---
library_name: transformers
license: mit
base_model: FacebookAI/xlm-roberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: panoncology-biomedical-ner-sp
  results: []
language:
- es
pipeline_tag: token-classification
---

# panoncology-biomedical-ner-sp

This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the breast and onco dataset in spanish: [anvorja/onco-clinical-dataset-spanish](https://huggingface.co/datasets/anvorja/onco-clinical-dataset-spanish).
It achieves the following results on the evaluation set:
- Loss: 0.0079
- Precision: 0.9908
- Recall: 0.9921
- F1: 0.9914
- Accuracy: 0.9979

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.2
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 9.9000        | 1.0   | 222  | 1.1292          | 0.4116    | 0.3161 | 0.3576 | 0.7362   |
| 3.0825        | 2.0   | 444  | 0.3111          | 0.7571    | 0.7911 | 0.7737 | 0.9228   |
| 1.5658        | 3.0   | 666  | 0.1636          | 0.8284    | 0.9008 | 0.8631 | 0.9560   |
| 1.1567        | 4.0   | 888  | 0.1138          | 0.8827    | 0.9181 | 0.9000 | 0.9674   |
| 0.8496        | 5.0   | 1110 | 0.0723          | 0.9159    | 0.9325 | 0.9242 | 0.9789   |
| 0.7698        | 6.0   | 1332 | 0.0591          | 0.9236    | 0.9534 | 0.9382 | 0.9830   |
| 0.5803        | 7.0   | 1554 | 0.0495          | 0.9345    | 0.9620 | 0.9481 | 0.9863   |
| 0.5420        | 8.0   | 1776 | 0.0401          | 0.9470    | 0.9613 | 0.9541 | 0.9886   |
| 0.4140        | 9.0   | 1998 | 0.0284          | 0.9587    | 0.9722 | 0.9654 | 0.9907   |
| 0.3513        | 10.0  | 2220 | 0.0288          | 0.9623    | 0.9742 | 0.9682 | 0.9917   |
| 0.3234        | 11.0  | 2442 | 0.0192          | 0.9748    | 0.9769 | 0.9758 | 0.9943   |
| 0.2056        | 12.0  | 2664 | 0.0180          | 0.9761    | 0.9809 | 0.9785 | 0.9950   |
| 0.1464        | 13.0  | 2886 | 0.0139          | 0.9803    | 0.9856 | 0.9829 | 0.9961   |
| 0.1446        | 14.0  | 3108 | 0.0127          | 0.9813    | 0.9876 | 0.9844 | 0.9964   |
| 0.1165        | 15.0  | 3330 | 0.0107          | 0.9847    | 0.9896 | 0.9871 | 0.9970   |
| 0.1628        | 16.0  | 3552 | 0.0093          | 0.9906    | 0.9921 | 0.9913 | 0.9978   |
| 0.1140        | 17.0  | 3774 | 0.0091          | 0.9881    | 0.9903 | 0.9892 | 0.9976   |
| 0.1020        | 18.0  | 3996 | 0.0082          | 0.9906    | 0.9921 | 0.9913 | 0.9979   |
| 0.0974        | 19.0  | 4218 | 0.0079          | 0.9908    | 0.9921 | 0.9914 | 0.9979   |
| 0.1244        | 20.0  | 4440 | 0.0079          | 0.9901    | 0.9916 | 0.9908 | 0.9979   |


### Framework versions

- Transformers 5.9.0
- Pytorch 2.11.0+cu128
- Datasets 4.8.5
- Tokenizers 0.22.2

## License

CC-BY-SA-4.0