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letingliu/my_awesome_model_tweets
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: 0.5490
- Validation Loss: 0.5429
- Train Accuracy: 0.6692
- Epoch: 19
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': False, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 40, '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 | Epoch |
---|---|---|---|
0.6582 | 0.6337 | 0.6692 | 0 |
0.6230 | 0.6035 | 0.6692 | 1 |
0.6015 | 0.5766 | 0.6692 | 2 |
0.5738 | 0.5533 | 0.6692 | 3 |
0.5540 | 0.5429 | 0.6692 | 4 |
0.5534 | 0.5429 | 0.6692 | 5 |
0.5515 | 0.5429 | 0.6692 | 6 |
0.5524 | 0.5429 | 0.6692 | 7 |
0.5455 | 0.5429 | 0.6692 | 8 |
0.5463 | 0.5429 | 0.6692 | 9 |
0.5380 | 0.5429 | 0.6692 | 10 |
0.5494 | 0.5429 | 0.6692 | 11 |
0.5467 | 0.5429 | 0.6692 | 12 |
0.5382 | 0.5429 | 0.6692 | 13 |
0.5562 | 0.5429 | 0.6692 | 14 |
0.5517 | 0.5429 | 0.6692 | 15 |
0.5462 | 0.5429 | 0.6692 | 16 |
0.5456 | 0.5429 | 0.6692 | 17 |
0.5499 | 0.5429 | 0.6692 | 18 |
0.5490 | 0.5429 | 0.6692 | 19 |
Framework versions
- Transformers 4.27.4
- TensorFlow 2.12.0
- Datasets 2.11.0
- Tokenizers 0.13.2