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HBERTv1_48_L8_H128_A2_emotion

This model is a fine-tuned version of gokuls/HBERTv1_48_L8_H128_A2 on the emotion dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3128
  • Accuracy: 0.892

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: 64
  • eval_batch_size: 64
  • seed: 33
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.4287 1.0 250 1.1300 0.5955
0.9053 2.0 500 0.6770 0.792
0.5736 3.0 750 0.5154 0.843
0.4098 4.0 1000 0.4139 0.867
0.3334 5.0 1250 0.3652 0.873
0.2874 6.0 1500 0.3259 0.8825
0.2462 7.0 1750 0.3138 0.89
0.2202 8.0 2000 0.3188 0.8895
0.1973 9.0 2250 0.3117 0.8915
0.1868 10.0 2500 0.3128 0.892

Framework versions

  • Transformers 4.34.0
  • Pytorch 1.14.0a0+410ce96
  • Datasets 2.14.5
  • Tokenizers 0.14.0
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Dataset used to train gokuls/HBERTv1_48_L8_H128_A2_emotion

Evaluation results