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twitter-emotion-classifier-BERT
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.1487
- Train Sparse Categorical Accuracy: 0.9374
- Validation Loss: 0.1447
- Validation Sparse Categorical Accuracy: 0.9390
- Epoch: 1
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:
- optimizer: {'name': 'Adam', 'learning_rate': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
|---|---|---|---|---|
| 0.5268 | 0.8156 | 0.2002 | 0.9265 | 0 |
| 0.1487 | 0.9374 | 0.1447 | 0.9390 | 1 |
Framework versions
- Transformers 4.22.2
- TensorFlow 2.8.2
- Datasets 2.5.2
- Tokenizers 0.12.1
