distilbert-base-uncased_rotten_tomatoes

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

  • Loss: 0.9770
  • Accuracy: 0.8405

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: 16
  • eval_batch_size: 16
  • 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
0.4274 1.0 534 0.3831 0.8452
0.2256 2.0 1068 0.5080 0.8405
0.1048 3.0 1602 0.7442 0.8368
0.0503 4.0 2136 0.8985 0.8443
0.0187 5.0 2670 0.9770 0.8405

Framework versions

  • Transformers 4.24.0
  • Pytorch 1.12.1+cu113
  • Datasets 2.7.0
  • Tokenizers 0.13.2
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Dataset used to train xianzhew/distilbert-base-uncased_rotten_tomatoes

Evaluation results