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---
library_name: transformers
license: mit
base_model: dbmdz/bert-base-turkish-cased
tags:
- generated_from_keras_callback
model-index:
- name: umutarpayy/bert_matematik_6
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# umutarpayy/bert_matematik_6
This model is a fine-tuned version of [dbmdz/bert-base-turkish-cased](https://huggingface.co/dbmdz/bert-base-turkish-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.2283
- Train Accuracy: 0.9475
- Validation Loss: 0.1557
- Validation Accuracy: 0.9614
- Epoch: 11
## 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:
- optimizer: {'name': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 9300, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
- training_precision: float32
### Training results
| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
| 3.0220 | 0.2760 | 1.7334 | 0.5717 | 0 |
| 1.5144 | 0.5985 | 1.1455 | 0.6699 | 1 |
| 1.1069 | 0.6872 | 0.8943 | 0.7295 | 2 |
| 0.8911 | 0.7434 | 0.6902 | 0.7931 | 3 |
| 0.7160 | 0.7937 | 0.5481 | 0.8486 | 4 |
| 0.5892 | 0.8327 | 0.4402 | 0.8744 | 5 |
| 0.4838 | 0.8665 | 0.3478 | 0.9010 | 6 |
| 0.4034 | 0.8944 | 0.2653 | 0.9300 | 7 |
| 0.3421 | 0.9069 | 0.2125 | 0.9436 | 8 |
| 0.2890 | 0.9263 | 0.1814 | 0.9549 | 9 |
| 0.2487 | 0.9384 | 0.1629 | 0.9589 | 10 |
| 0.2283 | 0.9475 | 0.1557 | 0.9614 | 11 |
### Framework versions
- Transformers 4.47.1
- TensorFlow 2.17.1
- Datasets 3.2.0
- Tokenizers 0.21.0
|