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: 0.0934
• Train Accuracy: 0.9923
• Validation Loss: 0.2064
• Validation Accuracy: 0.9196
• Epoch: 7

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': 5e-06, '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
0.6893	0.5367	0.6705	0.5536	0
0.6573	0.6911	0.6171	0.8125	1
0.5946	0.7876	0.5066	0.9196	2
0.4681	0.9035	0.3703	0.9107	3
0.3276	0.9266	0.2682	0.9286	4
0.2147	0.9614	0.2311	0.9196	5
0.1356	0.9768	0.2067	0.9286	6
0.0934	0.9923	0.2064	0.9196	7

Framework versions

• Transformers 4.44.2
• TensorFlow 2.18.0-dev20240717
• Datasets 2.21.0
• Tokenizers 0.19.1