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safepaca/absolute-harmfulness-predictor-redteam
absolute-harmfulness-predictor-redteam is a text classification model from safepaca. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
Downloads · 30 days
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From the Hugging Face model README
This model is a fine-tuned version of microsoft/deberta-v3-large on an unknown 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 | Mse |
|---|---|---|---|---|
| 2.2203 | 0.05 | 50 | 1.8289 | 1.8289 |
| 1.8997 | 0.1 | 100 | 1.7516 | 1.7516 |
| 1.4082 | 0.15 | 150 | 1.3950 | 1.3950 |
| 1.5899 | 0.2 | 200 | 1.9590 | 1.9590 |
| 1.3633 | 0.25 | 250 | 1.3316 | 1.3316 |
| 1.3758 | 0.29 | 300 | 1.2860 | 1.2860 |
| 1.3339 | 0.34 | 350 | 1.2694 | 1.2694 |
| 1.2831 | 0.39 | 400 | 1.3048 | 1.3048 |
| 1.2928 | 0.44 | 450 | 1.2395 | 1.2395 |
| 1.2506 | 0.49 | 500 | 1.4315 | 1.4315 |
| 1.204 | 0.54 | 550 | 1.1596 | 1.1596 |
| 1.1749 | 0.59 | 600 | 1.1995 | 1.1995 |
| 1.134 | 0.64 | 650 | 1.3782 | 1.3782 |
| 1.3097 | 0.69 | 700 | 1.1867 | 1.1867 |
| 1.29 | 0.74 | 750 | 1.2024 | 1.2024 |
| 1.1575 | 0.78 | 800 | 1.1197 | 1.1197 |
| 1.2148 | 0.83 | 850 | 1.1944 | 1.1944 |
| 1.1597 | 0.88 | 900 | 1.2023 | 1.2023 |
| 1.1422 | 0.93 | 950 | 1.1546 | 1.1546 |
| 1.0734 | 0.98 | 1000 | 1.2593 | 1.2593 |