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distilbert-base-uncased-finetuned-emotion

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

  • Loss: 0.2185
  • Accuracy: 0.928
  • F1: 0.9281

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: 2e-05
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.8374 1.0 250 0.3188 0.9045 0.9012
0.254 2.0 500 0.2185 0.928 0.9281

Framework versions

  • Transformers 4.22.2
  • Pytorch 1.12.1+cpu
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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Dataset used to train Lwhieldon/distilbert-base-uncased-finetuned-emotion

Evaluation results