tfmodel

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: 0.1456
• Train Sparse Categorical Accuracy: 0.9391
• Validation Loss: 0.1419
• Validation Sparse Categorical Accuracy: 0.9400
• Epoch: 1

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': 5e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Train Sparse Categorical Accuracy	Validation Loss	Validation Sparse Categorical Accuracy	Epoch
0.5263	0.8181	0.1763	0.9280	0
0.1456	0.9391	0.1419	0.9400	1

Framework versions

• Transformers 4.48.3
• TensorFlow 2.18.0
• Datasets 3.3.2
• Tokenizers 0.21.0