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genki10/ASAP_FineTuningBERT_AugV6_k1_task1_organization_k1_k1_fold4
ASAP_FineTuningBERT_AugV6_k1_task1_organization_k1_k1_fold4 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 | 1.0 | 2 | 12.8890 | -0.0011 | 12.8890 | 3.5901 |
| No log | 2.0 | 4 | 9.9472 | 0.0018 | 9.9472 | 3.1539 |
| No log | 3.0 | 6 | 8.7139 | 0.0 | 8.7139 | 2.9519 |
| No log | 4.0 | 8 | 7.3810 | 0.0 | 7.3810 | 2.7168 |
| No log | 5.0 | 10 | 5.7643 | 0.0065 | 5.7643 | 2.4009 |
| No log | 6.0 | 12 | 4.3938 | 0.0079 | 4.3938 | 2.0961 |
| No log | 7.0 | 14 | 3.2416 | 0.0040 | 3.2416 | 1.8004 |
| No log | 8.0 | 16 | 2.4935 | 0.0230 | 2.4935 | 1.5791 |
| No log | 9.0 | 18 | 2.0364 | 0.0747 | 2.0364 | 1.4270 |
| No log | 10.0 | 20 | 1.6875 | 0.0518 | 1.6875 | 1.2990 |
| No log | 11.0 | 22 | 1.4080 | 0.0533 | 1.4080 | 1.1866 |
| No log | 12.0 | 24 | 1.0618 | 0.0316 | 1.0618 | 1.0304 |
| No log | 13.0 | 26 | 0.9812 | 0.0316 | 0.9812 | 0.9906 |
| No log | 14.0 | 28 | 1.0974 | 0.0316 | 1.0974 | 1.0475 |
| No log | 15.0 | 30 | 1.3938 | 0.0850 | 1.3938 | 1.1806 |
| No log | 16.0 | 32 | 1.2501 | 0.1064 | 1.2501 | 1.1181 |
| No log | 17.0 | 34 | 1.0616 | 0.1777 | 1.0616 | 1.0303 |
| No log | 18.0 | 36 | 1.1793 | 0.2216 | 1.1793 | 1.0859 |
| No log | 19.0 | 38 | 1.0778 | 0.3308 | 1.0778 | 1.0382 |
| No log | 20.0 | 40 | 1.1801 | 0.3898 | 1.1801 | 1.0863 |
| No log | 21.0 | 42 | 1.9151 | 0.2538 | 1.9151 | 1.3839 |
| No log | 22.0 | 44 | 1.5416 | 0.3298 | 1.5416 | 1.2416 |
| No log | 23.0 | 46 | 1.4745 | 0.3378 | 1.4745 | 1.2143 |
| No log | 24.0 | 48 | 0.8477 | 0.4446 | 0.8477 | 0.9207 |
| No log | 25.0 | 50 | 0.7671 | 0.4725 | 0.7671 | 0.8758 |
| No log | 26.0 | 52 | 1.3353 | 0.3428 | 1.3353 | 1.1556 |
| No log | 27.0 | 54 | 1.4812 | 0.3132 | 1.4812 | 1.2170 |
| No log | 28.0 | 56 | 0.9152 | 0.4389 | 0.9152 | 0.9567 |
| No log | 29.0 | 58 | 0.7235 | 0.5094 | 0.7235 | 0.8506 |
| No log | 30.0 | 60 | 0.7219 | 0.4935 | 0.7219 | 0.8497 |
| No log | 31.0 | 62 | 1.1388 | 0.3762 | 1.1388 | 1.0672 |
| No log | 32.0 | 64 | 1.0083 | 0.4257 | 1.0083 | 1.0041 |
| No log | 33.0 | 66 | 0.7755 | 0.4911 | 0.7755 | 0.8806 |
| No log | 34.0 | 68 | 0.8231 | 0.4779 | 0.8231 | 0.9073 |
| No log | 35.0 | 70 | 0.9423 | 0.4742 | 0.9423 | 0.9707 |
| No log | 36.0 | 72 | 0.9206 | 0.4719 | 0.9206 | 0.9595 |
| No log | 37.0 | 74 | 0.8846 | 0.4651 | 0.8846 | 0.9405 |
| No log | 38.0 | 76 | 0.9781 | 0.4241 | 0.9781 | 0.9890 |
| No log | 39.0 | 78 | 1.1599 | 0.4229 | 1.1599 | 1.0770 |
| No log | 40.0 | 80 | 0.9518 | 0.4437 | 0.9518 | 0.9756 |
| No log | 41.0 | 82 | 0.8629 | 0.4652 | 0.8629 | 0.9289 |
| No log | 42.0 | 84 | 0.8836 | 0.4625 | 0.8836 | 0.9400 |
| No log | 43.0 | 86 | 1.1953 | 0.4134 | 1.1953 | 1.0933 |
| No log | 44.0 | 88 | 0.9837 | 0.4446 | 0.9837 | 0.9918 |
| No log | 45.0 | 90 | 0.9300 | 0.4697 | 0.9300 | 0.9643 |
| No log | 46.0 | 92 | 1.0302 | 0.4278 | 1.0302 | 1.0150 |
| No log | 47.0 | 94 | 1.1905 | 0.4037 | 1.1905 | 1.0911 |
| No log | 48.0 | 96 | 0.9827 | 0.4597 | 0.9827 | 0.9913 |
| No log | 49.0 | 98 | 0.8680 | 0.4949 | 0.8680 | 0.9316 |