bert-base-chinese-SSEC – AI Model by hw2942 | AlphaNeural AI

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hw2942/
bert-base-chinese-SSEC

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text-classification

generated_from_trainer

google-bert/bert-base-chinese

autotrain_compatible

endpoints_compatible

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bert-base-chinese-wallstreetcn-morning-news-market-overview-SSEC-v3

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

Loss: 3.1007
Accuracy: 0.6875

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:

learning_rate: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	34	2.2173	0.7188
No log	2.0	68	1.8368	0.7188
No log	3.0	102	2.7822	0.625
No log	4.0	136	2.3597	0.7188
No log	5.0	170	3.3032	0.5312
No log	6.0	204	2.9527	0.6562
No log	7.0	238	2.7575	0.6875
No log	8.0	272	2.9714	0.6875
No log	9.0	306	3.0941	0.6875
No log	10.0	340	3.1007	0.6875

Framework versions

Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3