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multiclinner-enigma-es-disease-xlm-roberta-large
SU-FMI-AI/multiclinner-enigma-es-disease-xlm-roberta-large
multiclinner-enigma-es-disease-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 27, 2026
- Updated
- Mar 29, 2026
- SHA
- b4aae159
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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_disease
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: 0.0016
- Precision: 0.9939
- Recall: 0.9967
- F1: 0.9953
- Accuracy: 0.9995
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 |
|---|---|---|---|---|---|---|---|
| 0.1394 | 1.0 | 739 | 0.0602 | 0.8513 | 0.8926 | 0.8715 | 0.9786 |
| 0.0723 | 2.0 | 1478 | 0.0329 | 0.9162 | 0.9230 | 0.9196 | 0.9874 |
| 0.0414 | 3.0 | 2217 | 0.0245 | 0.9201 | 0.9616 | 0.9404 | 0.9911 |
| 0.0338 | 4.0 | 2956 | 0.0144 | 0.9671 | 0.9606 | 0.9638 | 0.9948 |
| 0.0202 | 5.0 | 3695 | 0.0095 | 0.9740 | 0.9815 | 0.9777 | 0.9970 |
| 0.0159 | 6.0 | 4434 | 0.0066 | 0.9794 | 0.9865 | 0.9830 | 0.9978 |
| 0.0098 | 7.0 | 5173 | 0.0045 | 0.9826 | 0.9931 | 0.9878 | 0.9986 |
| 0.0084 | 8.0 | 5912 | 0.0031 | 0.9911 | 0.9943 | 0.9927 | 0.9990 |
| 0.0056 | 9.0 | 6651 | 0.0018 | 0.9945 | 0.9961 | 0.9953 | 0.9995 |
| 0.0044 | 10.0 | 7390 | 0.0016 | 0.9939 | 0.9967 | 0.9953 | 0.9995 |
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 27, 2026
- Updated
- Mar 29, 2026