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sergiomvazq/DeBERTaV3_model_V2
DeBERTaV3_model_V2 is a text classification model from sergiomvazq. 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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.safetensors568 MB · 96%
From the Hugging Face model README
This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:
More information needed
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More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 50 | 0.3627 | 0.875 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 100 | 0.3804 | 0.875 | 0.0 | 0.0 | 0.0 |
| No log | 3.0 | 150 | 0.3085 | 0.8934 | 0.2564 | 1.0 | 0.1471 |
| No log | 4.0 | 200 | 0.2722 | 0.9007 | 0.4706 | 0.7059 | 0.3529 |
| No log | 5.0 | 250 | 0.2206 | 0.9118 | 0.6129 | 0.6786 | 0.5588 |
| No log | 6.0 | 300 | 0.2140 | 0.9265 | 0.6667 | 0.7692 | 0.5882 |
| No log | 7.0 | 350 | 0.2022 | 0.9265 | 0.6875 | 0.7333 | 0.6471 |
| No log | 8.0 | 400 | 0.1940 | 0.9301 | 0.7077 | 0.7419 | 0.6765 |
| No log | 9.0 | 450 | 0.1711 | 0.9412 | 0.7500 | 0.8 | 0.7059 |
| 0.2198 | 10.0 | 500 | 0.1778 | 0.9338 | 0.7188 | 0.7667 | 0.6765 |