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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: roberta-finetuned-CPV_Spanish
results: []
---
<!-- 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. -->
# roberta-finetuned-CPV_Spanish
This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne) on a dataset derived from Spanish Public Procurement documents from 2019. The whole fine-tuning process is available in the following [Kaggle notebook](https://www.kaggle.com/code/marianavasloro/fine-tuned-roberta-for-spanish-cpv-codes).
It achieves the following results on the evaluation set:
- Loss: 0.0465
- F1: 0.7918
- Roc Auc: 0.8860
- Accuracy: 0.7376
- Coverage Error: 10.2744
- Label Ranking Average Precision Score: 0.7973
## Intended uses & limitations
This model only predicts the first two digits of the CPV codes.
## Training and evaluation data
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | Coverage Error | Label Ranking Average Precision Score |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|:--------------:|:-------------------------------------:|
| 0.0354 | 1.0 | 9054 | 0.0362 | 0.7560 | 0.8375 | 0.6963 | 14.0835 | 0.7357 |
| 0.0311 | 2.0 | 18108 | 0.0331 | 0.7756 | 0.8535 | 0.7207 | 12.7880 | 0.7633 |
| 0.0235 | 3.0 | 27162 | 0.0333 | 0.7823 | 0.8705 | 0.7283 | 11.5179 | 0.7811 |
| 0.0157 | 4.0 | 36216 | 0.0348 | 0.7821 | 0.8699 | 0.7274 | 11.5836 | 0.7798 |
| 0.011 | 5.0 | 45270 | 0.0377 | 0.7799 | 0.8787 | 0.7239 | 10.9173 | 0.7841 |
| 0.008 | 6.0 | 54324 | 0.0395 | 0.7854 | 0.8787 | 0.7309 | 10.9042 | 0.7879 |
| 0.0042 | 7.0 | 63378 | 0.0421 | 0.7872 | 0.8823 | 0.7300 | 10.5687 | 0.7903 |
| 0.0025 | 8.0 | 72432 | 0.0439 | 0.7884 | 0.8867 | 0.7305 | 10.2220 | 0.7934 |
| 0.0015 | 9.0 | 81486 | 0.0456 | 0.7889 | 0.8872 | 0.7316 | 10.1781 | 0.7945 |
| 0.001 | 10.0 | 90540 | 0.0465 | 0.7918 | 0.8860 | 0.7376 | 10.2744 | 0.7973 |
### Framework versions
- Transformers 4.16.2
- Pytorch 1.9.1
- Datasets 1.18.4
- Tokenizers 0.11.6
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