metadata
library_name: transformers
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-ner-turkish-cased
results: []
bert-ner-turkish-cased
This model is a fine-tuned version of dbmdz/bert-base-turkish-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0987
- Precision: 0.9112
- Recall: 0.9364
- F1: 0.9236
- Accuracy: 0.9600
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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1351 | 1.0 | 1527 | 0.1158 | 0.8592 | 0.9070 | 0.8825 | 0.9517 |
| 0.1088 | 2.0 | 3054 | 0.1045 | 0.8787 | 0.9336 | 0.9053 | 0.9574 |
| 0.1016 | 3.0 | 4581 | 0.0993 | 0.8901 | 0.9280 | 0.9086 | 0.9576 |
| 0.1102 | 4.0 | 6108 | 0.0963 | 0.8991 | 0.9277 | 0.9132 | 0.9587 |
| 0.0877 | 5.0 | 7635 | 0.0953 | 0.9046 | 0.9292 | 0.9167 | 0.9584 |
| 0.0933 | 6.0 | 9162 | 0.0939 | 0.9036 | 0.9321 | 0.9176 | 0.9593 |
| 0.0827 | 7.0 | 10689 | 0.0967 | 0.8986 | 0.9398 | 0.9188 | 0.9605 |
| 0.0933 | 8.0 | 12216 | 0.0949 | 0.9122 | 0.9292 | 0.9206 | 0.9593 |
| 0.084 | 9.0 | 13743 | 0.0987 | 0.9112 | 0.9364 | 0.9236 | 0.9600 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0