bertweet-emotion-base
This model is a fine-tuned version of Bertweet. It achieves the following results on the evaluation set:
- Loss: 0.1172
- Accuracy: 0.945
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 80
- eval_batch_size: 80
- lr_scheduler_type: linear
- num_epochs: 6.0
Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu113
- Datasets 1.15.1
- Tokenizers 0.10.3
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Dataset used to train Emanuel/bertweet-emotion-base
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Evaluation results
- Accuracy on emotionself-reported0.945
- Accuracy on emotiontest set verified0.928
- Precision Macro on emotiontest set verified0.888
- Precision Micro on emotiontest set verified0.928
- Precision Weighted on emotiontest set verified0.929
- Recall Macro on emotiontest set verified0.886
- Recall Micro on emotiontest set verified0.928
- Recall Weighted on emotiontest set verified0.928
- F1 Macro on emotiontest set verified0.886
- F1 Micro on emotiontest set verified0.928
- F1 Weighted on emotiontest set verified0.928
- loss on emotiontest set verified0.135