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weiweishi-roc-bert-base-zh – AI Model by daze-unlv | AlphaNeural AI
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weiweishi-roc-bert-base-zh
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transformers
tensorboard
safetensors
roc_bert
multiple-choice
generated_from_trainer
weiweishi/roc-bert-base-zh
finetune
endpoints_compatible
us
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weiweishi-roc-bert-base-zh
This model is a fine-tuned version of
weiweishi/roc-bert-base-zh
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.3863
Accuracy: 0.2601
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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
1.388
1.0
2857
1.3863
0.2584
1.3891
2.0
5714
1.3863
0.2608
1.3882
3.0
8571
1.3863
0.2601
Framework versions
Transformers 4.39.0.dev0
Pytorch 2.2.0+cu121
Datasets 2.18.0
Tokenizers 0.15.0
