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ntu_adl_paragraph_selection_model – AI Model by xjlulu | AlphaNeural AI
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ntu_adl_paragraph_selection_model
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transformers
pytorch
bert
multiple-choice
generated_from_trainer
google-bert/bert-base-chinese
finetune
endpoints_compatible
us
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ntu_adl_paragraph_selection_model
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: 0.2527
Accuracy: 0.9505
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: 3e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 2
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.2626
1.0
10857
0.2527
0.9505
Framework versions
Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.5
Tokenizers 0.14.1
