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Randomized_Bert_Stacked_model_100 – AI Model by Ariffiq99 | AlphaNeural AI
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Randomized_Bert_Stacked_model_100
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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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Randomized_Bert_Stacked_model_100
This model is a fine-tuned version of
google-bert/bert-base-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.1038
F1: 0.5899
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: 64
eval_batch_size: 64
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
F1
1.0272
1.0
1576
1.0783
0.5897
1.0025
2.0
3152
1.0931
0.5869
0.9597
3.0
4728
1.0840
0.5904
0.9409
4.0
6304
1.1012
0.5902
0.918
5.0
7880
1.1038
0.5899
Framework versions
Transformers 4.44.2
Pytorch 2.5.0+cu121
Datasets 3.0.2
Tokenizers 0.19.1
