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gBERT_sa_cv_9_fold1 – AI Model by DiederikMartens | AlphaNeural AI
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DiederikMartens
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gBERT_sa_cv_9_fold1
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transformers
tensorboard
safetensors
bert
text-classification
generated_from_trainer
google-bert/bert-base-german-cased
finetune
mit
autotrain_compatible
endpoints_compatible
us
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gBERT_sa_cv_9_fold1
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: 0.4921
F1: 0.7049
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: 4.47e-05
train_batch_size: 16
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
F1
No log
1.0
325
0.4068
0.5480
0.4456
2.0
650
0.4064
0.6868
0.4456
3.0
975
0.4921
0.7049
Framework versions
Transformers 4.41.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1
