---
library_name: transformers
license: mit
base_model: gpt2
tags:
- generated_from_keras_callback
model-index:
- name: turkishElectrick-mini-model
  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. -->

# turkishElectrick-mini-model

This model is a fine-tuned version of [gpt2](https://huggingface.co./gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.6456
- Validation Loss: 1.7437
- Epoch: 99

## 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': 'AdamWeightDecay', 'learning_rate': {'module': 'transformers.optimization_tf', 'class_name': 'WarmUp', 'config': {'initial_learning_rate': 5e-05, 'decay_schedule_fn': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': -981, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}, 'registered_name': 'WarmUp'}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 7.8609     | 7.6497          | 0     |
| 7.4033     | 6.9102          | 1     |
| 6.7940     | 6.4910          | 2     |
| 6.4110     | 6.1667          | 3     |
| 6.1566     | 5.9352          | 4     |
| 5.9535     | 5.7224          | 5     |
| 5.7576     | 5.5135          | 6     |
| 5.5523     | 5.2730          | 7     |
| 5.3273     | 5.0157          | 8     |
| 5.0893     | 4.7472          | 9     |
| 4.8421     | 4.4614          | 10    |
| 4.5883     | 4.1934          | 11    |
| 4.3480     | 3.9637          | 12    |
| 4.1266     | 3.7447          | 13    |
| 3.9195     | 3.5359          | 14    |
| 3.7044     | 3.3124          | 15    |
| 3.5097     | 3.1111          | 16    |
| 3.3371     | 2.9532          | 17    |
| 3.1614     | 2.7941          | 18    |
| 3.0044     | 2.6662          | 19    |
| 2.8511     | 2.5749          | 20    |
| 2.7244     | 2.4281          | 21    |
| 2.5806     | 2.3450          | 22    |
| 2.4819     | 2.2632          | 23    |
| 2.3593     | 2.1921          | 24    |
| 2.2577     | 2.1169          | 25    |
| 2.1563     | 2.0540          | 26    |
| 2.0613     | 2.0063          | 27    |
| 1.9667     | 1.9627          | 28    |
| 1.8827     | 1.9393          | 29    |
| 1.8151     | 1.8864          | 30    |
| 1.7214     | 1.8717          | 31    |
| 1.6412     | 1.8502          | 32    |
| 1.5774     | 1.7942          | 33    |
| 1.5114     | 1.7909          | 34    |
| 1.4588     | 1.7749          | 35    |
| 1.4006     | 1.7770          | 36    |
| 1.3340     | 1.7404          | 37    |
| 1.2674     | 1.7468          | 38    |
| 1.2138     | 1.7298          | 39    |
| 1.1611     | 1.7218          | 40    |
| 1.1231     | 1.7275          | 41    |
| 1.0758     | 1.7187          | 42    |
| 1.0199     | 1.7249          | 43    |
| 0.9813     | 1.6946          | 44    |
| 0.9286     | 1.7022          | 45    |
| 0.8793     | 1.7378          | 46    |
| 0.8404     | 1.6809          | 47    |
| 0.8028     | 1.7204          | 48    |
| 0.7706     | 1.7212          | 49    |
| 0.7406     | 1.7010          | 50    |
| 0.6994     | 1.7265          | 51    |
| 0.6785     | 1.7437          | 52    |
| 0.6438     | 1.7437          | 53    |
| 0.6456     | 1.7437          | 54    |
| 0.6406     | 1.7437          | 55    |
| 0.6422     | 1.7437          | 56    |
| 0.6453     | 1.7437          | 57    |
| 0.6428     | 1.7437          | 58    |
| 0.6454     | 1.7437          | 59    |
| 0.6477     | 1.7437          | 60    |
| 0.6438     | 1.7437          | 61    |
| 0.6477     | 1.7437          | 62    |
| 0.6462     | 1.7437          | 63    |
| 0.6461     | 1.7437          | 64    |
| 0.6469     | 1.7437          | 65    |
| 0.6448     | 1.7437          | 66    |
| 0.6450     | 1.7437          | 67    |
| 0.6469     | 1.7437          | 68    |
| 0.6407     | 1.7437          | 69    |
| 0.6492     | 1.7437          | 70    |
| 0.6410     | 1.7437          | 71    |
| 0.6445     | 1.7437          | 72    |
| 0.6385     | 1.7437          | 73    |
| 0.6413     | 1.7437          | 74    |
| 0.6397     | 1.7437          | 75    |
| 0.6456     | 1.7437          | 76    |
| 0.6403     | 1.7437          | 77    |
| 0.6439     | 1.7437          | 78    |
| 0.6398     | 1.7437          | 79    |
| 0.6415     | 1.7437          | 80    |
| 0.6431     | 1.7437          | 81    |
| 0.6421     | 1.7437          | 82    |
| 0.6423     | 1.7437          | 83    |
| 0.6454     | 1.7437          | 84    |
| 0.6406     | 1.7437          | 85    |
| 0.6440     | 1.7437          | 86    |
| 0.6423     | 1.7437          | 87    |
| 0.6431     | 1.7437          | 88    |
| 0.6448     | 1.7437          | 89    |
| 0.6436     | 1.7437          | 90    |
| 0.6362     | 1.7437          | 91    |
| 0.6445     | 1.7437          | 92    |
| 0.6407     | 1.7437          | 93    |
| 0.6410     | 1.7437          | 94    |
| 0.6431     | 1.7437          | 95    |
| 0.6434     | 1.7437          | 96    |
| 0.6415     | 1.7437          | 97    |
| 0.6438     | 1.7437          | 98    |
| 0.6456     | 1.7437          | 99    |


### Framework versions

- Transformers 4.44.2
- TensorFlow 2.17.0
- Datasets 3.0.0
- Tokenizers 0.19.1