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udayGay/resume_model
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: 1.1040
- Validation Loss: 1.4298
- Train Accuracy: 0.6640
- Train Precision: 0.5589
- Train Recall: 0.5938
- Train F1: 0.5692
- Epoch: 29
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', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 1470, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
Training results
| Train Loss | Validation Loss | Train Accuracy | Train Precision | Train Recall | Train F1 | Epoch |
|---|---|---|---|---|---|---|
| 3.1654 | 3.1440 | 0.0402 | 0.0017 | 0.0417 | 0.0033 | 0 |
| 3.1553 | 3.1474 | 0.0282 | 0.0012 | 0.0417 | 0.0023 | 1 |
| 3.1208 | 3.0528 | 0.0805 | 0.0147 | 0.0812 | 0.0225 | 2 |
| 2.9896 | 2.8784 | 0.1469 | 0.0746 | 0.1384 | 0.0825 | 3 |
| 2.6886 | 2.5739 | 0.3300 | 0.2207 | 0.3033 | 0.2182 | 4 |
| 2.2855 | 2.1620 | 0.4547 | 0.3432 | 0.4138 | 0.3395 | 5 |
| 1.9018 | 1.9030 | 0.5151 | 0.4141 | 0.4679 | 0.4118 | 6 |
| 1.6218 | 1.7029 | 0.5795 | 0.4872 | 0.5205 | 0.4854 | 7 |
| 1.4058 | 1.5916 | 0.6217 | 0.5261 | 0.5595 | 0.5278 | 8 |
| 1.2705 | 1.4954 | 0.6479 | 0.5457 | 0.5815 | 0.5557 | 9 |
| 1.1692 | 1.4469 | 0.6600 | 0.5548 | 0.5896 | 0.5643 | 10 |
| 1.1179 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 11 |
| 1.1162 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 12 |
| 1.1109 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 13 |
| 1.1142 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 14 |
| 1.1095 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 15 |
| 1.1108 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 16 |
| 1.1133 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 17 |
| 1.1132 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 18 |
| 1.1064 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 19 |
| 1.1098 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 20 |
| 1.1029 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 21 |
| 1.1055 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 22 |
| 1.1125 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 23 |
| 1.1081 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 24 |
| 1.1125 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 25 |
| 1.1130 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 26 |
| 1.1101 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 27 |
| 1.1134 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 28 |
| 1.1040 | 1.4298 | 0.6640 | 0.5589 | 0.5938 | 0.5692 | 29 |
Framework versions
- Transformers 4.31.0
- TensorFlow 2.12.0
- Datasets 2.14.4
- Tokenizers 0.13.3
