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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: 0.0422
- F1: 0.7739
- Roc Auc: 0.8704
- Accuracy: 0.7201
- Coverage Error: 11.5798
- Label Ranking Average Precision Score: 0.7742
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|:--------------:|:-------------------------------------:|
| 0.0579 | 1.0 | 2039 | 0.0548 | 0.6327 | 0.7485 | 0.5274 | 21.7879 | 0.5591 |
| 0.0411 | 2.0 | 4078 | 0.0441 | 0.7108 | 0.8027 | 0.6386 | 16.8647 | 0.6732 |
| 0.0294 | 3.0 | 6117 | 0.0398 | 0.7437 | 0.8295 | 0.6857 | 14.6700 | 0.7249 |
| 0.0223 | 4.0 | 8156 | 0.0389 | 0.7568 | 0.8453 | 0.7056 | 13.3552 | 0.7494 |
| 0.0163 | 5.0 | 10195 | 0.0397 | 0.7626 | 0.8569 | 0.7097 | 12.5895 | 0.7620 |
| 0.0132 | 6.0 | 12234 | 0.0395 | 0.7686 | 0.8620 | 0.7126 | 12.1926 | 0.7656 |
| 0.0095 | 7.0 | 14273 | 0.0409 | 0.7669 | 0.8694 | 0.7109 | 11.5978 | 0.7700 |
| 0.0066 | 8.0 | 16312 | 0.0415 | 0.7705 | 0.8726 | 0.7107 | 11.4252 | 0.7714 |
| 0.0055 | 9.0 | 18351 | 0.0417 | 0.7720 | 0.8689 | 0.7163 | 11.6987 | 0.7716 |
| 0.0045 | 10.0 | 20390 | 0.0422 | 0.7739 | 0.8704 | 0.7201 | 11.5798 | 0.7742 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.12.1
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