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OCRganize-bert-finetuned-v1 – AI Model by MissAvery | AlphaNeural AI
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MissAvery
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OCRganize-bert-finetuned-v1
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transformers
tensorboard
safetensors
bert
token-classification
generated_from_trainer
google-bert/bert-base-german-cased
finetune
mit
autotrain_compatible
endpoints_compatible
us
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OCRganize-bert-finetuned-v1
This model is a fine-tuned version of
bert-base-german-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0006
Precision: 0.9998
Recall: 0.9996
F1: 0.9997
Accuracy: 0.9999
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: Use OptimizerNames.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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.0032
1.0
1000
0.0010
0.9984
0.9982
0.9983
0.9996
0.0016
2.0
2000
0.0009
0.9996
0.9991
0.9993
0.9999
0.0008
3.0
3000
0.0006
0.9998
0.9996
0.9997
0.9999
Framework versions
Transformers 4.50.0
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.2
