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BERT-tiny-emotion-intent

This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the emotion dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3620
  • Accuracy: 0.91

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: 16
  • eval_batch_size: 16
  • seed: 33
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 50
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.2603 1.0 1000 0.7766 0.7815
0.5919 2.0 2000 0.4117 0.884
0.367 3.0 3000 0.3188 0.8995
0.2848 4.0 4000 0.2928 0.8985
0.2395 5.0 5000 0.2906 0.898
0.2094 6.0 6000 0.2887 0.907
0.1884 7.0 7000 0.2831 0.9065
0.1603 8.0 8000 0.3044 0.9065
0.1519 9.0 9000 0.3124 0.9095
0.1291 10.0 10000 0.3256 0.9065
0.1179 11.0 11000 0.3651 0.9035
0.1091 12.0 12000 0.3620 0.91
0.0977 13.0 13000 0.3992 0.907
0.0914 14.0 14000 0.4285 0.908
0.0876 15.0 15000 0.4268 0.9055

Framework versions

  • Transformers 4.22.1
  • Pytorch 1.12.1+cu113
  • Datasets 2.5.1
  • Tokenizers 0.12.1
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Dataset used to train gokuls/BERT-tiny-emotion-intent

Evaluation results