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bert-base-combined-large – AI Model by asparius | AlphaNeural AI
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asparius
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bert-base-combined-large
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transformers
pytorch
tensorboard
safetensors
bert
text-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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bert-base-combined-large
This model is a fine-tuned version of
dbmdz/bert-base-turkish-uncased
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.3029
Accuracy: 0.8940
F1: 0.8956
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: 32
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
Accuracy
F1
0.2668
1.0
3077
0.2812
0.8931
0.8915
0.2042
2.0
6154
0.2675
0.8952
0.8950
0.1453
3.0
9231
0.3029
0.8940
0.8956
Framework versions
Transformers 4.21.2
Pytorch 1.12.1+cu102
Datasets 2.4.0
Tokenizers 0.12.1
