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ckiplab-bert-base-chinese-DottedWSD – AI Model by lopentu | AlphaNeural AI
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ckiplab-bert-base-chinese-DottedWSD
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transformers
safetensors
bert
text-classification
generated_from_trainer
ckiplab/bert-base-chinese
finetune
gpl-3.0
text-embeddings-inference
endpoints_compatible
us
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ckiplab-bert-base-chinese-DottedWSD
This model is a fine-tuned version of
ckiplab/bert-base-chinese
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.1319
Accuracy: 0.9554
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: 5e-05
train_batch_size: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 512
optimizer: Use adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.1444
0.9997
770
0.1318
0.9464
0.1027
1.9994
1540
0.1224
0.9537
0.0761
2.9990
2310
0.1319
0.9554
Framework versions
Transformers 4.46.2
Pytorch 2.5.0+cu121
Datasets 3.0.1
Tokenizers 0.20.1
