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This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

  • eval_loss: 2.1211
  • eval_accuracy: 0.6112
  • eval_precision: 0.5704
  • eval_recall: 0.5609
  • eval_f1: 0.5599
  • eval_runtime: 16.4845
  • eval_samples_per_second: 26.995
  • eval_steps_per_second: 3.397
  • step: 0

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: 0
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.4.0.dev20240427
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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