snar7/ooo_phrase
This model is a fine-tuned version of bert-large-uncased-whole-word-masking-finetuned-squad on a private dataset of out-of-office emails tagged with the exact phrase which contains the out-of-office context. It achieves the following results on the evaluation set:
- Eval Loss (during training): 0.2761, Epochs : 3
- Jaccard Score on a test set of tagged out-of-office phrases: ~ 94%
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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1140, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16
Training results
| Train Loss | Epoch |
|---|---|
| 0.5315 | 1 |
| 0.3629 | 2 |
| 0.2761 | 3 |
Framework versions
- Transformers 4.29.1
- TensorFlow 2.11.0
- Datasets 2.12.0
- Tokenizers 0.13.2
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