luiscunhacsc/masked-lm-tpu

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

• Train Loss: 9.8209
• Train Accuracy: 0.0113
• Validation Loss: 9.6999
• Validation Accuracy: 0.0188
• Epoch: 9

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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0001, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0001, 'decay_steps': 22325, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 1175, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.001}
• training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
10.2855	0.0000	10.2842	0.0	0
10.2729	0.0000	10.2651	0.0000	1
10.2599	0.0	10.2357	0.0000	2
10.2335	0.0	10.1943	0.0000	3
10.1915	0.0000	10.1447	0.0000	4
10.1449	0.0000	10.0705	0.0000	5
10.0750	0.0000	9.9926	0.0001	6
10.0099	0.0002	9.9074	0.0023	7
9.9197	0.0025	9.7964	0.0146	8
9.8209	0.0113	9.6999	0.0188	9

Framework versions

• Transformers 4.29.2
• TensorFlow 2.12.0
• Tokenizers 0.13.3