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g-assismoraes/deberta-semeval25_justEN08_fold4
deberta-semeval25_justEN08_fold4 is a text classification model from g-assismoraes. 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. --
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From the Hugging Face model README
This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Precision Samples | Recall Samples | F1 Samples | Precision Macro | Recall Macro | F1 Macro | Precision Micro | Recall Micro | F1 Micro | Precision Weighted | Recall Weighted | F1 Weighted |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 5 | 9.3895 | 1.0 | 0.0 | 0.0 | 1.0 | 0.3571 | 0.3571 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 8.4727 | 2.0 | 10 | 9.1240 | 1.0 | 0.0 | 0.0 | 1.0 | 0.3571 | 0.3571 | 1.0 | 0.0 | 0.0 | 1.0 | 0.0 | 0.0 |
| 8.4727 | 3.0 | 15 | 8.9313 | 0.475 | 0.475 | 0.475 | 0.9925 | 0.3714 | 0.3663 | 0.475 | 0.2135 | 0.2946 | 0.8879 | 0.2135 | 0.1375 |
| 7.9967 | 4.0 | 20 | 8.7771 | 0.475 | 0.475 | 0.475 | 0.9925 | 0.3714 | 0.3663 | 0.475 | 0.2135 | 0.2946 | 0.8879 | 0.2135 | 0.1375 |
| 7.9967 | 5.0 | 25 | 8.6665 | 0.475 | 0.475 | 0.475 | 0.9925 | 0.3714 | 0.3663 | 0.475 | 0.2135 | 0.2946 | 0.8879 | 0.2135 | 0.1375 |
| 7.6436 | 6.0 | 30 | 8.6018 | 0.475 | 0.475 | 0.475 | 0.9925 | 0.3714 | 0.3663 | 0.475 | 0.2135 | 0.2946 | 0.8879 | 0.2135 | 0.1375 |
| 7.6436 | 7.0 | 35 | 8.5536 | 0.475 | 0.475 | 0.475 | 0.9925 | 0.3714 | 0.3663 | 0.475 | 0.2135 | 0.2946 | 0.8879 | 0.2135 | 0.1375 |
| 7.4488 | 8.0 | 40 | 8.5164 | 0.475 | 0.475 | 0.475 | 0.9925 | 0.3714 | 0.3663 | 0.475 | 0.2135 | 0.2946 | 0.8879 | 0.2135 | 0.1375 |
| 7.4488 | 9.0 | 45 | 8.4947 | 0.475 | 0.475 | 0.475 | 0.9925 | 0.3714 | 0.3663 | 0.475 | 0.2135 | 0.2946 | 0.8879 | 0.2135 | 0.1375 |
| 7.3567 | 10.0 | 50 | 8.4863 | 0.475 | 0.475 | 0.475 | 0.9925 | 0.3714 | 0.3663 | 0.475 | 0.2135 | 0.2946 | 0.8879 | 0.2135 | 0.1375 |