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IIC/BETO_Galen-meddocan
BETO_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 BETOGalen for the meddocan dataset used in a benchmark in the paper TODO. The model has a F1 of 0.682
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From the Hugging Face model README
This model is a finetuned version of BETO_Galen for the meddocan dataset used in a benchmark in the paper TODO. The model has a F1 of 0.682
Please refer to the original publication for more information TODO LINK
| 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 |
TODO