distilbert-base-uncased-finetuned-emo
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3127
- Accuracy: 0.8775
- F1: 0.8775
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4049 | 1.0 | 500 | 0.3183 | 0.8655 | 0.8653 |
| 0.247 | 2.0 | 1000 | 0.3127 | 0.8775 | 0.8775 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.0
- Datasets 2.13.0
- Tokenizers 0.13.3