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Trained model with classification head weights
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metadata
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: defect-classification-distilbert-baseline-20-epochs
    results: []

defect-classification-distilbert-baseline-20-epochs

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

  • Loss: 0.2853
  • Accuracy: 0.8811

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: 512
  • eval_batch_size: 512
  • 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
0.6293 1.0 1062 0.5118 0.7980
0.5347 2.0 2124 0.3975 0.8323
0.4369 3.0 3186 0.3575 0.8526
0.4335 4.0 4248 0.3329 0.8627
0.4325 5.0 5310 0.3173 0.8693
0.4259 6.0 6372 0.3058 0.8763
0.35 7.0 7434 0.2999 0.8784
0.4424 8.0 8496 0.2985 0.8779
0.3915 9.0 9558 0.2987 0.8755
0.4196 10.0 10620 0.2942 0.8783
0.3827 11.0 11682 0.2936 0.8783
0.32 12.0 12744 0.2895 0.8806
0.3664 13.0 13806 0.2971 0.8737
0.3623 14.0 14868 0.2935 0.8760
0.3542 15.0 15930 0.2943 0.8745
0.3391 16.0 16992 0.2881 0.8810
0.3404 17.0 18054 0.2888 0.8783
0.3747 18.0 19116 0.2893 0.8776
0.38 19.0 20178 0.2856 0.8807
0.3123 20.0 21240 0.2853 0.8811

Framework versions

  • Transformers 4.47.0
  • Pytorch 2.5.1+cu124
  • Datasets 3.2.0
  • Tokenizers 0.21.0