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bert-chinese-sentiment – AI Model by fish8180 | AlphaNeural AI
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fish8180
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bert-chinese-sentiment
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peft
tensorboard
safetensors
adapter
lora
transformers
google-bert/bert-base-chinese
adapter
apache-2.0
us
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bert-chinese-sentiment
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: 0.7466
Accuracy: 0.5
F1: 0.0
Precision: 0.0
Recall: 0.0
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: 0.0002
train_batch_size: 16
eval_batch_size: 32
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: 3
mixed_precision_training: Native AMP
Training results
Framework versions
PEFT 0.17.1
Transformers 4.56.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.0