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distilbert-base-uncased-fine-tuned-on-emotion-dataset
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: 0.2138
- Accuracy Score: 0.9275
- F1 Score: 0.9275
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 Score | F1 Score |
|---|---|---|---|---|---|
| 0.8024 | 1.0 | 250 | 0.3089 | 0.906 | 0.9021 |
| 0.2448 | 2.0 | 500 | 0.2138 | 0.9275 | 0.9275 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1
