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BERT_test_graident_accumulation_test4 – AI Model by BrianHsu | AlphaNeural AI
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BERT_test_graident_accumulation_test4
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transformers
tensorboard
safetensors
bert
multiple-choice
generated_from_trainer
google-bert/bert-base-chinese
finetune
endpoints_compatible
us
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BERT_test_graident_accumulation_test4
This model is a fine-tuned version of
bert-base-chinese
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.1752
Accuracy: 0.5781
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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
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
No log
1.0
116
1.0083
0.5586
No log
1.99
232
1.0274
0.5913
No log
2.99
348
1.1752
0.5781
Framework versions
Transformers 4.36.0
Pytorch 2.1.1+cu118
Datasets 2.15.0
Tokenizers 0.15.0
