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bert_pretrained – AI Model by Kaspar | AlphaNeural AI
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Kaspar
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bert_pretrained
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transformers
safetensors
bert
fill-mask
generated_from_trainer
google-bert/bert-base-uncased
finetune
apache-2.0
endpoints_compatible
us
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bert_pretrained
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: 2.2565
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: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
2.5679
1.0
1123
2.4295
2.3683
2.0
2246
2.3089
2.3398
3.0
3369
2.2539
Framework versions
Transformers 4.57.6
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.2
