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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: 0.0152
- F1: 0.9462
- Roc Auc: 0.9698
- Accuracy: 0.9297
- Coverage Error: 3.6573
- Label Ranking Average Precision Score: 0.9451
## Intended uses & limitations
This model only predicts the first two digits of the CPV codes.
## 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 |
|:-------------:|:-----:|:------:|:---------------:|:------:|:-------:|:--------:|:--------------:|:-------------------------------------:|
| 0.0287 | 1.0 | 20385 | 0.0270 | 0.8235 | 0.8815 | 0.7695 | 10.4603 | 0.8167 |
| 0.0172 | 2.0 | 40770 | 0.0199 | 0.8773 | 0.9210 | 0.8306 | 7.5943 | 0.8768 |
| 0.01 | 3.0 | 61155 | 0.0168 | 0.9028 | 0.9364 | 0.8639 | 6.2111 | 0.9045 |
| 0.0062 | 4.0 | 81540 | 0.0152 | 0.9207 | 0.9520 | 0.8871 | 5.1353 | 0.9213 |
| 0.0037 | 5.0 | 101925 | 0.0151 | 0.9300 | 0.9569 | 0.9026 | 4.7350 | 0.9295 |
| 0.0021 | 6.0 | 122310 | 0.0147 | 0.9365 | 0.9625 | 0.9123 | 4.2946 | 0.9355 |
| 0.0013 | 7.0 | 142695 | 0.0148 | 0.9396 | 0.9659 | 0.9184 | 3.9912 | 0.9387 |
| 0.001 | 8.0 | 163080 | 0.0150 | 0.9426 | 0.9680 | 0.9243 | 3.8065 | 0.9422 |
| 0.0006 | 9.0 | 183465 | 0.0152 | 0.9445 | 0.9693 | 0.9274 | 3.7064 | 0.9438 |
| 0.0003 | 10.0 | 203850 | 0.0152 | 0.9462 | 0.9698 | 0.9297 | 3.6573 | 0.9451 |
### Framework versions
- Transformers 4.16.2
- Pytorch 1.9.1
- Datasets 1.18.4
- Tokenizers 0.11.6
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