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multiclinner-enigma-es-symptom-xlm-roberta-large
SU-FMI-AI/multiclinner-enigma-es-symptom-xlm-roberta-large
multiclinner-enigma-es-symptom-xlm-roberta-large is a token classification model from SU-FMI-AI. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- xlm-roberta
- Access
- Public
- Created
- Mar 29, 2026
- Updated
- Mar 30, 2026
- SHA
- 046614fe
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Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
xlm-roberta-large-spanish-clinical_es_symptom
This model is a fine-tuned version of llange/xlm-roberta-large-spanish-clinical on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0057
- Precision: 0.9855
- Recall: 0.9919
- F1: 0.9887
- Accuracy: 0.9982
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1862 | 1.0 | 739 | 0.0924 | 0.8357 | 0.8449 | 0.8403 | 0.9630 |
| 0.1146 | 2.0 | 1478 | 0.0670 | 0.8700 | 0.9071 | 0.8882 | 0.9747 |
| 0.0763 | 3.0 | 2217 | 0.0433 | 0.9198 | 0.9273 | 0.9235 | 0.9847 |
| 0.0639 | 4.0 | 2956 | 0.0293 | 0.9389 | 0.9565 | 0.9476 | 0.9901 |
| 0.0414 | 5.0 | 3695 | 0.0198 | 0.9583 | 0.9685 | 0.9634 | 0.9931 |
| 0.0341 | 6.0 | 4434 | 0.0162 | 0.9619 | 0.9774 | 0.9696 | 0.9947 |
| 0.0231 | 7.0 | 5173 | 0.0106 | 0.9781 | 0.9828 | 0.9804 | 0.9969 |
| 0.0203 | 8.0 | 5912 | 0.0078 | 0.9801 | 0.9898 | 0.9849 | 0.9976 |
| 0.0147 | 9.0 | 6651 | 0.0065 | 0.9854 | 0.9903 | 0.9878 | 0.9981 |
| 0.0122 | 10.0 | 7390 | 0.0057 | 0.9855 | 0.9919 | 0.9887 | 0.9982 |
Framework versions
- Transformers 5.4.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.4
- Tokenizers 0.22.2
- Task
- Token Classification
- Library
- transformers
- Type
- xlm-roberta
- Created
- Mar 29, 2026
- Updated
- Mar 30, 2026