|
--- |
|
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 |
|
|
