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genki10/ASAP_FineTuningBERT_AugV8_k10_task1_organization_fold0
ASAP_FineTuningBERT_AugV8_k10_task1_organization_fold0 is a text classification model from genki10. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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From the Hugging Face model README
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Qwk | Mse | Rmse |
|---|---|---|---|---|---|---|
| No log | 0.25 | 2 | 9.0420 | 0.0 | 9.0420 | 3.0070 |
| No log | 0.5 | 4 | 7.6145 | 0.0 | 7.6145 | 2.7594 |
| No log | 0.75 | 6 | 6.8108 | 0.0 | 6.8108 | 2.6097 |
| No log | 1.0 | 8 | 5.9556 | 0.0209 | 5.9556 | 2.4404 |
| 5.2789 | 1.25 | 10 | 5.0773 | 0.0115 | 5.0773 | 2.2533 |
| 5.2789 | 1.5 | 12 | 4.2390 | 0.0039 | 4.2390 | 2.0589 |
| 5.2789 | 1.75 | 14 | 3.4491 | 0.0 | 3.4491 | 1.8572 |
| 5.2789 | 2.0 | 16 | 2.7368 | 0.0 | 2.7368 | 1.6543 |
| 5.2789 | 2.25 | 18 | 2.0942 | 0.0689 | 2.0942 | 1.4471 |
| 2.4977 | 2.5 | 20 | 1.6274 | 0.0316 | 1.6274 | 1.2757 |
| 2.4977 | 2.75 | 22 | 1.3581 | 0.0316 | 1.3581 | 1.1654 |
| 2.4977 | 3.0 | 24 | 1.1374 | 0.0316 | 1.1374 | 1.0665 |
| 2.4977 | 3.25 | 26 | 1.5673 | 0.0316 | 1.5673 | 1.2519 |
| 2.4977 | 3.5 | 28 | 2.0877 | 0.1765 | 2.0877 | 1.4449 |
| 1.9099 | 3.75 | 30 | 1.4721 | 0.0575 | 1.4721 | 1.2133 |
| 1.9099 | 4.0 | 32 | 0.8284 | 0.2557 | 0.8284 | 0.9101 |
| 1.9099 | 4.25 | 34 | 1.0157 | 0.0567 | 1.0157 | 1.0078 |
| 1.9099 | 4.5 | 36 | 1.7498 | 0.1415 | 1.7498 | 1.3228 |
| 1.9099 | 4.75 | 38 | 1.3940 | 0.0714 | 1.3940 | 1.1807 |
| 1.7092 | 5.0 | 40 | 1.1002 | 0.0779 | 1.1002 | 1.0489 |
| 1.7092 | 5.25 | 42 | 1.1317 | 0.1516 | 1.1318 | 1.0638 |
| 1.7092 | 5.5 | 44 | 1.0288 | 0.2613 | 1.0288 | 1.0143 |
| 1.7092 | 5.75 | 46 | 1.0641 | 0.2996 | 1.0641 | 1.0315 |
| 1.7092 | 6.0 | 48 | 1.0741 | 0.3357 | 1.0741 | 1.0364 |
| 1.319 | 6.25 | 50 | 0.6738 | 0.4565 | 0.6738 | 0.8209 |
| 1.319 | 6.5 | 52 | 0.7498 | 0.4629 | 0.7498 | 0.8659 |
| 1.319 | 6.75 | 54 | 0.6227 | 0.4495 | 0.6227 | 0.7891 |
| 1.319 | 7.0 | 56 | 0.6315 | 0.4608 | 0.6315 | 0.7947 |
| 1.319 | 7.25 | 58 | 0.5875 | 0.4590 | 0.5875 | 0.7665 |
| 0.7315 | 7.5 | 60 | 0.6049 | 0.4375 | 0.6049 | 0.7777 |
| 0.7315 | 7.75 | 62 | 0.6788 | 0.4699 | 0.6788 | 0.8239 |
| 0.7315 | 8.0 | 64 | 0.6401 | 0.4462 | 0.6401 | 0.8000 |
| 0.7315 | 8.25 | 66 | 0.7471 | 0.4749 | 0.7471 | 0.8643 |
| 0.7315 | 8.5 | 68 | 0.6558 | 0.4991 | 0.6558 | 0.8098 |
| 0.4584 | 8.75 | 70 | 0.6045 | 0.5298 | 0.6045 | 0.7775 |
| 0.4584 | 9.0 | 72 | 1.0280 | 0.4024 | 1.0280 | 1.0139 |
| 0.4584 | 9.25 | 74 | 0.5699 | 0.5009 | 0.5699 | 0.7549 |
| 0.4584 | 9.5 | 76 | 0.5599 | 0.5188 | 0.5599 | 0.7483 |
| 0.4584 | 9.75 | 78 | 0.8521 | 0.4420 | 0.8521 | 0.9231 |
| 0.3911 | 10.0 | 80 | 0.5990 | 0.5326 | 0.5990 | 0.7740 |
| 0.3911 | 10.25 | 82 | 0.6045 | 0.5448 | 0.6045 | 0.7775 |
| 0.3911 | 10.5 | 84 | 0.7424 | 0.5166 | 0.7424 | 0.8616 |
| 0.3911 | 10.75 | 86 | 0.6233 | 0.5375 | 0.6233 | 0.7895 |
| 0.3911 | 11.0 | 88 | 0.6030 | 0.5613 | 0.6030 | 0.7765 |
| 0.2934 | 11.25 | 90 | 0.7415 | 0.5094 | 0.7415 | 0.8611 |
| 0.2934 | 11.5 | 92 | 0.6086 | 0.5581 | 0.6086 | 0.7801 |
| 0.2934 | 11.75 | 94 | 0.5970 | 0.5577 | 0.5970 | 0.7727 |
| 0.2934 | 12.0 | 96 | 0.7225 | 0.5170 | 0.7225 | 0.8500 |
| 0.2934 | 12.25 | 98 | 0.6135 | 0.5511 | 0.6135 | 0.7833 |
| 0.2689 | 12.5 | 100 | 0.5936 | 0.5480 | 0.5936 | 0.7705 |
| 0.2689 | 12.75 | 102 | 0.7169 | 0.5183 | 0.7169 | 0.8467 |
| 0.2689 | 13.0 | 104 | 0.5848 | 0.5551 | 0.5848 | 0.7647 |
| 0.2689 | 13.25 | 106 | 0.6048 | 0.5350 | 0.6048 | 0.7777 |
| 0.2689 | 13.5 | 108 | 0.5943 | 0.5472 | 0.5943 | 0.7709 |