mrm8488 / deberta-v3-small-finetuned-qnli

huggingface.co
Total runs: 46
24-hour runs: 5
7-day runs: -5
30-day runs: 17
Model's Last Updated: December 05 2022
text-classification

Introduction of deberta-v3-small-finetuned-qnli

Model Details of deberta-v3-small-finetuned-qnli

DeBERTa-v3-small fine-tuned on QNLI

This model is a fine-tuned version of microsoft/deberta-v3-small on the GLUE QNLI dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2143
  • Accuracy: 0.9151
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: 3e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5.0
Training results
Training Loss Epoch Step Validation Loss Accuracy
0.2823 1.0 6547 0.2143 0.9151
0.1996 2.0 13094 0.2760 0.9103
0.1327 3.0 19641 0.3293 0.9169
0.0811 4.0 26188 0.4278 0.9193
0.05 5.0 32735 0.5110 0.9176
Framework versions
  • Transformers 4.13.0.dev0
  • Pytorch 1.10.0+cu111
  • Datasets 1.16.1
  • Tokenizers 0.10.3

Runs of mrm8488 deberta-v3-small-finetuned-qnli on huggingface.co

46
Total runs
5
24-hour runs
6
3-day runs
-5
7-day runs
17
30-day runs

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deberta-v3-small-finetuned-qnli install

deberta-v3-small-finetuned-qnli is an open source model from GitHub that offers a free installation service, and any user can find deberta-v3-small-finetuned-qnli on GitHub to install. At the same time, huggingface.co provides the effect of deberta-v3-small-finetuned-qnli install, users can directly use deberta-v3-small-finetuned-qnli installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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