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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: roberta-finetuned-CPV_Spanish |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# roberta-finetuned-CPV_Spanish |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0463 |
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- F1: 0.7931 |
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- Roc Auc: 0.8858 |
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- Accuracy: 0.7376 |
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- Coverage Error: 10.3626 |
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- Label Ranking Average Precision Score: 0.7968 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | Coverage Error | Label Ranking Average Precision Score | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|:--------------:|:-------------------------------------:| |
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| 0.0355 | 1.0 | 9054 | 0.0366 | 0.7550 | 0.8373 | 0.6950 | 14.1539 | 0.7347 | |
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| 0.0309 | 2.0 | 18108 | 0.0330 | 0.7773 | 0.8553 | 0.7204 | 12.6503 | 0.7647 | |
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| 0.0234 | 3.0 | 27162 | 0.0330 | 0.7836 | 0.8693 | 0.7293 | 11.6192 | 0.7799 | |
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| 0.0159 | 4.0 | 36216 | 0.0348 | 0.7830 | 0.8709 | 0.7291 | 11.5355 | 0.7810 | |
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| 0.0109 | 5.0 | 45270 | 0.0376 | 0.7789 | 0.8786 | 0.7201 | 10.9898 | 0.7812 | |
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| 0.0075 | 6.0 | 54324 | 0.0397 | 0.7838 | 0.8813 | 0.7241 | 10.7035 | 0.7861 | |
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| 0.0039 | 7.0 | 63378 | 0.0415 | 0.7888 | 0.8818 | 0.7309 | 10.6559 | 0.7898 | |
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| 0.0028 | 8.0 | 72432 | 0.0437 | 0.7906 | 0.8838 | 0.7326 | 10.5117 | 0.7924 | |
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| 0.0016 | 9.0 | 81486 | 0.0453 | 0.7908 | 0.8890 | 0.7308 | 10.0988 | 0.7957 | |
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| 0.001 | 10.0 | 90540 | 0.0463 | 0.7931 | 0.8858 | 0.7376 | 10.3626 | 0.7968 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 1.9.1 |
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- Datasets 1.18.4 |
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- Tokenizers 0.11.6 |
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