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mdeberta-v3-base-livingner3
IIC/mdeberta-v3-base-livingner3
mdeberta-v3-base-livingner3 is a text classification model from IIC. 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.
This model is a finetuned version of mdeberta-v3-base for the livingner3 dataset used in a benchmark in the paper TODO. The model has a F1 of 0.153
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From the Hugging Face model README
mdeberta-v3-base-livingner3
This model is a finetuned version of mdeberta-v3-base for the livingner3 dataset used in a benchmark in the paper TODO. The model has a F1 of 0.153
Please refer to the original publication for more information TODO LINK
Parameters used
| parameter | Value |
|---|---|
| batch size | 64 |
| learning rate | 1e-05 |
| classifier dropout | 0.2 |
| warmup ratio | 0 |
| warmup steps | 0 |
| weight decay | 0 |
| optimizer | AdamW |
| epochs | 10 |
| early stopping patience | 3 |
BibTeX entry and citation info
TODO
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Languages
- es
- Created
- Jun 26, 2023
- Updated
- Nov 25, 2024