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emotion_classification

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

  • Loss: 1.6119
  • F1: 0.3852

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss F1
No log 1.0 313 1.8826 0.1762
2.1614 2.0 626 1.6738 0.3442
2.1614 3.0 939 1.6119 0.3852

Framework versions

  • Transformers 4.28.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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Dataset used to train imrazaa/emotion_classification

Evaluation results