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xlm-roberta-large-ner-prostata-bs32
deefe92/xlm-roberta-large-ner-prostata-bs32
xlm-roberta-large-ner-prostata-bs32 is a token classification model from deefe92. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jul 4, 2026
- Updated
- Jul 4, 2026
- SHA
- 715753a5
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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-ner-prostata-bs32
This model is a fine-tuned version of xlm-roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0236
- Precision: 0.9692
- Recall: 0.9761
- F1: 0.9726
- Accuracy: 0.9956
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 2.0892 | 0.9987 | 97 | 0.1604 | 0.7006 | 0.7799 | 0.7381 | 0.9560 |
| 0.1344 | 1.9974 | 194 | 0.0448 | 0.9053 | 0.9346 | 0.9197 | 0.9887 |
| 0.0614 | 2.9961 | 291 | 0.0352 | 0.9336 | 0.9560 | 0.9447 | 0.9917 |
| 0.0377 | 3.9949 | 388 | 0.0291 | 0.9441 | 0.9735 | 0.9586 | 0.9932 |
| 0.0295 | 4.9936 | 485 | 0.0242 | 0.9635 | 0.9741 | 0.9688 | 0.9950 |
| 0.0187 | 5.9923 | 582 | 0.0236 | 0.9692 | 0.9761 | 0.9726 | 0.9956 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.11.0+cu128
- Datasets 3.0.1
- Tokenizers 0.20.3
- Task
- Token Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jul 4, 2026
- Updated
- Jul 4, 2026