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Librarian Bot: Add base_model information to model (#2)
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---
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
---
<!-- 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-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