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bert-large-uncased-finetuned-bert-large-uncase-p2 – AI Model by jbdaniel | AlphaNeural AI
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jbdaniel
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bert-large-uncased-finetuned-bert-large-uncase-p2
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transformers
pytorch
tensorboard
bert
fill-mask
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-large-uncased-finetuned-bert-large-uncase-p2
This model is a fine-tuned version of
bert-large-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0980
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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
Training results
Training Loss
Epoch
Step
Validation Loss
0.1081
1.0
5696
0.0977
0.1008
2.0
11392
0.0980
Framework versions
Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2
