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