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my_awesome_wnut_model – AI Model by Buseak | AlphaNeural AI
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Buseak
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my_awesome_wnut_model
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transformers
pytorch
tensorboard
bert
token-classification
generated_from_trainer
mit
autotrain_compatible
endpoints_compatible
us
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my_awesome_wnut_model
This model is a fine-tuned version of
dbmdz/bert-base-turkish-cased
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.2661
Precision: 0.8999
Recall: 0.8933
F1: 0.8966
Accuracy: 0.9264
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: 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
Precision
Recall
F1
Accuracy
No log
1.0
488
0.3614
0.8731
0.8606
0.8668
0.9043
0.6843
2.0
976
0.2872
0.8927
0.8856
0.8891
0.9209
0.3517
3.0
1464
0.2661
0.8999
0.8933
0.8966
0.9264
Framework versions
Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2
