Mattis0525/bert-base-chinese-finetuned-tcfd

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

• Train Loss: 0.6502
• Train Accuracy: 0.0591
• Validation Loss: 0.6504
• Validation Accuracy: 0.0591
• 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': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': -800, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: float32

Training results

Train Loss	Train Accuracy	Validation Loss	Validation Accuracy	Epoch
0.9480	0.0555	0.8742	0.0566	0
0.8735	0.0567	0.7660	0.0589	1
0.7694	0.0574	0.7093	0.0584	2
0.7190	0.0588	0.6563	0.0604	3
0.6720	0.0592	0.6636	0.0601	4
0.6479	0.0596	0.6639	0.0602	5
0.6446	0.0598	0.6266	0.0614	6
0.6257	0.0602	0.6393	0.0609	7
0.6534	0.0590	0.6301	0.0588	8
0.6502	0.0591	0.6504	0.0591	9

Framework versions

• Transformers 4.41.1
• TensorFlow 2.15.0
• Datasets 2.19.1
• Tokenizers 0.19.1