transformers pytorch safetensors roberta question-answering generated_from_trainer es dataset:sqac base_model:BSC-LT/roberta-base-bne base_model:finetune:BSC-LT/roberta-base-bne license:apache-2.0 model-index endpoints_compatible region:us
---
base_model: BSC-TeMU/roberta-base-bne
datasets:
- sqac
language: es
license: apache-2.0
metrics:
- f1
tags:
- generated_from_trainer
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
---

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# 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
