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Text Classification GoEmotions
This model is a fine-tuned version of roberta-large on the go_emotions dataset. It achieves the following results on the test set (with a threshold of 0.15):
- Accuracy: 0.4175
- Precision: 0.4934
- Recall: 0.5621
- F1: 0.5102
Code
Code for training this model can be found here.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- 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 | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|
| No log | 1.0 | 0.088978 | 0.404349 | 0.480763 | 0.456827 | 0.444685 |
| 0.10620 | 2.0 | 0.082806 | 0.411353 | 0.460896 | 0.536386 | 0.486819 |
| 0.10620 | 3.0 | 0.081338 | 0.420199 | 0.519828 | 0.561297 | 0.522716 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0
- Datasets 2.1.0
- Tokenizers 0.12.1
