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bert-base-uncased-finetune – AI Model by ashishkumar0154 | AlphaNeural AI
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bert-base-uncased-finetune
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transformers
tensorboard
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-uncased-finetune
This model is a fine-tuned version of
bert-base-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 1.0235
Accuracy: 0.7882
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: 16
eval_batch_size: 16
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
0.7709
1.0
4597
0.6150
0.7628
0.3835
2.0
9194
0.6235
0.7856
0.1396
3.0
13791
1.0235
0.7882
Framework versions
Transformers 4.40.0
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.19.1
