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RuletakerBert – AI Model by nguyenthanhasia | AlphaNeural AI
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RuletakerBert
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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RuletakerBert
This model is a fine-tuned version of
bert-base-cased
on the Ruletaker dataset. It achieves the following results on the evaluation set:
Loss: 0.1587
Accuracy: 0.9312
Model description
This model is to verify the entailment relationship between two sentence
Intended uses & limitations
We use it for multple purpose, including RLLF
Training and evaluation data
Ruletaker dataset
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 2e-05
train_batch_size: 48
eval_batch_size: 48
seed: 42
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
0.1672
1.0
10004
0.1587
0.9312
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0
