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metadata
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: interview_classifier
    results: []

interview_classifier

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5007
  • Accuracy: 0.9815

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: 1e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 1.0 54 2.2376 0.2222
No log 2.0 108 2.1541 0.2130
No log 3.0 162 2.0326 0.5370
No log 4.0 216 1.8738 0.6481
No log 5.0 270 1.7025 0.7037
No log 6.0 324 1.5183 0.8333
No log 7.0 378 1.3588 0.8426
No log 8.0 432 1.2014 0.8796
No log 9.0 486 1.0698 0.9074
1.8141 10.0 540 0.9494 0.9259
1.8141 11.0 594 0.8497 0.9352
1.8141 12.0 648 0.7666 0.9352
1.8141 13.0 702 0.6960 0.9444
1.8141 14.0 756 0.6407 0.9537
1.8141 15.0 810 0.5952 0.9537
1.8141 16.0 864 0.5619 0.9630
1.8141 17.0 918 0.5335 0.9630
1.8141 18.0 972 0.5159 0.9722
0.7883 19.0 1026 0.5044 0.9815
0.7883 20.0 1080 0.5007 0.9815

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1