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XLM_R_Galen-meddocan
IIC/XLM_R_Galen-meddocan
XLM_R_Galen-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 XLMRGalen for the meddocan dataset used in a benchmark in the paper TODO. The model has a F1 of 0.947
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From the Hugging Face model README
XLM_R_Galen-meddocan
This model is a finetuned version of XLM_R_Galen for the meddocan dataset used in a benchmark in the paper TODO. The model has a F1 of 0.947
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
- xlm-roberta
- License
- mit
- Languages
- es
- Created
- Jun 21, 2023
- Updated
- Mar 24, 2025