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distilbert-base-cased

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

  • Loss: 0.9431
  • Accuracy: 0.7218
  • Micro-precision: 0.7218
  • Micro-recall: 0.7218
  • Micro-f1: 0.7218
  • Macro-precision: 0.3546
  • Macro-recall: 0.2905
  • Macro-f1: 0.2888
  • Weighted-precision: 0.6807
  • Weighted-recall: 0.7218
  • Weighted-f1: 0.6875

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Accuracy Micro-precision Micro-recall Micro-f1 Macro-precision Macro-recall Macro-f1 Weighted-precision Weighted-recall Weighted-f1
0.9397 1.0 2980 0.9431 0.7218 0.7218 0.7218 0.7218 0.3546 0.2905 0.2888 0.6807 0.7218 0.6875

Framework versions

  • Transformers 4.26.0
  • Pytorch 1.13.1+cu116
  • Datasets 2.9.0
  • Tokenizers 0.13.2
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Dataset used to train ahmetayrnc/distilbert-base-cased

Evaluation results