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HBERTv1_48_L10_H768_A12_emotion

This model is a fine-tuned version of gokuls/HBERTv1_48_L10_H768_A12 on the emotion dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3767
  • Accuracy: 0.894

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
1.0909 1.0 250 0.7130 0.719
0.4931 2.0 500 0.4298 0.8715
0.3355 3.0 750 0.3714 0.8895
0.2579 4.0 1000 0.3767 0.894
0.209 5.0 1250 0.3489 0.889
0.1749 6.0 1500 0.3507 0.8925
0.1406 7.0 1750 0.3585 0.891
0.1136 8.0 2000 0.4010 0.887
0.0926 9.0 2250 0.4301 0.893
0.0767 10.0 2500 0.4688 0.8935

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_L10_H768_A12_emotion

Evaluation results