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distilbert-swag's Introduction

license base_model tags datasets metrics model-index
apache-2.0
distilbert-base-uncased
generated_from_trainer
swag
accuracy
name results
distilbert-swag

distilbert-swag

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

  • Loss: 0.9079
  • Accuracy: 0.7105

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.9186 1.0 2298 0.7658 0.6950
0.5843 2.0 4597 0.7453 0.7059
0.3548 3.0 6894 0.9079 0.7105

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1
  • Datasets 2.13.1
  • Tokenizers 0.13.3

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