distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of distilbert-base-uncased on the emo dataset. It achieves the following results on the evaluation set:
- Loss: 0.3616
- Accuracy: 0.8708
- F1: 0.8824
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4841 | 1.0 | 472 | 0.3516 | 0.8695 | 0.8812 |
| 0.2767 | 2.0 | 944 | 0.3616 | 0.8708 | 0.8824 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.12.1