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metadata
license: mit
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: model_TrainTestSplit_berturk_v2_24Feb
    results: []

model_TrainTestSplit_berturk_v2_24Feb

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: 0.0003
  • Precision: 0.9999
  • Recall: 0.9999
  • F1: 0.9999
  • Accuracy: 0.9999

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: 15

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
No log 1.0 196 0.0058 0.9982 0.9980 0.9981 0.9986
No log 2.0 392 0.0042 0.9987 0.9986 0.9986 0.9990
0.0132 3.0 588 0.0042 0.9985 0.9988 0.9986 0.9990
0.0132 4.0 784 0.0022 0.9993 0.9992 0.9992 0.9993
0.0132 5.0 980 0.0020 0.9993 0.9992 0.9993 0.9995
0.0069 6.0 1176 0.0013 0.9994 0.9994 0.9994 0.9995
0.0069 7.0 1372 0.0008 0.9997 0.9997 0.9997 0.9998
0.0035 8.0 1568 0.0008 0.9997 0.9997 0.9997 0.9998
0.0035 9.0 1764 0.0006 0.9996 0.9997 0.9996 0.9997
0.0035 10.0 1960 0.0004 0.9998 0.9999 0.9998 0.9999
0.0019 11.0 2156 0.0003 0.9999 0.9999 0.9999 0.9999
0.0019 12.0 2352 0.0003 0.9999 0.9999 0.9999 0.9999
0.0012 13.0 2548 0.0004 0.9999 0.9999 0.9999 0.9999
0.0012 14.0 2744 0.0003 0.9999 0.9999 0.9999 0.9999
0.0012 15.0 2940 0.0003 0.9999 0.9999 0.9999 0.9999

Framework versions

  • Transformers 4.26.1
  • Pytorch 1.13.1+cu116
  • Datasets 2.10.0
  • Tokenizers 0.13.2