ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k17_task2_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: 0.5685
- Qwk: 0.3966
- Mse: 0.5685
- Rmse: 0.7540
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 | 0.0225 | 2 | 4.1777 | -0.0106 | 4.1777 | 2.0439 |
No log | 0.0449 | 4 | 2.3504 | 0.0552 | 2.3504 | 1.5331 |
No log | 0.0674 | 6 | 1.5512 | 0.0022 | 1.5512 | 1.2455 |
No log | 0.0899 | 8 | 1.2505 | -0.0277 | 1.2505 | 1.1182 |
No log | 0.1124 | 10 | 0.9192 | 0.0733 | 0.9192 | 0.9587 |
No log | 0.1348 | 12 | 0.8052 | 0.2138 | 0.8052 | 0.8973 |
No log | 0.1573 | 14 | 0.9607 | 0.0795 | 0.9607 | 0.9802 |
No log | 0.1798 | 16 | 1.3006 | -0.0007 | 1.3006 | 1.1404 |
No log | 0.2022 | 18 | 1.2681 | 0.0094 | 1.2681 | 1.1261 |
No log | 0.2247 | 20 | 1.0579 | 0.1336 | 1.0579 | 1.0286 |
No log | 0.2472 | 22 | 0.8668 | 0.2403 | 0.8668 | 0.9310 |
No log | 0.2697 | 24 | 0.8337 | 0.2436 | 0.8337 | 0.9131 |
No log | 0.2921 | 26 | 0.8115 | 0.2097 | 0.8115 | 0.9008 |
No log | 0.3146 | 28 | 0.9134 | 0.0794 | 0.9134 | 0.9557 |
No log | 0.3371 | 30 | 1.0275 | 0.0957 | 1.0275 | 1.0137 |
No log | 0.3596 | 32 | 1.0001 | 0.0957 | 1.0001 | 1.0000 |
No log | 0.3820 | 34 | 0.8593 | 0.1248 | 0.8593 | 0.9270 |
No log | 0.4045 | 36 | 0.8161 | 0.1680 | 0.8161 | 0.9034 |
No log | 0.4270 | 38 | 0.7701 | 0.2138 | 0.7701 | 0.8776 |
No log | 0.4494 | 40 | 0.7743 | 0.2399 | 0.7743 | 0.8800 |
No log | 0.4719 | 42 | 0.7820 | 0.2693 | 0.7820 | 0.8843 |
No log | 0.4944 | 44 | 0.7855 | 0.2136 | 0.7855 | 0.8863 |
No log | 0.5169 | 46 | 0.9205 | 0.1955 | 0.9205 | 0.9594 |
No log | 0.5393 | 48 | 1.1515 | 0.0740 | 1.1515 | 1.0731 |
No log | 0.5618 | 50 | 1.3154 | 0.0572 | 1.3154 | 1.1469 |
No log | 0.5843 | 52 | 1.3248 | 0.0924 | 1.3248 | 1.1510 |
No log | 0.6067 | 54 | 1.0073 | 0.1971 | 1.0073 | 1.0036 |
No log | 0.6292 | 56 | 0.9338 | 0.2582 | 0.9338 | 0.9663 |
No log | 0.6517 | 58 | 1.0365 | 0.2350 | 1.0365 | 1.0181 |
No log | 0.6742 | 60 | 1.0710 | 0.2267 | 1.0710 | 1.0349 |
No log | 0.6966 | 62 | 0.9700 | 0.2226 | 0.9700 | 0.9849 |
No log | 0.7191 | 64 | 0.7034 | 0.3475 | 0.7034 | 0.8387 |
No log | 0.7416 | 66 | 0.7036 | 0.4420 | 0.7036 | 0.8388 |
No log | 0.7640 | 68 | 0.9002 | 0.3891 | 0.9002 | 0.9488 |
No log | 0.7865 | 70 | 0.8536 | 0.3469 | 0.8536 | 0.9239 |
No log | 0.8090 | 72 | 0.6304 | 0.4232 | 0.6304 | 0.7940 |
No log | 0.8315 | 74 | 0.6138 | 0.3593 | 0.6138 | 0.7835 |
No log | 0.8539 | 76 | 0.6087 | 0.3593 | 0.6087 | 0.7802 |
No log | 0.8764 | 78 | 0.6557 | 0.3997 | 0.6557 | 0.8097 |
No log | 0.8989 | 80 | 0.8225 | 0.3514 | 0.8225 | 0.9069 |
No log | 0.9213 | 82 | 0.8256 | 0.3234 | 0.8256 | 0.9086 |
No log | 0.9438 | 84 | 0.7580 | 0.3955 | 0.7580 | 0.8706 |
No log | 0.9663 | 86 | 0.7204 | 0.4370 | 0.7204 | 0.8488 |
No log | 0.9888 | 88 | 0.6890 | 0.4661 | 0.6890 | 0.8301 |
No log | 1.0112 | 90 | 0.7028 | 0.4793 | 0.7028 | 0.8383 |
No log | 1.0337 | 92 | 0.7373 | 0.4211 | 0.7373 | 0.8587 |
No log | 1.0562 | 94 | 0.8296 | 0.4672 | 0.8296 | 0.9108 |
No log | 1.0787 | 96 | 0.8450 | 0.4672 | 0.8450 | 0.9192 |
No log | 1.1011 | 98 | 0.7698 | 0.4426 | 0.7698 | 0.8774 |
No log | 1.1236 | 100 | 0.7634 | 0.4514 | 0.7634 | 0.8737 |
No log | 1.1461 | 102 | 0.7214 | 0.4843 | 0.7214 | 0.8493 |
No log | 1.1685 | 104 | 0.7241 | 0.4955 | 0.7241 | 0.8509 |
No log | 1.1910 | 106 | 0.7211 | 0.4293 | 0.7211 | 0.8492 |
No log | 1.2135 | 108 | 0.7309 | 0.3958 | 0.7309 | 0.8549 |
No log | 1.2360 | 110 | 0.7048 | 0.3971 | 0.7048 | 0.8395 |
No log | 1.2584 | 112 | 0.7282 | 0.3604 | 0.7282 | 0.8534 |
No log | 1.2809 | 114 | 0.9335 | 0.3286 | 0.9335 | 0.9662 |
No log | 1.3034 | 116 | 0.9041 | 0.3204 | 0.9041 | 0.9509 |
No log | 1.3258 | 118 | 0.7006 | 0.3731 | 0.7006 | 0.8370 |
No log | 1.3483 | 120 | 0.7893 | 0.4765 | 0.7893 | 0.8885 |
No log | 1.3708 | 122 | 0.7621 | 0.4485 | 0.7621 | 0.8730 |
No log | 1.3933 | 124 | 0.7070 | 0.3545 | 0.7070 | 0.8408 |
No log | 1.4157 | 126 | 0.7348 | 0.3841 | 0.7348 | 0.8572 |
No log | 1.4382 | 128 | 0.7852 | 0.3982 | 0.7852 | 0.8861 |
No log | 1.4607 | 130 | 0.8191 | 0.3786 | 0.8191 | 0.9050 |
No log | 1.4831 | 132 | 0.7028 | 0.4182 | 0.7028 | 0.8383 |
No log | 1.5056 | 134 | 0.7081 | 0.3725 | 0.7081 | 0.8415 |
No log | 1.5281 | 136 | 0.7185 | 0.3701 | 0.7185 | 0.8476 |
No log | 1.5506 | 138 | 0.7359 | 0.3526 | 0.7359 | 0.8578 |
No log | 1.5730 | 140 | 0.9207 | 0.3220 | 0.9207 | 0.9596 |
No log | 1.5955 | 142 | 0.8869 | 0.3212 | 0.8869 | 0.9418 |
No log | 1.6180 | 144 | 0.7754 | 0.3218 | 0.7754 | 0.8806 |
No log | 1.6404 | 146 | 0.7043 | 0.3016 | 0.7043 | 0.8392 |
No log | 1.6629 | 148 | 0.7353 | 0.4109 | 0.7353 | 0.8575 |
No log | 1.6854 | 150 | 0.7089 | 0.4244 | 0.7089 | 0.8420 |
No log | 1.7079 | 152 | 0.6704 | 0.3850 | 0.6704 | 0.8188 |
No log | 1.7303 | 154 | 0.6830 | 0.3733 | 0.6830 | 0.8264 |
No log | 1.7528 | 156 | 0.6470 | 0.3763 | 0.6470 | 0.8044 |
No log | 1.7753 | 158 | 0.6863 | 0.3979 | 0.6863 | 0.8284 |
No log | 1.7978 | 160 | 0.6830 | 0.4077 | 0.6830 | 0.8264 |
No log | 1.8202 | 162 | 0.6625 | 0.4349 | 0.6625 | 0.8139 |
No log | 1.8427 | 164 | 0.6366 | 0.4129 | 0.6366 | 0.7979 |
No log | 1.8652 | 166 | 0.6417 | 0.3783 | 0.6417 | 0.8011 |
No log | 1.8876 | 168 | 0.6270 | 0.3896 | 0.6270 | 0.7919 |
No log | 1.9101 | 170 | 0.6306 | 0.4051 | 0.6306 | 0.7941 |
No log | 1.9326 | 172 | 0.6224 | 0.4105 | 0.6224 | 0.7889 |
No log | 1.9551 | 174 | 0.6664 | 0.3807 | 0.6664 | 0.8163 |
No log | 1.9775 | 176 | 0.7455 | 0.4496 | 0.7455 | 0.8634 |
No log | 2.0 | 178 | 0.7570 | 0.4910 | 0.7570 | 0.8700 |
No log | 2.0225 | 180 | 0.6760 | 0.4122 | 0.6760 | 0.8222 |
No log | 2.0449 | 182 | 0.6365 | 0.3735 | 0.6365 | 0.7978 |
No log | 2.0674 | 184 | 0.6285 | 0.3355 | 0.6285 | 0.7928 |
No log | 2.0899 | 186 | 0.6282 | 0.3658 | 0.6282 | 0.7926 |
No log | 2.1124 | 188 | 0.6314 | 0.3666 | 0.6314 | 0.7946 |
No log | 2.1348 | 190 | 0.6634 | 0.3626 | 0.6634 | 0.8145 |
No log | 2.1573 | 192 | 0.6321 | 0.3414 | 0.6321 | 0.7950 |
No log | 2.1798 | 194 | 0.6353 | 0.3404 | 0.6353 | 0.7971 |
No log | 2.2022 | 196 | 0.6474 | 0.3896 | 0.6474 | 0.8046 |
No log | 2.2247 | 198 | 0.6577 | 0.4058 | 0.6577 | 0.8110 |
No log | 2.2472 | 200 | 0.6602 | 0.4439 | 0.6602 | 0.8125 |
No log | 2.2697 | 202 | 0.6544 | 0.4453 | 0.6544 | 0.8089 |
No log | 2.2921 | 204 | 0.6989 | 0.3969 | 0.6989 | 0.8360 |
No log | 2.3146 | 206 | 0.9037 | 0.4376 | 0.9037 | 0.9506 |
No log | 2.3371 | 208 | 1.1138 | 0.3665 | 1.1138 | 1.0553 |
No log | 2.3596 | 210 | 1.0875 | 0.3526 | 1.0875 | 1.0428 |
No log | 2.3820 | 212 | 0.7774 | 0.4235 | 0.7774 | 0.8817 |
No log | 2.4045 | 214 | 0.6987 | 0.4883 | 0.6987 | 0.8359 |
No log | 2.4270 | 216 | 0.8748 | 0.3955 | 0.8748 | 0.9353 |
No log | 2.4494 | 218 | 0.8398 | 0.4593 | 0.8398 | 0.9164 |
No log | 2.4719 | 220 | 0.6997 | 0.4567 | 0.6997 | 0.8365 |
No log | 2.4944 | 222 | 0.6581 | 0.3995 | 0.6581 | 0.8113 |
No log | 2.5169 | 224 | 0.6652 | 0.4214 | 0.6652 | 0.8156 |
No log | 2.5393 | 226 | 0.7435 | 0.4062 | 0.7435 | 0.8623 |
No log | 2.5618 | 228 | 0.8730 | 0.3952 | 0.8730 | 0.9343 |
No log | 2.5843 | 230 | 0.8795 | 0.3952 | 0.8795 | 0.9378 |
No log | 2.6067 | 232 | 0.7909 | 0.4620 | 0.7909 | 0.8894 |
No log | 2.6292 | 234 | 0.7242 | 0.4183 | 0.7242 | 0.8510 |
No log | 2.6517 | 236 | 0.7166 | 0.4559 | 0.7166 | 0.8465 |
No log | 2.6742 | 238 | 0.7480 | 0.4698 | 0.7480 | 0.8649 |
No log | 2.6966 | 240 | 0.7253 | 0.4148 | 0.7253 | 0.8517 |
No log | 2.7191 | 242 | 0.7027 | 0.4318 | 0.7027 | 0.8383 |
No log | 2.7416 | 244 | 0.6879 | 0.4112 | 0.6879 | 0.8294 |
No log | 2.7640 | 246 | 0.6442 | 0.4438 | 0.6442 | 0.8026 |
No log | 2.7865 | 248 | 0.6630 | 0.4051 | 0.6630 | 0.8143 |
No log | 2.8090 | 250 | 0.6682 | 0.4542 | 0.6682 | 0.8175 |
No log | 2.8315 | 252 | 0.6448 | 0.4188 | 0.6448 | 0.8030 |
No log | 2.8539 | 254 | 0.6681 | 0.4795 | 0.6681 | 0.8174 |
No log | 2.8764 | 256 | 0.6659 | 0.4506 | 0.6659 | 0.8160 |
No log | 2.8989 | 258 | 0.6814 | 0.4585 | 0.6814 | 0.8255 |
No log | 2.9213 | 260 | 0.6682 | 0.4552 | 0.6682 | 0.8175 |
No log | 2.9438 | 262 | 0.6748 | 0.4640 | 0.6748 | 0.8214 |
No log | 2.9663 | 264 | 0.6580 | 0.4401 | 0.6580 | 0.8112 |
No log | 2.9888 | 266 | 0.6560 | 0.4323 | 0.6560 | 0.8100 |
No log | 3.0112 | 268 | 0.6408 | 0.4276 | 0.6408 | 0.8005 |
No log | 3.0337 | 270 | 0.7493 | 0.4708 | 0.7493 | 0.8656 |
No log | 3.0562 | 272 | 0.8084 | 0.4560 | 0.8084 | 0.8991 |
No log | 3.0787 | 274 | 0.7400 | 0.4655 | 0.7400 | 0.8602 |
No log | 3.1011 | 276 | 0.6549 | 0.4679 | 0.6549 | 0.8093 |
No log | 3.1236 | 278 | 0.6435 | 0.5083 | 0.6435 | 0.8022 |
No log | 3.1461 | 280 | 0.6593 | 0.4598 | 0.6593 | 0.8119 |
No log | 3.1685 | 282 | 0.6511 | 0.4735 | 0.6511 | 0.8069 |
No log | 3.1910 | 284 | 0.6770 | 0.4599 | 0.6770 | 0.8228 |
No log | 3.2135 | 286 | 0.7940 | 0.4735 | 0.7940 | 0.8911 |
No log | 3.2360 | 288 | 0.7536 | 0.5045 | 0.7536 | 0.8681 |
No log | 3.2584 | 290 | 0.6486 | 0.4651 | 0.6486 | 0.8054 |
No log | 3.2809 | 292 | 0.5992 | 0.3655 | 0.5992 | 0.7741 |
No log | 3.3034 | 294 | 0.6740 | 0.4366 | 0.6740 | 0.8210 |
No log | 3.3258 | 296 | 0.6913 | 0.4480 | 0.6913 | 0.8314 |
No log | 3.3483 | 298 | 0.5984 | 0.4121 | 0.5984 | 0.7735 |
No log | 3.3708 | 300 | 0.6005 | 0.4499 | 0.6005 | 0.7749 |
No log | 3.3933 | 302 | 0.6310 | 0.4934 | 0.6310 | 0.7943 |
No log | 3.4157 | 304 | 0.5793 | 0.4218 | 0.5793 | 0.7611 |
No log | 3.4382 | 306 | 0.5852 | 0.4318 | 0.5852 | 0.7650 |
No log | 3.4607 | 308 | 0.7511 | 0.4757 | 0.7511 | 0.8666 |
No log | 3.4831 | 310 | 0.8194 | 0.4719 | 0.8194 | 0.9052 |
No log | 3.5056 | 312 | 0.6887 | 0.5234 | 0.6887 | 0.8299 |
No log | 3.5281 | 314 | 0.5883 | 0.4389 | 0.5883 | 0.7670 |
No log | 3.5506 | 316 | 0.5768 | 0.4632 | 0.5768 | 0.7595 |
No log | 3.5730 | 318 | 0.5777 | 0.4443 | 0.5777 | 0.7600 |
No log | 3.5955 | 320 | 0.6107 | 0.4603 | 0.6107 | 0.7815 |
No log | 3.6180 | 322 | 0.7280 | 0.4971 | 0.7280 | 0.8532 |
No log | 3.6404 | 324 | 0.9405 | 0.4133 | 0.9405 | 0.9698 |
No log | 3.6629 | 326 | 1.0120 | 0.4042 | 1.0120 | 1.0060 |
No log | 3.6854 | 328 | 0.9394 | 0.4087 | 0.9394 | 0.9692 |
No log | 3.7079 | 330 | 0.7744 | 0.4929 | 0.7744 | 0.8800 |
No log | 3.7303 | 332 | 0.6056 | 0.4528 | 0.6056 | 0.7782 |
No log | 3.7528 | 334 | 0.5849 | 0.4185 | 0.5849 | 0.7648 |
No log | 3.7753 | 336 | 0.5952 | 0.3987 | 0.5952 | 0.7715 |
No log | 3.7978 | 338 | 0.6140 | 0.3829 | 0.6140 | 0.7836 |
No log | 3.8202 | 340 | 0.6662 | 0.4399 | 0.6662 | 0.8162 |
No log | 3.8427 | 342 | 0.7486 | 0.4413 | 0.7486 | 0.8652 |
No log | 3.8652 | 344 | 0.7270 | 0.4472 | 0.7270 | 0.8526 |
No log | 3.8876 | 346 | 0.6477 | 0.4449 | 0.6477 | 0.8048 |
No log | 3.9101 | 348 | 0.5863 | 0.4076 | 0.5863 | 0.7657 |
No log | 3.9326 | 350 | 0.6385 | 0.3907 | 0.6385 | 0.7991 |
No log | 3.9551 | 352 | 0.6807 | 0.4349 | 0.6807 | 0.8251 |
No log | 3.9775 | 354 | 0.6584 | 0.4232 | 0.6584 | 0.8114 |
No log | 4.0 | 356 | 0.6034 | 0.3887 | 0.6034 | 0.7768 |
No log | 4.0225 | 358 | 0.6177 | 0.4488 | 0.6177 | 0.7859 |
No log | 4.0449 | 360 | 0.6387 | 0.4227 | 0.6387 | 0.7992 |
No log | 4.0674 | 362 | 0.6140 | 0.4415 | 0.6140 | 0.7836 |
No log | 4.0899 | 364 | 0.5948 | 0.3876 | 0.5948 | 0.7712 |
No log | 4.1124 | 366 | 0.5987 | 0.4096 | 0.5987 | 0.7738 |
No log | 4.1348 | 368 | 0.5974 | 0.4096 | 0.5974 | 0.7729 |
No log | 4.1573 | 370 | 0.5975 | 0.3858 | 0.5975 | 0.7730 |
No log | 4.1798 | 372 | 0.5995 | 0.4130 | 0.5995 | 0.7742 |
No log | 4.2022 | 374 | 0.5886 | 0.4039 | 0.5886 | 0.7672 |
No log | 4.2247 | 376 | 0.6064 | 0.3695 | 0.6064 | 0.7787 |
No log | 4.2472 | 378 | 0.6179 | 0.3413 | 0.6179 | 0.7861 |
No log | 4.2697 | 380 | 0.6002 | 0.4155 | 0.6002 | 0.7747 |
No log | 4.2921 | 382 | 0.6031 | 0.3738 | 0.6031 | 0.7766 |
No log | 4.3146 | 384 | 0.6208 | 0.3559 | 0.6208 | 0.7879 |
No log | 4.3371 | 386 | 0.6252 | 0.3774 | 0.6252 | 0.7907 |
No log | 4.3596 | 388 | 0.6357 | 0.3774 | 0.6357 | 0.7973 |
No log | 4.3820 | 390 | 0.6253 | 0.3946 | 0.6253 | 0.7908 |
No log | 4.4045 | 392 | 0.6101 | 0.3517 | 0.6101 | 0.7811 |
No log | 4.4270 | 394 | 0.6018 | 0.3743 | 0.6018 | 0.7757 |
No log | 4.4494 | 396 | 0.6061 | 0.4085 | 0.6061 | 0.7785 |
No log | 4.4719 | 398 | 0.6292 | 0.3997 | 0.6292 | 0.7932 |
No log | 4.4944 | 400 | 0.6133 | 0.4267 | 0.6133 | 0.7831 |
No log | 4.5169 | 402 | 0.6027 | 0.3375 | 0.6027 | 0.7763 |
No log | 4.5393 | 404 | 0.6110 | 0.3337 | 0.6110 | 0.7817 |
No log | 4.5618 | 406 | 0.6080 | 0.3088 | 0.6080 | 0.7798 |
No log | 4.5843 | 408 | 0.6328 | 0.3894 | 0.6328 | 0.7955 |
No log | 4.6067 | 410 | 0.7844 | 0.4323 | 0.7844 | 0.8857 |
No log | 4.6292 | 412 | 0.7978 | 0.4264 | 0.7978 | 0.8932 |
No log | 4.6517 | 414 | 0.6636 | 0.4134 | 0.6636 | 0.8146 |
No log | 4.6742 | 416 | 0.6154 | 0.3925 | 0.6154 | 0.7845 |
No log | 4.6966 | 418 | 0.6881 | 0.4337 | 0.6881 | 0.8295 |
No log | 4.7191 | 420 | 0.6782 | 0.4437 | 0.6782 | 0.8235 |
No log | 4.7416 | 422 | 0.6203 | 0.4329 | 0.6203 | 0.7876 |
No log | 4.7640 | 424 | 0.6162 | 0.3350 | 0.6162 | 0.7850 |
No log | 4.7865 | 426 | 0.6406 | 0.3764 | 0.6406 | 0.8004 |
No log | 4.8090 | 428 | 0.6907 | 0.4297 | 0.6907 | 0.8311 |
No log | 4.8315 | 430 | 0.6799 | 0.4105 | 0.6799 | 0.8246 |
No log | 4.8539 | 432 | 0.6260 | 0.3343 | 0.6260 | 0.7912 |
No log | 4.8764 | 434 | 0.6137 | 0.4002 | 0.6137 | 0.7834 |
No log | 4.8989 | 436 | 0.6154 | 0.3423 | 0.6154 | 0.7845 |
No log | 4.9213 | 438 | 0.6172 | 0.3777 | 0.6172 | 0.7856 |
No log | 4.9438 | 440 | 0.6184 | 0.4127 | 0.6184 | 0.7864 |
No log | 4.9663 | 442 | 0.6563 | 0.3944 | 0.6563 | 0.8101 |
No log | 4.9888 | 444 | 0.7124 | 0.4648 | 0.7124 | 0.8440 |
No log | 5.0112 | 446 | 0.7317 | 0.4471 | 0.7317 | 0.8554 |
No log | 5.0337 | 448 | 0.6890 | 0.4219 | 0.6890 | 0.8301 |
No log | 5.0562 | 450 | 0.6491 | 0.4571 | 0.6491 | 0.8056 |
No log | 5.0787 | 452 | 0.6048 | 0.4156 | 0.6048 | 0.7777 |
No log | 5.1011 | 454 | 0.5929 | 0.4176 | 0.5929 | 0.7700 |
No log | 5.1236 | 456 | 0.5949 | 0.3866 | 0.5949 | 0.7713 |
No log | 5.1461 | 458 | 0.5914 | 0.3557 | 0.5914 | 0.7690 |
No log | 5.1685 | 460 | 0.5794 | 0.4157 | 0.5793 | 0.7612 |
No log | 5.1910 | 462 | 0.5737 | 0.4421 | 0.5737 | 0.7574 |
No log | 5.2135 | 464 | 0.6083 | 0.4236 | 0.6083 | 0.7799 |
No log | 5.2360 | 466 | 0.6065 | 0.4391 | 0.6065 | 0.7788 |
No log | 5.2584 | 468 | 0.5962 | 0.4232 | 0.5962 | 0.7721 |
No log | 5.2809 | 470 | 0.5629 | 0.3972 | 0.5629 | 0.7503 |
No log | 5.3034 | 472 | 0.5657 | 0.4411 | 0.5657 | 0.7522 |
No log | 5.3258 | 474 | 0.5797 | 0.4159 | 0.5797 | 0.7614 |
No log | 5.3483 | 476 | 0.5682 | 0.4275 | 0.5682 | 0.7538 |
No log | 5.3708 | 478 | 0.5613 | 0.4350 | 0.5613 | 0.7492 |
No log | 5.3933 | 480 | 0.5669 | 0.4265 | 0.5669 | 0.7529 |
No log | 5.4157 | 482 | 0.5758 | 0.4436 | 0.5758 | 0.7588 |
No log | 5.4382 | 484 | 0.5842 | 0.4575 | 0.5842 | 0.7643 |
No log | 5.4607 | 486 | 0.5859 | 0.4627 | 0.5859 | 0.7654 |
No log | 5.4831 | 488 | 0.5795 | 0.5046 | 0.5795 | 0.7613 |
No log | 5.5056 | 490 | 0.5795 | 0.5005 | 0.5795 | 0.7612 |
No log | 5.5281 | 492 | 0.5770 | 0.5114 | 0.5770 | 0.7596 |
No log | 5.5506 | 494 | 0.5737 | 0.5161 | 0.5737 | 0.7574 |
No log | 5.5730 | 496 | 0.5777 | 0.5107 | 0.5777 | 0.7601 |
No log | 5.5955 | 498 | 0.5806 | 0.4841 | 0.5806 | 0.7620 |
0.3528 | 5.6180 | 500 | 0.5881 | 0.4621 | 0.5881 | 0.7669 |
0.3528 | 5.6404 | 502 | 0.5719 | 0.4645 | 0.5719 | 0.7563 |
0.3528 | 5.6629 | 504 | 0.5659 | 0.4607 | 0.5659 | 0.7522 |
0.3528 | 5.6854 | 506 | 0.5704 | 0.4622 | 0.5704 | 0.7552 |
0.3528 | 5.7079 | 508 | 0.5635 | 0.4605 | 0.5635 | 0.7507 |
0.3528 | 5.7303 | 510 | 0.6024 | 0.4354 | 0.6024 | 0.7761 |
0.3528 | 5.7528 | 512 | 0.6207 | 0.4356 | 0.6207 | 0.7878 |
0.3528 | 5.7753 | 514 | 0.5766 | 0.4130 | 0.5766 | 0.7593 |
0.3528 | 5.7978 | 516 | 0.5685 | 0.3966 | 0.5685 | 0.7540 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
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Model tree for MayBashendy/ArabicNewSplits8_usingWellWrittenEssays_FineTuningAraBERT_run1_AugV5_k17_task2_organization
Base model
aubmindlab/bert-base-arabertv02