imagine0711/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: 0.6361
• Train Accuracy: 0.0595
• Validation Loss: 0.6676
• Validation Accuracy: 0.0605
• 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': '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
0.9501	0.0559	0.8560	0.0569	0
0.8356	0.0571	0.7513	0.0585	1
0.7771	0.0584	0.7556	0.0602	2
0.6974	0.0590	0.6988	0.0589	3
0.6641	0.0599	0.5843	0.0609	4
0.6423	0.0599	0.6116	0.0605	5
0.6540	0.0596	0.6470	0.0605	6
0.6361	0.0595	0.6676	0.0605	7

Framework versions

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