DearSola/my-awesome-model_1113

This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.1382
• Validation Loss: 0.3086
• Train Accuracy: 0.8771
• Train F1: 0.7370
• Train Precision: 0.7584
• Train Recall: 0.7168
• Epoch: 2

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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 675, '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	Train F1	Train Precision	Train Recall	Epoch
0.4029	0.3051	0.8618	0.6846	0.7579	0.6243	0
0.2311	0.2948	0.8701	0.7497	0.6983	0.8092	1
0.1382	0.3086	0.8771	0.7370	0.7584	0.7168	2

Framework versions

• Transformers 4.41.1
• TensorFlow 2.17.0
• Datasets 2.20.0
• Tokenizers 0.19.1