--- base_model: aubmindlab/bert-base-arabertv02 tags: - generated_from_trainer model-index: - name: arabert_cross_relevance_task5_fold2 results: [] --- # arabert_cross_relevance_task5_fold2 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: 0.3102 - Qwk: 0.0 - Mse: 0.3106 ## 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 | 0.8487 | 0.0102 | 0.8475 | | No log | 0.25 | 4 | 0.3505 | 0.1091 | 0.3504 | | No log | 0.375 | 6 | 0.4480 | 0.0599 | 0.4484 | | No log | 0.5 | 8 | 0.3079 | 0.0534 | 0.3080 | | No log | 0.625 | 10 | 0.3015 | 0.0245 | 0.3018 | | No log | 0.75 | 12 | 0.3131 | 0.0 | 0.3134 | | No log | 0.875 | 14 | 0.3140 | 0.0 | 0.3143 | | No log | 1.0 | 16 | 0.3539 | -0.0164 | 0.3543 | | No log | 1.125 | 18 | 0.3562 | -0.0164 | 0.3567 | | No log | 1.25 | 20 | 0.3449 | 0.0 | 0.3454 | | No log | 1.375 | 22 | 0.3408 | 0.0 | 0.3412 | | No log | 1.5 | 24 | 0.3416 | 0.0 | 0.3421 | | No log | 1.625 | 26 | 0.3321 | 0.0 | 0.3325 | | No log | 1.75 | 28 | 0.3068 | 0.0 | 0.3072 | | No log | 1.875 | 30 | 0.3135 | 0.0 | 0.3139 | | No log | 2.0 | 32 | 0.3564 | 0.0122 | 0.3570 | | No log | 2.125 | 34 | 0.3393 | 0.0 | 0.3399 | | No log | 2.25 | 36 | 0.2992 | 0.0 | 0.2996 | | No log | 2.375 | 38 | 0.3002 | 0.0 | 0.3005 | | No log | 2.5 | 40 | 0.3396 | 0.0122 | 0.3402 | | No log | 2.625 | 42 | 0.3703 | 0.0368 | 0.3710 | | No log | 2.75 | 44 | 0.3599 | 0.0203 | 0.3605 | | No log | 2.875 | 46 | 0.3243 | 0.0 | 0.3248 | | No log | 3.0 | 48 | 0.3164 | 0.0 | 0.3169 | | No log | 3.125 | 50 | 0.3455 | -0.0208 | 0.3460 | | No log | 3.25 | 52 | 0.3796 | -0.0707 | 0.3802 | | No log | 3.375 | 54 | 0.3560 | -0.0495 | 0.3565 | | No log | 3.5 | 56 | 0.3121 | 0.0 | 0.3125 | | No log | 3.625 | 58 | 0.2932 | 0.0 | 0.2935 | | No log | 3.75 | 60 | 0.2950 | 0.0 | 0.2953 | | No log | 3.875 | 62 | 0.3159 | 0.0 | 0.3163 | | No log | 4.0 | 64 | 0.3268 | 0.0 | 0.3273 | | No log | 4.125 | 66 | 0.3199 | 0.0 | 0.3203 | | No log | 4.25 | 68 | 0.3055 | 0.0 | 0.3059 | | No log | 4.375 | 70 | 0.3033 | 0.0 | 0.3037 | | No log | 4.5 | 72 | 0.3090 | 0.0 | 0.3094 | | No log | 4.625 | 74 | 0.3329 | 0.0 | 0.3333 | | No log | 4.75 | 76 | 0.3437 | 0.0 | 0.3442 | | No log | 4.875 | 78 | 0.3238 | 0.0 | 0.3242 | | No log | 5.0 | 80 | 0.2995 | 0.0 | 0.2998 | | No log | 5.125 | 82 | 0.2952 | 0.0 | 0.2954 | | No log | 5.25 | 84 | 0.3110 | 0.0122 | 0.3113 | | No log | 5.375 | 86 | 0.3451 | -0.0329 | 0.3455 | | No log | 5.5 | 88 | 0.3521 | -0.0373 | 0.3526 | | No log | 5.625 | 90 | 0.3417 | -0.0329 | 0.3422 | | No log | 5.75 | 92 | 0.3246 | 0.0122 | 0.3250 | | No log | 5.875 | 94 | 0.3260 | 0.0122 | 0.3264 | | No log | 6.0 | 96 | 0.3312 | 0.0 | 0.3316 | | No log | 6.125 | 98 | 0.3222 | 0.0 | 0.3226 | | No log | 6.25 | 100 | 0.3187 | 0.0 | 0.3191 | | No log | 6.375 | 102 | 0.3168 | 0.0122 | 0.3171 | | No log | 6.5 | 104 | 0.3231 | 0.0122 | 0.3235 | | No log | 6.625 | 106 | 0.3288 | 0.0122 | 0.3292 | | No log | 6.75 | 108 | 0.3225 | 0.0122 | 0.3229 | | No log | 6.875 | 110 | 0.3117 | 0.0122 | 0.3120 | | No log | 7.0 | 112 | 0.3032 | 0.0 | 0.3034 | | No log | 7.125 | 114 | 0.3022 | 0.0 | 0.3024 | | No log | 7.25 | 116 | 0.3089 | 0.0122 | 0.3091 | | No log | 7.375 | 118 | 0.3150 | 0.0122 | 0.3153 | | No log | 7.5 | 120 | 0.3157 | 0.0122 | 0.3161 | | No log | 7.625 | 122 | 0.3102 | 0.0122 | 0.3106 | | No log | 7.75 | 124 | 0.3060 | 0.0 | 0.3063 | | No log | 7.875 | 126 | 0.3061 | 0.0 | 0.3063 | | No log | 8.0 | 128 | 0.3089 | 0.0122 | 0.3092 | | No log | 8.125 | 130 | 0.3108 | 0.0122 | 0.3111 | | No log | 8.25 | 132 | 0.3154 | 0.0122 | 0.3158 | | No log | 8.375 | 134 | 0.3210 | 0.0122 | 0.3215 | | No log | 8.5 | 136 | 0.3202 | 0.0122 | 0.3206 | | No log | 8.625 | 138 | 0.3172 | 0.0122 | 0.3176 | | No log | 8.75 | 140 | 0.3139 | 0.0 | 0.3143 | | No log | 8.875 | 142 | 0.3121 | 0.0 | 0.3125 | | No log | 9.0 | 144 | 0.3115 | 0.0 | 0.3118 | | No log | 9.125 | 146 | 0.3118 | 0.0 | 0.3121 | | No log | 9.25 | 148 | 0.3121 | 0.0 | 0.3124 | | No log | 9.375 | 150 | 0.3120 | 0.0 | 0.3124 | | No log | 9.5 | 152 | 0.3116 | 0.0 | 0.3119 | | No log | 9.625 | 154 | 0.3110 | 0.0 | 0.3114 | | No log | 9.75 | 156 | 0.3106 | 0.0 | 0.3109 | | No log | 9.875 | 158 | 0.3103 | 0.0 | 0.3106 | | No log | 10.0 | 160 | 0.3102 | 0.0 | 0.3106 | ### Framework versions - Transformers 4.44.0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1