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bert-base-uncased_emotion_ft

This model was trained from scratch on the emotion dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1553
  • Accuracy: 0.9355
  • F1: 0.9357
  • Precision: 0.9108

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: 4

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision
0.82 1.0 250 0.2697 0.9105 0.9112 0.8759
0.2002 2.0 500 0.1846 0.9325 0.9331 0.9059
0.1237 3.0 750 0.1562 0.9365 0.9368 0.9120
0.097 4.0 1000 0.1553 0.9355 0.9357 0.9108

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.4
  • Tokenizers 0.13.3
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Dataset used to train colingao/bert-base-uncased_emotion_ft

Evaluation results