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curated_merged_colon_dataset – AI Model by gmanzone | AlphaNeural AI | AlphaNeural AI
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curated_merged_colon_dataset
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transformers
safetensors
bert
token-classification
generated_from_trainer
google-bert/bert-base-german-cased
finetune
mit
endpoints_compatible
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curated_merged_colon_dataset
This model is a fine-tuned version of
google-bert/bert-base-german-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.0581
Precision: 0.9034
Recall: 0.9542
F1: 0.9281
Accuracy: 0.9951
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: 16
eval_batch_size: 16
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
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Precision
Recall
F1
Accuracy
0.0434
1.0
262
0.0233
0.914
0.9521
0.9327
0.9945
0.0206
2.0
524
0.0581
0.9034
0.9542
0.9281
0.9951
Framework versions
Transformers 4.49.0
Pytorch 2.8.0+cu126
Datasets 4.2.0
Tokenizers 0.21.4
