---
library_name: transformers
license: mit
base_model: Labira/LabiraPJOK_5x_50
tags:
- generated_from_keras_callback
model-index:
- name: Labira/LabiraPJOK_6x_50
  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. -->

# Labira/LabiraPJOK_6x_50

This model is a fine-tuned version of [Labira/LabiraPJOK_5x_50](https://huggingface.co/Labira/LabiraPJOK_5x_50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.1155
- Validation Loss: 2.1395
- Epoch: 45

## 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': 150, '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 | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 2.0573     | 2.3329          | 0     |
| 1.3047     | 2.0503          | 1     |
| 1.1311     | 1.8969          | 2     |
| 0.4437     | 1.8286          | 3     |
| 0.4078     | 1.8199          | 4     |
| 0.5102     | 1.8192          | 5     |
| 0.4207     | 1.8550          | 6     |
| 0.2787     | 1.9171          | 7     |
| 0.4091     | 1.9373          | 8     |
| 0.3602     | 1.9061          | 9     |
| 0.2561     | 1.8889          | 10    |
| 0.2233     | 1.8902          | 11    |
| 0.2392     | 1.8824          | 12    |
| 0.1526     | 1.8853          | 13    |
| 0.1237     | 1.9106          | 14    |
| 0.1993     | 1.9339          | 15    |
| 0.3208     | 1.9720          | 16    |
| 0.1681     | 2.0189          | 17    |
| 0.1451     | 2.0625          | 18    |
| 0.2050     | 2.0801          | 19    |
| 0.1442     | 2.0687          | 20    |
| 0.2149     | 2.0457          | 21    |
| 0.1707     | 2.0365          | 22    |
| 0.1915     | 2.0288          | 23    |
| 0.1657     | 2.0256          | 24    |
| 0.1676     | 2.0323          | 25    |
| 0.1489     | 2.0413          | 26    |
| 0.1763     | 2.0559          | 27    |
| 0.0684     | 2.0698          | 28    |
| 0.1342     | 2.1025          | 29    |
| 0.1239     | 2.1459          | 30    |
| 0.0993     | 2.1898          | 31    |
| 0.1242     | 2.2285          | 32    |
| 0.1523     | 2.2495          | 33    |
| 0.1173     | 2.2643          | 34    |
| 0.2508     | 2.2549          | 35    |
| 0.0771     | 2.2329          | 36    |
| 0.0981     | 2.2178          | 37    |
| 0.1489     | 2.2089          | 38    |
| 0.1475     | 2.2051          | 39    |
| 0.0799     | 2.1896          | 40    |
| 0.0974     | 2.1739          | 41    |
| 0.2017     | 2.1636          | 42    |
| 0.1171     | 2.1517          | 43    |
| 0.0789     | 2.1435          | 44    |
| 0.1155     | 2.1395          | 45    |


### Framework versions

- Transformers 4.44.2
- TensorFlow 2.17.0
- Datasets 3.0.1
- Tokenizers 0.19.1