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vedantjumle/indo-ml-final-test-xlnet-1
This model is a fine-tuned version of xlnet-large-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.7254
- Validation Loss: 0.6440
- Train Accuracy: 0.88
- Epoch: 9
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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 6000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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 | Epoch |
|---|---|---|---|
| 5.1411 | 5.0487 | 0.01 | 0 |
| 5.0561 | 4.8924 | 0.0267 | 1 |
| 4.8362 | 4.4063 | 0.2033 | 2 |
| 4.2361 | 3.4961 | 0.45 | 3 |
| 3.3575 | 2.5506 | 0.6167 | 4 |
| 2.5070 | 1.8625 | 0.74 | 5 |
| 1.8507 | 1.3431 | 0.8067 | 6 |
| 1.3367 | 0.9980 | 0.84 | 7 |
| 0.9787 | 0.7747 | 0.86 | 8 |
| 0.7254 | 0.6440 | 0.88 | 9 |
Framework versions
- Transformers 4.34.0
- TensorFlow 2.13.0
- Datasets 2.14.5
- Tokenizers 0.14.1
