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lernnavi_bert – AI Model by lucazed | AlphaNeural AI
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lucazed
/
lernnavi_bert
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transformers
pytorch
tensorboard
bert
fill-mask
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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lernnavi_bert
This model is a fine-tuned version of
dbmdz/bert-base-german-uncased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0228
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: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3.0
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.1036
1.0
782
0.0411
0.0384
2.0
1564
0.0251
0.0291
3.0
2346
0.0230
Framework versions
Transformers 4.29.1
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3
