ArabicNewSplits8_usingALLEssays_FineTuningAraBERT_run1_AugV5_k16_task1_organization

This model is a fine-tuned version of aubmindlab/bert-base-arabertv02 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8035
  • Qwk: 0.6572
  • Mse: 0.8035
  • Rmse: 0.8964

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 100

Training results

Training Loss Epoch Step Validation Loss Qwk Mse Rmse
No log 0.025 2 5.4649 -0.0128 5.4649 2.3377
No log 0.05 4 3.2387 0.0639 3.2387 1.7996
No log 0.075 6 2.0832 0.1250 2.0832 1.4433
No log 0.1 8 1.9833 0.0176 1.9833 1.4083
No log 0.125 10 1.5524 0.0235 1.5524 1.2459
No log 0.15 12 1.2340 0.2479 1.2340 1.1108
No log 0.175 14 1.3463 0.0794 1.3463 1.1603
No log 0.2 16 1.2583 0.1792 1.2583 1.1217
No log 0.225 18 1.2432 0.0828 1.2432 1.1150
No log 0.25 20 1.2427 0.0738 1.2427 1.1147
No log 0.275 22 1.2553 0.1145 1.2553 1.1204
No log 0.3 24 1.2581 0.1325 1.2581 1.1216
No log 0.325 26 1.2115 0.2016 1.2115 1.1007
No log 0.35 28 1.1368 0.2548 1.1368 1.0662
No log 0.375 30 1.0761 0.2284 1.0761 1.0373
No log 0.4 32 1.0700 0.2251 1.0700 1.0344
No log 0.425 34 1.0757 0.3399 1.0757 1.0371
No log 0.45 36 1.0625 0.4006 1.0625 1.0308
No log 0.475 38 1.0312 0.3076 1.0312 1.0155
No log 0.5 40 1.0411 0.3083 1.0411 1.0204
No log 0.525 42 1.0637 0.3614 1.0637 1.0314
No log 0.55 44 1.2229 0.3106 1.2229 1.1059
No log 0.575 46 1.4320 0.2372 1.4320 1.1967
No log 0.6 48 1.6702 0.2606 1.6702 1.2924
No log 0.625 50 1.5867 0.2793 1.5867 1.2596
No log 0.65 52 1.6982 0.2606 1.6982 1.3031
No log 0.675 54 1.6379 0.2793 1.6379 1.2798
No log 0.7 56 1.4878 0.2738 1.4878 1.2197
No log 0.725 58 1.3186 0.2696 1.3186 1.1483
No log 0.75 60 1.2437 0.2666 1.2437 1.1152
No log 0.775 62 1.0333 0.3824 1.0333 1.0165
No log 0.8 64 0.8869 0.4953 0.8869 0.9418
No log 0.825 66 0.9221 0.4320 0.9221 0.9602
No log 0.85 68 1.0071 0.4001 1.0071 1.0035
No log 0.875 70 1.0602 0.3451 1.0602 1.0296
No log 0.9 72 1.0450 0.3763 1.0450 1.0222
No log 0.925 74 1.1075 0.3389 1.1075 1.0524
No log 0.95 76 1.2508 0.2569 1.2508 1.1184
No log 0.975 78 1.3163 0.2262 1.3163 1.1473
No log 1.0 80 1.1777 0.3192 1.1777 1.0852
No log 1.025 82 1.0307 0.3603 1.0307 1.0153
No log 1.05 84 0.8842 0.4624 0.8842 0.9403
No log 1.075 86 0.8078 0.5342 0.8078 0.8988
No log 1.1 88 0.7544 0.5240 0.7544 0.8686
No log 1.125 90 0.7148 0.5735 0.7148 0.8455
No log 1.15 92 0.7286 0.5642 0.7286 0.8536
No log 1.175 94 0.7772 0.5478 0.7772 0.8816
No log 1.2 96 0.8676 0.5446 0.8676 0.9314
No log 1.225 98 1.0223 0.3846 1.0223 1.0111
No log 1.25 100 0.9039 0.5156 0.9039 0.9507
No log 1.275 102 0.7247 0.5771 0.7247 0.8513
No log 1.3 104 0.7475 0.5813 0.7475 0.8646
No log 1.325 106 0.8453 0.5727 0.8453 0.9194
No log 1.35 108 0.9193 0.5072 0.9193 0.9588
No log 1.375 110 0.8084 0.5821 0.8084 0.8991
No log 1.4 112 0.7540 0.6361 0.7540 0.8684
No log 1.425 114 0.8045 0.6074 0.8045 0.8970
No log 1.45 116 0.7949 0.5989 0.7949 0.8916
No log 1.475 118 0.7204 0.6037 0.7204 0.8487
No log 1.5 120 0.7646 0.5836 0.7646 0.8744
No log 1.525 122 1.0924 0.4908 1.0924 1.0452
No log 1.55 124 1.2331 0.4149 1.2331 1.1105
No log 1.575 126 1.0633 0.4766 1.0633 1.0311
No log 1.6 128 0.9530 0.4766 0.9530 0.9762
No log 1.625 130 1.0587 0.4647 1.0587 1.0289
No log 1.65 132 1.2924 0.4470 1.2924 1.1368
No log 1.675 134 1.1883 0.4830 1.1883 1.0901
No log 1.7 136 0.9907 0.5103 0.9907 0.9954
No log 1.725 138 0.8067 0.5562 0.8067 0.8981
No log 1.75 140 0.7621 0.5735 0.7621 0.8730
No log 1.775 142 0.7679 0.5879 0.7679 0.8763
No log 1.8 144 0.7757 0.5806 0.7757 0.8807
No log 1.825 146 0.7969 0.5750 0.7969 0.8927
No log 1.85 148 0.7617 0.6120 0.7617 0.8727
No log 1.875 150 0.7372 0.6480 0.7372 0.8586
No log 1.9 152 0.7476 0.6333 0.7476 0.8646
No log 1.925 154 0.7635 0.6096 0.7635 0.8738
No log 1.95 156 0.7697 0.6267 0.7697 0.8773
No log 1.975 158 0.7864 0.6287 0.7864 0.8868
No log 2.0 160 0.8766 0.6304 0.8766 0.9363
No log 2.025 162 0.8870 0.6245 0.8870 0.9418
No log 2.05 164 0.8579 0.6249 0.8579 0.9262
No log 2.075 166 0.7933 0.6387 0.7933 0.8907
No log 2.1 168 0.7628 0.6506 0.7628 0.8734
No log 2.125 170 0.7489 0.6391 0.7489 0.8654
No log 2.15 172 0.7383 0.6400 0.7383 0.8593
No log 2.175 174 0.7517 0.5928 0.7517 0.8670
No log 2.2 176 0.7958 0.5597 0.7958 0.8921
No log 2.225 178 0.9252 0.5516 0.9252 0.9619
No log 2.25 180 0.9209 0.5779 0.9209 0.9596
No log 2.275 182 0.8383 0.6140 0.8383 0.9156
No log 2.3 184 0.7569 0.6005 0.7569 0.8700
No log 2.325 186 0.7235 0.5693 0.7235 0.8506
No log 2.35 188 0.6904 0.5854 0.6904 0.8309
No log 2.375 190 0.6846 0.6147 0.6846 0.8274
No log 2.4 192 0.6906 0.5901 0.6906 0.8310
No log 2.425 194 0.7371 0.6223 0.7371 0.8586
No log 2.45 196 0.7359 0.6485 0.7359 0.8579
No log 2.475 198 0.7112 0.6373 0.7112 0.8433
No log 2.5 200 0.7002 0.6109 0.7002 0.8368
No log 2.525 202 0.7331 0.5974 0.7331 0.8562
No log 2.55 204 0.8403 0.5697 0.8403 0.9167
No log 2.575 206 0.9114 0.5723 0.9114 0.9546
No log 2.6 208 0.7800 0.6380 0.7800 0.8832
No log 2.625 210 0.7293 0.6267 0.7293 0.8540
No log 2.65 212 0.7372 0.6172 0.7372 0.8586
No log 2.675 214 0.7497 0.5989 0.7497 0.8659
No log 2.7 216 0.7443 0.5964 0.7443 0.8627
No log 2.725 218 0.7544 0.6027 0.7544 0.8686
No log 2.75 220 0.7999 0.6196 0.7999 0.8944
No log 2.775 222 0.9117 0.5649 0.9117 0.9548
No log 2.8 224 0.9829 0.5274 0.9829 0.9914
No log 2.825 226 1.1068 0.5016 1.1068 1.0520
No log 2.85 228 1.1105 0.5030 1.1105 1.0538
No log 2.875 230 0.9713 0.5770 0.9713 0.9855
No log 2.9 232 0.9465 0.5691 0.9465 0.9729
No log 2.925 234 1.0082 0.5341 1.0082 1.0041
No log 2.95 236 1.1037 0.5171 1.1037 1.0506
No log 2.975 238 0.9547 0.5806 0.9547 0.9771
No log 3.0 240 0.7832 0.6038 0.7832 0.8850
No log 3.025 242 0.7345 0.5911 0.7345 0.8570
No log 3.05 244 0.7213 0.6020 0.7213 0.8493
No log 3.075 246 0.7038 0.6338 0.7038 0.8389
No log 3.1 248 0.7391 0.5739 0.7391 0.8597
No log 3.125 250 0.8631 0.5743 0.8631 0.9290
No log 3.15 252 0.8763 0.5440 0.8763 0.9361
No log 3.175 254 0.7949 0.6075 0.7949 0.8916
No log 3.2 256 0.7243 0.6085 0.7243 0.8511
No log 3.225 258 0.7276 0.6549 0.7276 0.8530
No log 3.25 260 0.8524 0.6030 0.8524 0.9232
No log 3.275 262 0.8895 0.5908 0.8895 0.9431
No log 3.3 264 0.9399 0.5576 0.9399 0.9695
No log 3.325 266 0.8610 0.5983 0.8610 0.9279
No log 3.35 268 0.7495 0.6146 0.7495 0.8657
No log 3.375 270 0.7500 0.6057 0.7500 0.8660
No log 3.4 272 0.8014 0.6200 0.8014 0.8952
No log 3.425 274 0.8743 0.5887 0.8743 0.9350
No log 3.45 276 0.9307 0.5652 0.9307 0.9647
No log 3.475 278 0.8448 0.6003 0.8448 0.9191
No log 3.5 280 0.7857 0.5930 0.7857 0.8864
No log 3.525 282 0.8146 0.5969 0.8146 0.9025
No log 3.55 284 0.9039 0.5487 0.9039 0.9507
No log 3.575 286 0.8990 0.5635 0.8990 0.9482
No log 3.6 288 0.9144 0.5611 0.9144 0.9562
No log 3.625 290 0.8473 0.6032 0.8473 0.9205
No log 3.65 292 0.7752 0.6072 0.7752 0.8805
No log 3.675 294 0.7452 0.5700 0.7452 0.8632
No log 3.7 296 0.7554 0.5544 0.7554 0.8691
No log 3.725 298 0.7480 0.5780 0.7480 0.8649
No log 3.75 300 0.8113 0.5458 0.8113 0.9007
No log 3.775 302 0.9611 0.5595 0.9611 0.9804
No log 3.8 304 0.9870 0.5374 0.9870 0.9935
No log 3.825 306 0.8699 0.6036 0.8699 0.9327
No log 3.85 308 0.7893 0.6343 0.7893 0.8884
No log 3.875 310 0.7933 0.6284 0.7933 0.8907
No log 3.9 312 0.7712 0.6200 0.7712 0.8782
No log 3.925 314 0.8336 0.6279 0.8336 0.9130
No log 3.95 316 0.9446 0.5315 0.9446 0.9719
No log 3.975 318 0.9341 0.5704 0.9341 0.9665
No log 4.0 320 0.8964 0.5622 0.8964 0.9468
No log 4.025 322 0.8253 0.5725 0.8253 0.9085
No log 4.05 324 0.8195 0.5767 0.8195 0.9053
No log 4.075 326 0.8127 0.5846 0.8127 0.9015
No log 4.1 328 0.7753 0.6265 0.7753 0.8805
No log 4.125 330 0.7625 0.6338 0.7625 0.8732
No log 4.15 332 0.7975 0.6355 0.7975 0.8930
No log 4.175 334 0.8379 0.6008 0.8379 0.9154
No log 4.2 336 0.8067 0.5763 0.8067 0.8982
No log 4.225 338 0.7752 0.6284 0.7752 0.8805
No log 4.25 340 0.7568 0.6341 0.7568 0.8699
No log 4.275 342 0.7494 0.6292 0.7494 0.8657
No log 4.3 344 0.7481 0.6583 0.7481 0.8649
No log 4.325 346 0.7444 0.6435 0.7444 0.8628
No log 4.35 348 0.7447 0.6541 0.7447 0.8630
No log 4.375 350 0.7368 0.6228 0.7368 0.8584
No log 4.4 352 0.7123 0.6378 0.7123 0.8440
No log 4.425 354 0.7352 0.6505 0.7352 0.8574
No log 4.45 356 0.7354 0.6565 0.7354 0.8576
No log 4.475 358 0.7270 0.6636 0.7270 0.8527
No log 4.5 360 0.7281 0.6646 0.7281 0.8533
No log 4.525 362 0.7554 0.6617 0.7554 0.8691
No log 4.55 364 0.7155 0.6734 0.7155 0.8459
No log 4.575 366 0.6601 0.6785 0.6601 0.8125
No log 4.6 368 0.6654 0.6809 0.6654 0.8158
No log 4.625 370 0.7206 0.6606 0.7206 0.8489
No log 4.65 372 0.7148 0.6625 0.7148 0.8455
No log 4.675 374 0.6717 0.6774 0.6717 0.8196
No log 4.7 376 0.6527 0.6713 0.6527 0.8079
No log 4.725 378 0.6781 0.6761 0.6781 0.8235
No log 4.75 380 0.7114 0.6645 0.7114 0.8434
No log 4.775 382 0.6924 0.6899 0.6924 0.8321
No log 4.8 384 0.6952 0.6770 0.6952 0.8338
No log 4.825 386 0.7516 0.6715 0.7516 0.8669
No log 4.85 388 0.7880 0.6481 0.7880 0.8877
No log 4.875 390 0.8046 0.6412 0.8046 0.8970
No log 4.9 392 0.7205 0.6719 0.7205 0.8488
No log 4.925 394 0.6702 0.6187 0.6702 0.8187
No log 4.95 396 0.6627 0.6392 0.6627 0.8140
No log 4.975 398 0.6730 0.6757 0.6730 0.8204
No log 5.0 400 0.6900 0.6804 0.6900 0.8307
No log 5.025 402 0.7594 0.6568 0.7594 0.8714
No log 5.05 404 0.8679 0.6398 0.8679 0.9316
No log 5.075 406 0.9857 0.6132 0.9857 0.9928
No log 5.1 408 0.9778 0.6116 0.9778 0.9888
No log 5.125 410 0.8387 0.6290 0.8387 0.9158
No log 5.15 412 0.6730 0.6830 0.6730 0.8204
No log 5.175 414 0.6283 0.7016 0.6283 0.7926
No log 5.2 416 0.6528 0.7101 0.6528 0.8079
No log 5.225 418 0.7680 0.6612 0.7680 0.8763
No log 5.25 420 0.9129 0.6112 0.9129 0.9554
No log 5.275 422 0.9490 0.5979 0.9490 0.9742
No log 5.3 424 1.0104 0.5879 1.0104 1.0052
No log 5.325 426 1.0474 0.5438 1.0474 1.0234
No log 5.35 428 1.0146 0.5363 1.0146 1.0072
No log 5.375 430 0.9064 0.5940 0.9064 0.9521
No log 5.4 432 0.7884 0.5878 0.7884 0.8879
No log 5.425 434 0.7547 0.5897 0.7547 0.8687
No log 5.45 436 0.7453 0.6017 0.7453 0.8633
No log 5.475 438 0.7313 0.6263 0.7313 0.8551
No log 5.5 440 0.7490 0.6443 0.7490 0.8654
No log 5.525 442 0.8162 0.6376 0.8162 0.9034
No log 5.55 444 0.9052 0.5989 0.9052 0.9514
No log 5.575 446 0.9404 0.5975 0.9404 0.9697
No log 5.6 448 1.0740 0.5601 1.0740 1.0363
No log 5.625 450 1.1059 0.5471 1.1059 1.0516
No log 5.65 452 1.0444 0.5445 1.0444 1.0220
No log 5.675 454 1.0209 0.5623 1.0209 1.0104
No log 5.7 456 0.9581 0.5707 0.9581 0.9788
No log 5.725 458 0.9305 0.5834 0.9305 0.9646
No log 5.75 460 0.8714 0.5757 0.8714 0.9335
No log 5.775 462 0.8095 0.6308 0.8095 0.8997
No log 5.8 464 0.8239 0.6039 0.8239 0.9077
No log 5.825 466 0.9033 0.6182 0.9033 0.9504
No log 5.85 468 0.9026 0.6182 0.9026 0.9500
No log 5.875 470 0.8053 0.6353 0.8053 0.8974
No log 5.9 472 0.7029 0.6779 0.7029 0.8384
No log 5.925 474 0.6872 0.7051 0.6872 0.8290
No log 5.95 476 0.6722 0.6937 0.6722 0.8199
No log 5.975 478 0.7085 0.6851 0.7085 0.8417
No log 6.0 480 0.6695 0.6796 0.6695 0.8182
No log 6.025 482 0.6510 0.6563 0.6510 0.8069
No log 6.05 484 0.6506 0.6535 0.6506 0.8066
No log 6.075 486 0.6460 0.6792 0.6460 0.8038
No log 6.1 488 0.6907 0.6973 0.6907 0.8311
No log 6.125 490 0.7871 0.6824 0.7871 0.8872
No log 6.15 492 0.7695 0.6764 0.7695 0.8772
No log 6.175 494 0.7176 0.6998 0.7176 0.8471
No log 6.2 496 0.6806 0.6866 0.6806 0.8250
No log 6.225 498 0.6954 0.6997 0.6954 0.8339
0.3911 6.25 500 0.7710 0.6832 0.7710 0.8781
0.3911 6.275 502 0.8748 0.6395 0.8748 0.9353
0.3911 6.3 504 0.8851 0.6402 0.8851 0.9408
0.3911 6.325 506 0.8208 0.6421 0.8208 0.9060
0.3911 6.35 508 0.7750 0.6744 0.7750 0.8803
0.3911 6.375 510 0.8035 0.6572 0.8035 0.8964

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu118
  • Datasets 2.21.0
  • Tokenizers 0.19.1
Downloads last month
5
Safetensors
Model size
0.1B params
Tensor type
F32
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for MayBashendy/ArabicNewSplits8_usingALLEssays_FineTuningAraBERT_run1_AugV5_k16_task1_organization

Finetuned
(4040)
this model