results

This model is a fine-tuned version of akdeniz27/bert-base-turkish-cased-ner on the None dataset. It achieves the following results on the evaluation set:

• Loss: 8.5343

• Accuracy: 0.1071

• F1: 0.1212

• Classification Report: precision recall f1-score support

    DATE       0.07      0.67      0.13         3
  

  LOCATION 0.00 0.00 0.00 1 PERSON 0.00 0.00 0.00 1 micro avg 0.07 0.40 0.12 5 macro avg 0.02 0.22 0.04 5

weighted avg 0.04 0.40 0.08 5

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: 8
• eval_batch_size: 8
• 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	Classification Report
No log	1.0	1	10.3125	0.1071	0.1212	precision recall f1-score support

    DATE       0.07      0.67      0.13         3
LOCATION       0.00      0.00      0.00         1
  PERSON       0.00      0.00      0.00         1

micro avg 0.07 0.40 0.12 5 macro avg 0.02 0.22 0.04 5 weighted avg 0.04 0.40 0.08 5 | | No log | 2.0 | 2 | 9.1622 | 0.1071 | 0.1212 | precision recall f1-score support

    DATE       0.07      0.67      0.13         3
LOCATION       0.00      0.00      0.00         1
  PERSON       0.00      0.00      0.00         1

micro avg 0.07 0.40 0.12 5 macro avg 0.02 0.22 0.04 5 weighted avg 0.04 0.40 0.08 5 | | No log | 3.0 | 3 | 8.5343 | 0.1071 | 0.1212 | precision recall f1-score support

    DATE       0.07      0.67      0.13         3
LOCATION       0.00      0.00      0.00         1
  PERSON       0.00      0.00      0.00         1

micro avg 0.07 0.40 0.12 5 macro avg 0.02 0.22 0.04 5 weighted avg 0.04 0.40 0.08 5 |

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1