README.md

metadata

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 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