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distilbert-base-uncased-wandb-week-3-complaints-classifier-1500

This model is a fine-tuned version of distilbert-base-uncased on the consumer-finance-complaints dataset.

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1500
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.11.0+cu102
  • Datasets 2.3.2
  • Tokenizers 0.12.1
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Dataset used to train Kayvane/distilbert-base-uncased-wandb-week-3-complaints-classifier-1500