tl-test-learn-prompt-classifier

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: 0.0794
• Train Accuracy: 1.0
• Validation Loss: 0.2381
• Validation Accuracy: 0.9444
• Epoch: 5

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

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
0.6829	0.5808	0.6541	0.7639	0
0.6315	0.7784	0.5824	0.8472	1
0.4975	0.9222	0.4382	0.8889	2
0.3094	0.9521	0.3303	0.9028	3
0.1684	0.9820	0.2741	0.9028	4
0.0794	1.0	0.2381	0.9444	5

Framework versions

• Transformers 4.46.2
• TensorFlow 2.17.1
• Datasets 3.1.0
• Tokenizers 0.20.3