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metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: distilbert-base-uncased-survey-category-0.0.1
    results: []

distilbert-base-uncased-survey-category-0.0.1

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: 0.1004
  • Accuracy: 0.9886

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: 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: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 232 0.1063 0.9773
No log 2.0 464 0.0811 0.9773
0.2551 3.0 696 0.0704 0.9830
0.2551 4.0 928 0.0903 0.9830
0.0423 5.0 1160 0.0949 0.9830
0.0423 6.0 1392 0.0890 0.9886
0.0268 7.0 1624 0.0916 0.9886
0.0268 8.0 1856 0.1001 0.9886
0.0246 9.0 2088 0.0965 0.9886
0.0246 10.0 2320 0.1002 0.9886
0.0156 11.0 2552 0.0785 0.9886
0.0156 12.0 2784 0.0904 0.9886
0.0157 13.0 3016 0.0825 0.9886
0.0157 14.0 3248 0.0999 0.9886
0.0157 15.0 3480 0.1004 0.9886
0.0137 16.0 3712 0.1020 0.9886
0.0137 17.0 3944 0.1010 0.9886
0.0152 18.0 4176 0.1002 0.9886
0.0152 19.0 4408 0.0999 0.9886
0.0114 20.0 4640 0.1004 0.9886

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0