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mdeberta-v3-base-meddocan
IIC/mdeberta-v3-base-meddocan
mdeberta-v3-base-meddocan 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 meddocan dataset used in a benchmark in the paper TODO. The model has a F1 of 0.974
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From the Hugging Face model README
mdeberta-v3-base-meddocan
This model is a finetuned version of mdeberta-v3-base for the meddocan dataset used in a benchmark in the paper TODO. The model has a F1 of 0.974
Please refer to the original publication for more information TODO LINK
Parameters used
| parameter | Value |
|---|---|
| batch size | 16 |
| learning rate | 4e-05 |
| classifier dropout | 0.2 |
| warmup ratio | 0 |
| warmup steps | 0 |
| weight decay | 0 |
| optimizer | AdamW |
| epochs | 10 |
| early stopping patience | 3 |
BibTeX entry and citation info
TODO
- Task
- Token Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Languages
- es
- Created
- Jun 21, 2023
- Updated
- Jul 27, 2023