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distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of distilbert-base-uncased on the emotion dataset. It achieves the following results on the evaluation set:
- Loss: 0.1582
- Accuracy: 0.939
- F1: 0.9392
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 |
|---|---|---|---|---|---|
| 0.4977 | 1.0 | 1000 | 0.1919 | 0.9255 | 0.9253 |
| 0.1545 | 2.0 | 2000 | 0.1582 | 0.939 | 0.9392 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.8.1+cu102
- Datasets 1.17.0
- Tokenizers 0.10.3
