | 38 | 0.2965 | 0.7270 | 0.2958 | | No log | 2.6667 | 40 | 0.3334 | 0.7868 | 0.3325 | | No log | 2.8 | 42 | 0.3892 | 0.7967 | 0.3882 | | No log | 2.9333 | 44 | 0.3635 | 0.7640 | 0.3626 | | No log | 3.0667 | 46 | 0.3415 | 0.7020 | 0.3408 | | No log | 3.2 | 48 | 0.3452 | 0.6985 | 0.3445 | | No log | 3.3333 | 50 | 0.3467 | 0.7485 | 0.3460 | | No log | 3.4667 | 52 | 0.3606 | 0.7778 | 0.3598 | | No log | 3.6 | 54 | 0.3419 | 0.7735 | 0.3412 | | No log | 3.7333 | 56 | 0.3217 | 0.7477 | 0.3210 | | No log | 3.8667 | 58 | 0.3254 | 0.6951 | 0.3248 | | No log | 4.0 | 60 | 0.3366 | 0.6811 | 0.3360 | | No log | 4.1333 | 62 | 0.3255 | 0.7328 | 0.3248 | | No log | 4.2667 | 64 | 0.3255 | 0.7574 | 0.3248 | | No log | 4.4 | 66 | 0.3264 | 0.7713 | 0.3257 | | No log | 4.5333 | 68 | 0.3260 | 0.7538 | 0.3253 | | No log | 4.6667 | 70 | 0.3303 | 0.7599 | 0.3295 | | No log | 4.8 | 72 | 0.3278 | 0.7285 | 0.3270 | | No log | 4.9333 | 74 | 0.3399 | 0.7039 | 0.3391 | | No log | 5.0667 | 76 | 0.3696 | 0.6751 | 0.3689 | | No log | 5.2 | 78 | 0.3565 | 0.6740 | 0.3558 | | No log | 5.3333 | 80 | 0.3177 | 0.7247 | 0.3171 | | No log | 5.4667 | 82 | 0.3107 | 0.7637 | 0.3100 | | No log | 5.6 | 84 | 0.3037 | 0.7643 | 0.3031 | | No log | 5.7333 | 86 | 0.2968 | 0.7380 | 0.2962 | | No log | 5.8667 | 88 | 0.3026 | 0.6895 | 0.3020 | | No log | 6.0 | 90 | 0.2948 | 0.7283 | 0.2942 | | No log | 6.1333 | 92 | 0.2968 | 0.7351 | 0.2962 | | No log | 6.2667 | 94 | 0.3054 | 0.6898 | 0.3048 | | No log | 6.4 | 96 | 0.3335 | 0.6564 | 0.3329 | | No log | 6.5333 | 98 | 0.3257 | 0.6723 | 0.3250 | | No log | 6.6667 | 100 | 0.3148 | 0.7398 | 0.3141 | | No log | 6.8 | 102 | 0.3244 | 0.7519 | 0.3237 | | No log | 6.9333 | 104 | 0.3201 | 0.7549 | 0.3194 | | No log | 7.0667 | 106 | 0.3197 | 0.7204 | 0.3190 | | No log | 7.2 | 108 | 0.3241 | 0.7042 | 0.3234 | | No log | 7.3333 | 110 | 0.3257 | 0.7232 | 0.3250 | | No log | 7.4667 | 112 | 0.3300 | 0.7399 | 0.3293 | | No log | 7.6 | 114 | 0.3300 | 0.7379 | 0.3292 | | No log | 7.7333 | 116 | 0.3299 | 0.7286 | 0.3292 | | No log | 7.8667 | 118 | 0.3273 | 0.7096 | 0.3266 | | No log | 8.0 | 120 | 0.3291 | 0.6958 | 0.3284 | | No log | 8.1333 | 122 | 0.3265 | 0.6826 | 0.3258 | | No log | 8.2667 | 124 | 0.3190 | 0.7007 | 0.3182 | | No log | 8.4 | 126 | 0.3131 | 0.7151 | 0.3123 | | No log | 8.5333 | 128 | 0.3135 | 0.7284 | 0.3127 | | No log | 8.6667 | 130 | 0.3156 | 0.7284 | 0.3148 | | No log | 8.8 | 132 | 0.3172 | 0.7253 | 0.3164 | | No log | 8.9333 | 134 | 0.3198 | 0.7157 | 0.3190 | | No log | 9.0667 | 136 | 0.3222 | 0.7034 | 0.3214 | | No log | 9.2 | 138 | 0.3213 | 0.7089 | 0.3205 | | No log | 9.3333 | 140 | 0.3194 | 0.7170 | 0.3186 | | No log | 9.4667 | 142 | 0.3189 | 0.7241 | 0.3181 | | No log | 9.6 | 144 | 0.3199 | 0.7239 | 0.3191 | | No log | 9.7333 | 146 | 0.3215 | 0.7103 | 0.3207 | | No log | 9.8667 | 148 | 0.3223 | 0.7089 | 0.3215 | | No log | 10.0 | 150 | 0.3225 | 0.7089 | 0.3218 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1