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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
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Model size
124M params
Tensor type
I64
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F32
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Finetuned from

Spaces using nlp-en-es/roberta-base-bne-finetuned-sqac 4

Evaluation results