Arnold145 / distilbert-base-uncased-distilled-clinc

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Total runs: 9
24-hour runs: 0
7-day runs: 0
30-day runs: 1
Model's Last Updated: November 27 2025
text-classification

Introduction of distilbert-base-uncased-distilled-clinc

Model Details of distilbert-base-uncased-distilled-clinc

distilbert-base-uncased-distilled-clinc

This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4531
  • Accuracy: 0.9332
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: 48
  • eval_batch_size: 48
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 6
Training results
Training Loss Epoch Step Validation Loss Accuracy
2.8505 1.0 318 2.1560 0.7242
1.7266 2.0 636 1.2299 0.8561
1.0239 3.0 954 0.7710 0.9003
0.6707 4.0 1272 0.5683 0.9194
0.505 5.0 1590 0.4793 0.93
0.4361 6.0 1908 0.4531 0.9332
Framework versions
  • Transformers 4.52.4
  • Pytorch 2.6.0+cu126
  • Datasets 3.6.0
  • Tokenizers 0.21.1

Runs of Arnold145 distilbert-base-uncased-distilled-clinc on huggingface.co

9
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distilbert-base-uncased-distilled-clinc install

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

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