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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 the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0463
- F1: 0.7931
- Roc Auc: 0.8858
- Accuracy: 0.7376
- Coverage Error: 10.3626
- Label Ranking Average Precision Score: 0.7968
## 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|:--------------:|:-------------------------------------:|
| 0.0355 | 1.0 | 9054 | 0.0366 | 0.7550 | 0.8373 | 0.6950 | 14.1539 | 0.7347 |
| 0.0309 | 2.0 | 18108 | 0.0330 | 0.7773 | 0.8553 | 0.7204 | 12.6503 | 0.7647 |
| 0.0234 | 3.0 | 27162 | 0.0330 | 0.7836 | 0.8693 | 0.7293 | 11.6192 | 0.7799 |
| 0.0159 | 4.0 | 36216 | 0.0348 | 0.7830 | 0.8709 | 0.7291 | 11.5355 | 0.7810 |
| 0.0109 | 5.0 | 45270 | 0.0376 | 0.7789 | 0.8786 | 0.7201 | 10.9898 | 0.7812 |
| 0.0075 | 6.0 | 54324 | 0.0397 | 0.7838 | 0.8813 | 0.7241 | 10.7035 | 0.7861 |
| 0.0039 | 7.0 | 63378 | 0.0415 | 0.7888 | 0.8818 | 0.7309 | 10.6559 | 0.7898 |
| 0.0028 | 8.0 | 72432 | 0.0437 | 0.7906 | 0.8838 | 0.7326 | 10.5117 | 0.7924 |
| 0.0016 | 9.0 | 81486 | 0.0453 | 0.7908 | 0.8890 | 0.7308 | 10.0988 | 0.7957 |
| 0.001 | 10.0 | 90540 | 0.0463 | 0.7931 | 0.8858 | 0.7376 | 10.3626 | 0.7968 |
### Framework versions
- Transformers 4.16.2
- Pytorch 1.9.1
- Datasets 1.18.4
- Tokenizers 0.11.6
|