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TTC4900Model – AI Model by shivani05 | AlphaNeural AI
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shivani05
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TTC4900Model
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transformers
safetensors
bert
text-classification
generated_from_trainer
dbmdz/bert-base-turkish-uncased
finetune
mit
autotrain_compatible
endpoints_compatible
us
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TTC4900Model
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: 0.2304
Accuracy: 0.9341
F1: 0.8963
Precision: 0.9000
Recall: 0.8989
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: 5e-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
lr_scheduler_warmup_steps: 100
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
F1
Precision
Recall
2.581
0.88
50
2.0974
0.4317
0.2930
0.4400
0.3556
1.3915
1.75
100
0.6175
0.8590
0.8144
0.8008
0.8445
0.3808
2.63
150
0.3171
0.8767
0.8481
0.9359
0.8620
Framework versions
Transformers 4.35.2
Pytorch 2.1.0+cu118
Tokenizers 0.15.0
