--- language: es license: apache-2.0 tags: - generated_from_trainer datasets: - sqac metrics: - f1 base_model: BSC-TeMU/roberta-base-bne model-index: - name: roberta-base-bne-finetuned-sqac results: - task: type: Question-Answering name: Question Answering dataset: name: sqac type: sqac metrics: - type: f1 value: 0.7903 name: f1 --- # roberta-base-bne-finetuned-sqac This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on the sqac dataset. It achieves the following results on the evaluation set: - Loss: 1.2111 ## 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: 16 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.9971 | 1.0 | 1196 | 0.8646 | | 0.482 | 2.0 | 2392 | 0.9334 | | 0.1652 | 3.0 | 3588 | 1.2111 | ### Framework versions - Transformers 4.11.2 - Pytorch 1.9.0+cu111 - Datasets 1.12.1 - Tokenizers 0.10.3