---
library_name: transformers
license: mit
base_model: Labira/LabiraPJOK_1_50
tags:
- generated_from_keras_callback
model-index:
- name: Labira/LabiraPJOK_2x_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_2x_50

This model is a fine-tuned version of [Labira/LabiraPJOK_1_50](https://huggingface.co/Labira/LabiraPJOK_1_50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 0.0131
- Validation Loss: 4.2318
- Epoch: 44

## 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': 250, '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 |
|:----------:|:---------------:|:-----:|
| 4.4264     | 3.9800          | 0     |
| 3.0757     | 3.5083          | 1     |
| 2.2362     | 3.1869          | 2     |
| 1.5246     | 2.7953          | 3     |
| 0.9065     | 2.8214          | 4     |
| 0.7330     | 3.3041          | 5     |
| 0.6050     | 3.4187          | 6     |
| 0.5238     | 3.4963          | 7     |
| 0.3471     | 3.4544          | 8     |
| 0.2836     | 3.1970          | 9     |
| 0.4074     | 3.1324          | 10    |
| 0.1832     | 3.2997          | 11    |
| 0.1899     | 3.5169          | 12    |
| 0.0939     | 3.5228          | 13    |
| 0.1638     | 3.3909          | 14    |
| 0.1055     | 3.4798          | 15    |
| 0.0827     | 3.6602          | 16    |
| 0.1070     | 3.7096          | 17    |
| 0.0751     | 3.7451          | 18    |
| 0.0449     | 3.7821          | 19    |
| 0.0299     | 3.8203          | 20    |
| 0.0505     | 3.8744          | 21    |
| 0.0247     | 3.9163          | 22    |
| 0.0534     | 3.9760          | 23    |
| 0.0442     | 4.0388          | 24    |
| 0.0211     | 4.0753          | 25    |
| 0.0216     | 4.0966          | 26    |
| 0.0219     | 4.1131          | 27    |
| 0.0234     | 4.1117          | 28    |
| 0.0255     | 4.1391          | 29    |
| 0.0199     | 4.1682          | 30    |
| 0.0196     | 4.1973          | 31    |
| 0.0317     | 4.2302          | 32    |
| 0.0263     | 4.2538          | 33    |
| 0.0322     | 4.2648          | 34    |
| 0.0171     | 4.2541          | 35    |
| 0.0200     | 4.2429          | 36    |
| 0.0201     | 4.2240          | 37    |
| 0.0331     | 4.1675          | 38    |
| 0.0220     | 4.1519          | 39    |
| 0.0158     | 4.1661          | 40    |
| 0.0131     | 4.1824          | 41    |
| 0.0174     | 4.2002          | 42    |
| 0.0170     | 4.2208          | 43    |
| 0.0131     | 4.2318          | 44    |


### Framework versions

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