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bert-finetuned-ner_best-Hyperparameter – AI Model by RikvanSchaick | AlphaNeural AI
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bert-finetuned-ner_best-Hyperparameter
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
google-bert/bert-base-cased
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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bert-finetuned-ner_best-Hyperparameter
This model is a fine-tuned version of
bert-base-cased
on the None dataset.
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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
No log
1.0
7
0.3651
Framework versions
Transformers 4.46.2
Pytorch 2.5.0+cu121
Datasets 3.1.0
Tokenizers 0.20.3
