xlmroberta-ner-prostata-bs16
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: 0.0350
- F1: 0.9681
- Precision: 0.9667
- Recall: 0.9696
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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall |
|---|---|---|---|---|---|---|
| No log | 1.0 | 195 | 0.1152 | 0.8162 | 0.7970 | 0.8362 |
| No log | 2.0 | 390 | 0.0472 | 0.9115 | 0.8907 | 0.9333 |
| 5.3940 | 3.0 | 585 | 0.0358 | 0.9524 | 0.9527 | 0.9521 |
| 5.3940 | 4.0 | 780 | 0.0374 | 0.9515 | 0.9509 | 0.9521 |
| 5.3940 | 5.0 | 975 | 0.0262 | 0.9664 | 0.9645 | 0.9683 |
| 0.5972 | 6.0 | 1170 | 0.0246 | 0.9715 | 0.9721 | 0.9709 |
| 0.5972 | 7.0 | 1365 | 0.0314 | 0.9753 | 0.9779 | 0.9728 |
| 0.3538 | 8.0 | 1560 | 0.0259 | 0.9783 | 0.9799 | 0.9767 |
| 0.3538 | 9.0 | 1755 | 0.0326 | 0.9789 | 0.9811 | 0.9767 |
| 0.3538 | 10.0 | 1950 | 0.0272 | 0.9799 | 0.9806 | 0.9793 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2