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viz-wiz-bert-base-uncased_f32 – AI Model by eisenjulian | AlphaNeural AI
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eisenjulian
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viz-wiz-bert-base-uncased_f32
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transformers
pytorch
bert
fill-mask
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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viz-wiz-bert-base-uncased_f32
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: 1.0723
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: 64
eval_batch_size: 32
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
No log
1.0
321
1.1645
1.344
2.0
642
1.0789
1.344
3.0
963
1.0537
1.1234
4.0
1284
1.0195
1.065
5.0
1605
1.0723
Framework versions
Transformers 4.33.2
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3
