bert_model / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
base_model: distilbert-base-uncased
metrics:
  - accuracy
model-index:
  - name: model_results
    results: []

model_results

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: 0.1240
  • Accuracy: 0.9780

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: 0.0002
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.53 1.0 1270 0.3255 0.9425
0.2706 2.0 2540 0.2034 0.9630
0.1923 3.0 3810 0.1934 0.9685
0.1241 4.0 5080 0.1370 0.9783
0.0978 5.0 6350 0.1240 0.9780

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1