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ArabicNewSplits_FineTuningAraBERT_AugV5_k2_task1_organization_fold0
MayBashendy/ArabicNewSplits_FineTuningAraBERT_AugV5_k2_task1_organization_fold0
ArabicNewSplits_FineTuningAraBERT_AugV5_k2_task1_organization_fold0 is a text classification model from MayBashendy. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Nov 26, 2024
- Updated
- Nov 26, 2024
- SHA
- 38b0367b
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Base models
Model card
From the Hugging Face model README
<!-- 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. -->
ArabicNewSplits_FineTuningAraBERT_AugV5_k2_task1_organization_fold0
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: 1.1558
- Qwk: 0.1649
- Mse: 1.1558
- Rmse: 1.0751
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
|---|---|---|---|---|---|---|
| No log | 0.1667 | 2 | 4.8038 | -0.1032 | 4.8038 | 2.1918 |
| No log | 0.3333 | 4 | 2.7366 | 0.1117 | 2.7366 | 1.6543 |
| No log | 0.5 | 6 | 1.6272 | 0.2382 | 1.6272 | 1.2756 |
| No log | 0.6667 | 8 | 1.4544 | 0.0052 | 1.4544 | 1.2060 |
| No log | 0.8333 | 10 | 1.5379 | -0.0646 | 1.5379 | 1.2401 |
| No log | 1.0 | 12 | 1.3034 | 0.0854 | 1.3034 | 1.1417 |
| No log | 1.1667 | 14 | 1.5292 | -0.1775 | 1.5292 | 1.2366 |
| No log | 1.3333 | 16 | 2.0038 | -0.1510 | 2.0038 | 1.4156 |
| No log | 1.5 | 18 | 1.5015 | -0.0126 | 1.5015 | 1.2254 |
| No log | 1.6667 | 20 | 1.1528 | 0.0592 | 1.1528 | 1.0737 |
| No log | 1.8333 | 22 | 1.1277 | 0.2511 | 1.1277 | 1.0619 |
| No log | 2.0 | 24 | 1.1645 | 0.2299 | 1.1645 | 1.0791 |
| No log | 2.1667 | 26 | 1.2100 | 0.0380 | 1.2100 | 1.1000 |
| No log | 2.3333 | 28 | 1.2221 | -0.0505 | 1.2221 | 1.1055 |
| No log | 2.5 | 30 | 1.2115 | -0.0530 | 1.2115 | 1.1007 |
| No log | 2.6667 | 32 | 1.2196 | -0.0793 | 1.2196 | 1.1043 |
| No log | 2.8333 | 34 | 1.2823 | -0.0344 | 1.2823 | 1.1324 |
| No log | 3.0 | 36 | 1.3146 | -0.0344 | 1.3146 | 1.1466 |
| No log | 3.1667 | 38 | 1.3144 | 0.0 | 1.3144 | 1.1465 |
| No log | 3.3333 | 40 | 1.2691 | 0.0 | 1.2691 | 1.1265 |
| No log | 3.5 | 42 | 1.2288 | 0.0025 | 1.2288 | 1.1085 |
| No log | 3.6667 | 44 | 1.1868 | -0.0057 | 1.1868 | 1.0894 |
| No log | 3.8333 | 46 | 1.1570 | 0.1925 | 1.1570 | 1.0756 |
| No log | 4.0 | 48 | 1.1439 | 0.1461 | 1.1439 | 1.0695 |
| No log | 4.1667 | 50 | 1.1363 | 0.1688 | 1.1363 | 1.0660 |
| No log | 4.3333 | 52 | 1.1338 | 0.1850 | 1.1338 | 1.0648 |
| No log | 4.5 | 54 | 1.1098 | 0.1785 | 1.1098 | 1.0535 |
| No log | 4.6667 | 56 | 1.0828 | 0.2547 | 1.0828 | 1.0406 |
| No log | 4.8333 | 58 | 1.0750 | 0.3345 | 1.0750 | 1.0368 |
| No log | 5.0 | 60 | 1.0503 | 0.3103 | 1.0503 | 1.0248 |
| No log | 5.1667 | 62 | 1.0303 | 0.3071 | 1.0303 | 1.0150 |
| No log | 5.3333 | 64 | 0.9954 | 0.3723 | 0.9954 | 0.9977 |
| No log | 5.5 | 66 | 0.9660 | 0.3586 | 0.9660 | 0.9829 |
| No log | 5.6667 | 68 | 0.9580 | 0.3723 | 0.9580 | 0.9788 |
| No log | 5.8333 | 70 | 0.9715 | 0.3767 | 0.9715 | 0.9857 |
| No log | 6.0 | 72 | 0.9922 | 0.3345 | 0.9922 | 0.9961 |
| No log | 6.1667 | 74 | 0.9956 | 0.2685 | 0.9956 | 0.9978 |
| No log | 6.3333 | 76 | 0.9931 | 0.2789 | 0.9931 | 0.9966 |
| No log | 6.5 | 78 | 0.9841 | 0.3015 | 0.9841 | 0.9920 |
| No log | 6.6667 | 80 | 0.9856 | 0.2685 | 0.9856 | 0.9928 |
| No log | 6.8333 | 82 | 0.9772 | 0.2910 | 0.9772 | 0.9885 |
| No log | 7.0 | 84 | 0.9763 | 0.2910 | 0.9763 | 0.9881 |
| No log | 7.1667 | 86 | 0.9913 | 0.2910 | 0.9913 | 0.9956 |
| No log | 7.3333 | 88 | 1.0312 | 0.2581 | 1.0312 | 1.0155 |
| No log | 7.5 | 90 | 1.0633 | 0.2478 | 1.0633 | 1.0312 |
| No log | 7.6667 | 92 | 1.0997 | 0.1944 | 1.0997 | 1.0487 |
| No log | 7.8333 | 94 | 1.1110 | 0.1944 | 1.1110 | 1.0540 |
| No log | 8.0 | 96 | 1.1220 | 0.1944 | 1.1220 | 1.0592 |
| No log | 8.1667 | 98 | 1.1326 | 0.1944 | 1.1326 | 1.0642 |
| No log | 8.3333 | 100 | 1.1377 | 0.1944 | 1.1377 | 1.0667 |
| No log | 8.5 | 102 | 1.1531 | 0.1944 | 1.1531 | 1.0738 |
| No log | 8.6667 | 104 | 1.1519 | 0.1944 | 1.1519 | 1.0733 |
| No log | 8.8333 | 106 | 1.1555 | 0.2020 | 1.1555 | 1.0749 |
| No log | 9.0 | 108 | 1.1588 | 0.2020 | 1.1588 | 1.0765 |
| No log | 9.1667 | 110 | 1.1550 | 0.1568 | 1.1550 | 1.0747 |
| No log | 9.3333 | 112 | 1.1507 | 0.1649 | 1.1507 | 1.0727 |
| No log | 9.5 | 114 | 1.1511 | 0.1649 | 1.1511 | 1.0729 |
| No log | 9.6667 | 116 | 1.1522 | 0.1649 | 1.1522 | 1.0734 |
| No log | 9.8333 | 118 | 1.1537 | 0.1649 | 1.1537 | 1.0741 |
| No log | 10.0 | 120 | 1.1558 | 0.1649 | 1.1558 | 1.0751 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Nov 26, 2024
- Updated
- Nov 26, 2024