distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1650
- Accuracy: 0.93
- F1: 0.9304
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.8057 | 1.0 | 250 | 0.2695 | 0.9175 | 0.9161 |
| 0.2096 | 2.0 | 500 | 0.1715 | 0.924 | 0.9241 |
| 0.1427 | 3.0 | 750 | 0.1650 | 0.93 | 0.9304 |
Framework versions
- Transformers 4.13.0
- Pytorch 1.12.1
- Datasets 1.16.1
- Tokenizers 0.10.3