mrm8488 / roberta-base-bne-finetuned-sqac

huggingface.co
Total runs: 167
24-hour runs: -1
7-day runs: -2
30-day runs: 121
Model's Last Updated: October 05 2021
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Introduction of roberta-base-bne-finetuned-sqac

Model Details of roberta-base-bne-finetuned-sqac

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

Runs of mrm8488 roberta-base-bne-finetuned-sqac on huggingface.co

167
Total runs
-1
24-hour runs
-6
3-day runs
-2
7-day runs
121
30-day runs

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roberta-base-bne-finetuned-sqac install

roberta-base-bne-finetuned-sqac is an open source model from GitHub that offers a free installation service, and any user can find roberta-base-bne-finetuned-sqac on GitHub to install. At the same time, huggingface.co provides the effect of roberta-base-bne-finetuned-sqac install, users can directly use roberta-base-bne-finetuned-sqac installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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