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bert_base_uncased_ensemble_2 – AI Model by edwardyeung04 | AlphaNeural AI
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edwardyeung04
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bert_base_uncased_ensemble_2
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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_ensemble_2
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: 1.7949
Accuracy: 0.552
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: 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: 5
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
310
1.0565
0.546
0.9701
2.0
620
1.1190
0.58
0.9701
3.0
930
1.3406
0.556
0.4033
4.0
1240
1.6471
0.548
0.1509
5.0
1550
1.7949
0.552
Framework versions
Transformers 4.38.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2
