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bert-chinese-weibo-30p-v4 – AI Model by AnonymousCS | AlphaNeural AI
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bert-chinese-weibo-30p-v4
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transformers
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-chinese
finetune
apache-2.0
text-embeddings-inference
endpoints_compatible
us
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bert-chinese-weibo-30p-v4
This model is a fine-tuned version of
google-bert/bert-base-chinese
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2982
Accuracy: 0.9470
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: 128
eval_batch_size: 256
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 4
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
21
0.3315
0.9252
No log
2.0
42
0.2920
0.9502
No log
3.0
63
0.3029
0.9377
No log
4.0
84
0.2982
0.9470
Framework versions
Transformers 5.0.0
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.2
