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lct-rug-2022/edos-2023-baseline-microsoft-deberta-v3-base-label_vector
edos-2023-baseline-microsoft-deberta-v3-base-label_vector is a text classification model from lct-rug-2022. 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 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 | F1 |
|---|---|---|---|---|
| 2.1209 | 1.18 | 100 | 1.9990 | 0.0801 |
| 1.7997 | 2.35 | 200 | 1.7293 | 0.1349 |
| 1.5749 | 3.53 | 300 | 1.6080 | 0.2431 |
| 1.3674 | 4.71 | 400 | 1.5411 | 0.2793 |
| 1.2214 | 5.88 | 500 | 1.5285 | 0.2980 |
| 1.0752 | 7.06 | 600 | 1.5165 | 0.3054 |
| 0.9899 | 8.24 | 700 | 1.5210 | 0.3186 |
| 0.8733 | 9.41 | 800 | 1.5385 | 0.3134 |
| 0.8578 | 10.59 | 900 | 1.5524 | 0.3162 |