---
library_name: transformers
license: mit
base_model: Labira/LabiraPJOK_2x_50
tags:
- generated_from_keras_callback
model-index:
- name: Labira/LabiraPJOK_3x_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_3x_50

This model is a fine-tuned version of [Labira/LabiraPJOK_2x_50](https://huggingface.co/Labira/LabiraPJOK_2x_50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0125
- Validation Loss: 1.5431
- Epoch: 49

## 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': 450, '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 |
|:----------:|:---------------:|:-----:|
| 2.7214     | 1.2242          | 0     |
| 1.5828     | 1.1158          | 1     |
| 0.9946     | 1.0677          | 2     |
| 0.7404     | 1.2115          | 3     |
| 0.5481     | 1.0920          | 4     |
| 0.3599     | 1.1031          | 5     |
| 0.2659     | 1.1035          | 6     |
| 0.2725     | 1.1251          | 7     |
| 0.2207     | 1.1364          | 8     |
| 0.1379     | 1.2039          | 9     |
| 0.1687     | 1.2331          | 10    |
| 0.1154     | 1.1677          | 11    |
| 0.1126     | 1.2093          | 12    |
| 0.0953     | 1.2532          | 13    |
| 0.0753     | 1.2455          | 14    |
| 0.0519     | 1.2544          | 15    |
| 0.0603     | 1.2511          | 16    |
| 0.0609     | 1.2736          | 17    |
| 0.0530     | 1.2692          | 18    |
| 0.0384     | 1.2869          | 19    |
| 0.0337     | 1.3048          | 20    |
| 0.0304     | 1.3314          | 21    |
| 0.0565     | 1.3378          | 22    |
| 0.0351     | 1.3842          | 23    |
| 0.0480     | 1.4148          | 24    |
| 0.0308     | 1.3959          | 25    |
| 0.0454     | 1.3768          | 26    |
| 0.0557     | 1.4469          | 27    |
| 0.0397     | 1.4431          | 28    |
| 0.0212     | 1.4441          | 29    |
| 0.0251     | 1.4262          | 30    |
| 0.0291     | 1.4412          | 31    |
| 0.0194     | 1.5155          | 32    |
| 0.0238     | 1.5136          | 33    |
| 0.0209     | 1.5002          | 34    |
| 0.0183     | 1.4976          | 35    |
| 0.0204     | 1.5533          | 36    |
| 0.0183     | 1.6057          | 37    |
| 0.0147     | 1.6047          | 38    |
| 0.0137     | 1.6029          | 39    |
| 0.0090     | 1.5879          | 40    |
| 0.0323     | 1.5802          | 41    |
| 0.0181     | 1.5748          | 42    |
| 0.0144     | 1.5629          | 43    |
| 0.0215     | 1.5534          | 44    |
| 0.0058     | 1.5442          | 45    |
| 0.0144     | 1.5485          | 46    |
| 0.0122     | 1.5449          | 47    |
| 0.0139     | 1.5428          | 48    |
| 0.0125     | 1.5431          | 49    |


### Framework versions

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