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mdeberta-v3-base-livingner1
IIC/mdeberta-v3-base-livingner1
mdeberta-v3-base-livingner1 is a token classification model from IIC. Use it when you need labels on individual words, such as names. 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 livingner1 dataset used in a benchmark in the paper TODO. The model has a F1 of 0.953
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From the Hugging Face model README
mdeberta-v3-base-livingner1
This model is a finetuned version of mdeberta-v3-base for the livingner1 dataset used in a benchmark in the paper TODO. The model has a F1 of 0.953
Please refer to the original publication for more information TODO LINK
Parameters used
| parameter | Value |
|---|---|
| batch size | 16 |
| learning rate | 4e-05 |
| classifier dropout | 0.1 |
| warmup ratio | 0 |
| warmup steps | 0 |
| weight decay | 0 |
| optimizer | AdamW |
| epochs | 10 |
| early stopping patience | 3 |
BibTeX entry and citation info
TODO
- Task
- Token Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Languages
- es
- Created
- Jun 21, 2023
- Updated
- Mar 24, 2025