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bert-base – AI Model by TheNewPing | AlphaNeural AI
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TheNewPing
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bert-base
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transformers
safetensors
bert
multiple-choice
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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bert-base
This model is a fine-tuned version of
bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5726
Accuracy: 0.6855
Precision: 0.6780
Recall: 0.7066
F1: 0.6920
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: 1e-05
train_batch_size: 32
eval_batch_size: 32
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
Precision
Recall
F1
0.6944
1.0
1074
0.6932
0.4921
0.4901
0.3924
0.4359
0.6935
2.0
2148
0.6914
0.5337
0.5443
0.4139
0.4702
0.5977
3.0
3222
0.5726
0.6855
0.6780
0.7066
0.6920
Framework versions
Transformers 4.36.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0
