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bert-finetuned-rottentomatoes

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

  • Loss: 0.9971
  • Accuracy: 0.8443

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
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.1626 1.0 1067 0.8012 0.8340
0.1048 2.0 2134 0.9137 0.8405
0.0472 3.0 3201 0.9971 0.8443

Framework versions

  • Transformers 4.27.2
  • Pytorch 1.13.1+cu116
  • Datasets 2.10.1
  • Tokenizers 0.13.2
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Safetensors
Model size
108M params
Tensor type
I64
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F32
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Dataset used to train flowfree/bert-finetuned-rottentomatoes

Evaluation results