|
--- |
|
base_model: aubmindlab/bert-base-arabertv02 |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: arabert_cross_relevance_task4_fold1 |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# arabert_cross_relevance_task4_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: 0.1626 |
|
- Qwk: 0.0272 |
|
- Mse: 0.1626 |
|
|
|
## 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 | 0.1176 | 2 | 0.6734 | 0.0010 | 0.6734 | |
|
| No log | 0.2353 | 4 | 0.1546 | 0.0127 | 0.1546 | |
|
| No log | 0.3529 | 6 | 0.1344 | 0.0033 | 0.1344 | |
|
| No log | 0.4706 | 8 | 0.2292 | 0.0185 | 0.2292 | |
|
| No log | 0.5882 | 10 | 0.2260 | 0.0185 | 0.2260 | |
|
| No log | 0.7059 | 12 | 0.1786 | 0.0273 | 0.1786 | |
|
| No log | 0.8235 | 14 | 0.1782 | 0.0359 | 0.1782 | |
|
| No log | 0.9412 | 16 | 0.1951 | 0.0339 | 0.1951 | |
|
| No log | 1.0588 | 18 | 0.2431 | 0.0300 | 0.2431 | |
|
| No log | 1.1765 | 20 | 0.2607 | 0.0228 | 0.2607 | |
|
| No log | 1.2941 | 22 | 0.1938 | 0.0332 | 0.1938 | |
|
| No log | 1.4118 | 24 | 0.1436 | 0.0511 | 0.1436 | |
|
| No log | 1.5294 | 26 | 0.1294 | 0.0733 | 0.1294 | |
|
| No log | 1.6471 | 28 | 0.1285 | 0.0553 | 0.1285 | |
|
| No log | 1.7647 | 30 | 0.1515 | 0.0273 | 0.1515 | |
|
| No log | 1.8824 | 32 | 0.1764 | 0.0273 | 0.1764 | |
|
| No log | 2.0 | 34 | 0.1880 | 0.0273 | 0.1880 | |
|
| No log | 2.1176 | 36 | 0.1700 | 0.0254 | 0.1700 | |
|
| No log | 2.2353 | 38 | 0.1359 | 0.0273 | 0.1359 | |
|
| No log | 2.3529 | 40 | 0.1300 | 0.0307 | 0.1300 | |
|
| No log | 2.4706 | 42 | 0.1359 | 0.0304 | 0.1359 | |
|
| No log | 2.5882 | 44 | 0.1557 | 0.0319 | 0.1557 | |
|
| No log | 2.7059 | 46 | 0.1602 | 0.0335 | 0.1602 | |
|
| No log | 2.8235 | 48 | 0.1456 | 0.0423 | 0.1456 | |
|
| No log | 2.9412 | 50 | 0.1501 | 0.0339 | 0.1501 | |
|
| No log | 3.0588 | 52 | 0.1611 | 0.0339 | 0.1611 | |
|
| No log | 3.1765 | 54 | 0.1440 | 0.0355 | 0.1440 | |
|
| No log | 3.2941 | 56 | 0.1348 | 0.0441 | 0.1348 | |
|
| No log | 3.4118 | 58 | 0.1332 | 0.0475 | 0.1332 | |
|
| No log | 3.5294 | 60 | 0.1443 | 0.0458 | 0.1443 | |
|
| No log | 3.6471 | 62 | 0.1652 | 0.0389 | 0.1652 | |
|
| No log | 3.7647 | 64 | 0.1647 | 0.0458 | 0.1647 | |
|
| No log | 3.8824 | 66 | 0.1513 | 0.0529 | 0.1513 | |
|
| No log | 4.0 | 68 | 0.1475 | 0.0603 | 0.1475 | |
|
| No log | 4.1176 | 70 | 0.1571 | 0.0510 | 0.1571 | |
|
| No log | 4.2353 | 72 | 0.1593 | 0.0529 | 0.1593 | |
|
| No log | 4.3529 | 74 | 0.1445 | 0.0510 | 0.1445 | |
|
| No log | 4.4706 | 76 | 0.1337 | 0.0675 | 0.1337 | |
|
| No log | 4.5882 | 78 | 0.1314 | 0.0614 | 0.1314 | |
|
| No log | 4.7059 | 80 | 0.1364 | 0.0516 | 0.1364 | |
|
| No log | 4.8235 | 82 | 0.1610 | 0.0406 | 0.1610 | |
|
| No log | 4.9412 | 84 | 0.1875 | 0.0355 | 0.1875 | |
|
| No log | 5.0588 | 86 | 0.1836 | 0.0335 | 0.1836 | |
|
| No log | 5.1765 | 88 | 0.1626 | 0.0389 | 0.1626 | |
|
| No log | 5.2941 | 90 | 0.1440 | 0.0493 | 0.1440 | |
|
| No log | 5.4118 | 92 | 0.1353 | 0.0939 | 0.1353 | |
|
| No log | 5.5294 | 94 | 0.1367 | 0.1075 | 0.1367 | |
|
| No log | 5.6471 | 96 | 0.1399 | 0.0853 | 0.1399 | |
|
| No log | 5.7647 | 98 | 0.1521 | 0.0470 | 0.1521 | |
|
| No log | 5.8824 | 100 | 0.1665 | 0.0352 | 0.1665 | |
|
| No log | 6.0 | 102 | 0.1631 | 0.0372 | 0.1631 | |
|
| No log | 6.1176 | 104 | 0.1511 | 0.0372 | 0.1511 | |
|
| No log | 6.2353 | 106 | 0.1430 | 0.0463 | 0.1430 | |
|
| No log | 6.3529 | 108 | 0.1385 | 0.0708 | 0.1385 | |
|
| No log | 6.4706 | 110 | 0.1378 | 0.1029 | 0.1378 | |
|
| No log | 6.5882 | 112 | 0.1410 | 0.0775 | 0.1410 | |
|
| No log | 6.7059 | 114 | 0.1514 | 0.0515 | 0.1514 | |
|
| No log | 6.8235 | 116 | 0.1742 | 0.0351 | 0.1742 | |
|
| No log | 6.9412 | 118 | 0.1831 | 0.0317 | 0.1831 | |
|
| No log | 7.0588 | 120 | 0.1684 | 0.0347 | 0.1684 | |
|
| No log | 7.1765 | 122 | 0.1531 | 0.0652 | 0.1531 | |
|
| No log | 7.2941 | 124 | 0.1443 | 0.0679 | 0.1443 | |
|
| No log | 7.4118 | 126 | 0.1417 | 0.0749 | 0.1417 | |
|
| No log | 7.5294 | 128 | 0.1432 | 0.0618 | 0.1432 | |
|
| No log | 7.6471 | 130 | 0.1495 | 0.0614 | 0.1495 | |
|
| No log | 7.7647 | 132 | 0.1521 | 0.0495 | 0.1521 | |
|
| No log | 7.8824 | 134 | 0.1575 | 0.0420 | 0.1575 | |
|
| No log | 8.0 | 136 | 0.1621 | 0.0415 | 0.1621 | |
|
| No log | 8.1176 | 138 | 0.1649 | 0.0360 | 0.1649 | |
|
| No log | 8.2353 | 140 | 0.1614 | 0.0397 | 0.1614 | |
|
| No log | 8.3529 | 142 | 0.1589 | 0.0415 | 0.1589 | |
|
| No log | 8.4706 | 144 | 0.1604 | 0.0397 | 0.1604 | |
|
| No log | 8.5882 | 146 | 0.1587 | 0.0420 | 0.1587 | |
|
| No log | 8.7059 | 148 | 0.1531 | 0.0457 | 0.1531 | |
|
| No log | 8.8235 | 150 | 0.1511 | 0.0515 | 0.1511 | |
|
| No log | 8.9412 | 152 | 0.1466 | 0.0614 | 0.1466 | |
|
| No log | 9.0588 | 154 | 0.1458 | 0.0514 | 0.1458 | |
|
| No log | 9.1765 | 156 | 0.1471 | 0.0514 | 0.1471 | |
|
| No log | 9.2941 | 158 | 0.1511 | 0.0495 | 0.1511 | |
|
| No log | 9.4118 | 160 | 0.1570 | 0.0438 | 0.1570 | |
|
| No log | 9.5294 | 162 | 0.1612 | 0.0290 | 0.1612 | |
|
| No log | 9.6471 | 164 | 0.1642 | 0.0272 | 0.1642 | |
|
| No log | 9.7647 | 166 | 0.1639 | 0.0272 | 0.1639 | |
|
| No log | 9.8824 | 168 | 0.1630 | 0.0272 | 0.1630 | |
|
| No log | 10.0 | 170 | 0.1626 | 0.0272 | 0.1626 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.0 |
|
- Pytorch 2.4.0 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
