|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: FacebookAI/xlm-roberta-large |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- precision |
|
|
- recall |
|
|
- f1 |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: breast-cancer-biomedical-ner-sp |
|
|
results: [] |
|
|
language: |
|
|
- es |
|
|
pipeline_tag: token-classification |
|
|
--- |
|
|
|
|
|
<!-- 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. --> |
|
|
|
|
|
# breast-cancer-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 cancer dataset in spanish: [anvorja/breast_cancer_es_dataset](https://huggingface.co/datasets/anvorja/breast_cancer_es_dataset). |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.0178 |
|
|
- Precision: 0.9793 |
|
|
- Recall: 0.9867 |
|
|
- F1: 0.9830 |
|
|
- Accuracy: 0.9948 |
|
|
|
|
|
|
|
|
### 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_with_restarts |
|
|
- lr_scheduler_warmup_ratio: 0.2 |
|
|
- num_epochs: 20 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
|
| 2.1649 | 1.0 | 112 | 1.9231 | 0.0099 | 0.0051 | 0.0067 | 0.6051 | |
|
|
| 0.8237 | 2.0 | 224 | 0.6627 | 0.5850 | 0.5669 | 0.5758 | 0.8329 | |
|
|
| 0.391 | 3.0 | 336 | 0.3065 | 0.7703 | 0.8068 | 0.7882 | 0.9269 | |
|
|
| 0.2341 | 4.0 | 448 | 0.1873 | 0.8221 | 0.875 | 0.8477 | 0.9558 | |
|
|
| 0.1588 | 5.0 | 560 | 0.1463 | 0.8642 | 0.9078 | 0.8855 | 0.9641 | |
|
|
| 0.129 | 6.0 | 672 | 0.1099 | 0.8836 | 0.9205 | 0.9017 | 0.9720 | |
|
|
| 0.1098 | 7.0 | 784 | 0.0902 | 0.9166 | 0.9501 | 0.9330 | 0.9798 | |
|
|
| 0.0764 | 8.0 | 896 | 0.0772 | 0.9167 | 0.9444 | 0.9303 | 0.9822 | |
|
|
| 0.0745 | 9.0 | 1008 | 0.0613 | 0.9358 | 0.9577 | 0.9466 | 0.9856 | |
|
|
| 0.0645 | 10.0 | 1120 | 0.0496 | 0.9564 | 0.9691 | 0.9627 | 0.9891 | |
|
|
| 0.0623 | 11.0 | 1232 | 0.0426 | 0.9595 | 0.9722 | 0.9658 | 0.9898 | |
|
|
| 0.0489 | 12.0 | 1344 | 0.0393 | 0.9596 | 0.9741 | 0.9668 | 0.9901 | |
|
|
| 0.0389 | 13.0 | 1456 | 0.0307 | 0.9646 | 0.9798 | 0.9721 | 0.9917 | |
|
|
| 0.0371 | 14.0 | 1568 | 0.0255 | 0.9737 | 0.9798 | 0.9767 | 0.9934 | |
|
|
| 0.0232 | 15.0 | 1680 | 0.0228 | 0.9756 | 0.9830 | 0.9792 | 0.9939 | |
|
|
| 0.0237 | 16.0 | 1792 | 0.0205 | 0.9762 | 0.9842 | 0.9802 | 0.9939 | |
|
|
| 0.0262 | 17.0 | 1904 | 0.0178 | 0.9793 | 0.9867 | 0.9830 | 0.9948 | |
|
|
| 0.0189 | 18.0 | 2016 | 0.0174 | 0.9793 | 0.9855 | 0.9824 | 0.9947 | |
|
|
| 0.0188 | 19.0 | 2128 | 0.0170 | 0.9774 | 0.9848 | 0.9811 | 0.9946 | |
|
|
| 0.0214 | 20.0 | 2240 | 0.0172 | 0.9781 | 0.9855 | 0.9818 | 0.9945 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.51.3 |
|
|
- Pytorch 2.6.0+cu124 |
|
|
- Datasets 3.6.0 |
|
|
- Tokenizers 0.21.1 |
|
|
|
|
|
## License |
|
|
|
|
|
CC-BY-SA-4.0 |
|
|
|
|
|
|
